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Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

Avg.salinity(ppt) Femalecrabnumber  

E-Print Network (OSTI)

NERR quarterly for 11 time periods at 9 stations across a salinity gradient in the Ashpoo (green0 5 10 15 20 25 0 50 100 150 200 250 300 Avg.salinity(ppt) Femalecrabnumber > 25 ppt 15-25 ppt ppt Salinity 0 5 10 15 20 25 0 50 100 150 200 250 300 Avg.salinity(ppt) Malecrabnumber > 25 ppt 15

Childress, Michael J.

2

AVG Koeln GmbH | Open Energy Information  

Open Energy Info (EERE)

AVG Koeln GmbH Jump to: navigation, search Name: AVG Koeln GmbH Place: Kln, Germany Zip: 50735 Product: Operating a Waste-to-Energy facility in Kln, Germany. References:...

3

max kwh | OpenEI Community  

Open Energy Info (EERE)

max kwh max kwh Home Ewilson's picture Submitted by Ewilson(53) Contributor 4 January, 2013 - 08:42 Rates with tier problems max kwh tiers I've detected that the following rates all have the improper number of "Max kWh" values (should be one less than the number of charges, since the highest tier is always "all remaining"). This is likely due to users not understanding the meaning of "Max kWh"--often I see things like: "300, 700, 1000" (derived from "first 300, next 700, greater than 1000") which should be entered as "300, 1000". This is why we need checks on input that prevent users from entering this incorrectly. Here is the list (my script only checked residential rates): Syndicate content 429 Throttled (bot load)

4

kWh | OpenEI  

Open Energy Info (EERE)

kWh kWh Dataset Summary Description This dataset contains hourly load profile data for 16 commercial building types (based off the DOE commercial reference building models) and residential buildings (based off the Building America House Simulation Protocols). This dataset also includes the Residential Energy Consumption Survey (RECS) for statistical references of building types by location. Source Commercial and Residential Reference Building Models Date Released April 18th, 2013 (9 months ago) Date Updated July 02nd, 2013 (7 months ago) Keywords building building demand building load Commercial data demand Energy Consumption energy data hourly kWh load profiles Residential Data Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage Frequency Annually

5

Property:AvgAnnlGrossOpCpcty | Open Energy Information  

Open Energy Info (EERE)

AvgAnnlGrossOpCpcty AvgAnnlGrossOpCpcty Jump to: navigation, search Property Name AvgAnnlGrossOpCpcty Property Type Number Description Avg. Annual Gross Operating Capacity(MW). Pages using the property "AvgAnnlGrossOpCpcty" Showing 6 pages using this property. F Faulkner I Energy Generation Facility + 49.5 + N Navy I Geothermal Facility + 81.7 + Navy II Geothermal Facility + 86 + Neal Hot Springs Geothermal Power Plant + 22 + North Brawley Geothermal Power Plant + 50 + R Raft River Geothermal Facility + 11.5 + Retrieved from "http://en.openei.org/w/index.php?title=Property:AvgAnnlGrossOpCpcty&oldid=400186#SMWResults" Categories: Properties Geothermal Energy Generation Facilities properties What links here Related changes Special pages Printable version

6

Property:AvgGeoFluidTemp | Open Energy Information  

Open Energy Info (EERE)

AvgGeoFluidTemp AvgGeoFluidTemp Jump to: navigation, search Property Name AvgGeoFluidTemp Property Type Temperature Description Average temperature of geofluid in a geothermal area. Subproperties This property has the following 15 subproperties: B Beowawe Hot Springs Geothermal Area Brady Hot Springs Geothermal Area C Chena Geothermal Area D Desert Peak Geothermal Area E East Mesa Geothermal Area G Geysers Geothermal Area H Heber Geothermal Area L Lightning Dock Geothermal Area R Roosevelt Hot Springs Geothermal Area S Salton Sea Geothermal Area San Emidio Desert Geothermal Area S cont. Soda Lake Geothermal Area Steamboat Springs Geothermal Area Stillwater Geothermal Area W Wabuska Hot Springs Geothermal Area Pages using the property "AvgGeoFluidTemp" Showing 10 pages using this property.

7

Property:AvgReservoirDepth | Open Energy Information  

Open Energy Info (EERE)

AvgReservoirDepth AvgReservoirDepth Jump to: navigation, search Property Name AvgReservoirDepth Property Type Quantity Description Average depth to reservoir Use this type to express a quantity of length. The default unit is the meter (m). Acceptable units (and their conversions) are: Meters - 1 m, meter, meters Meter, Meters, METER, METERS Kilometers - 0.001 km, kilometer, kilometers, Kilometer, Kilometers, KILOMETERS, KILOMETERS Miles - 0.000621371 mi, mile, miles, Mile, Miles, MILE, MILES Feet - 3.28084 ft, foot, feet, Foot, Feet, FOOT, FEET Yards - 1.09361 yd, yard, yards, Yard, Yards, YARD, YARDS Pages using the property "AvgReservoirDepth" Showing 24 pages using this property. A Amedee Geothermal Area + 213 m0.213 km 0.132 mi 698.819 ft 232.939 yd + B Beowawe Hot Springs Geothermal Area + 850 m0.85 km

8

Property:Incentive/PVComFitDolKWh | Open Energy Information  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:Incentive/PVComFitDolKWh Jump to: navigation, search Property Name Incentive/PVComFitDolKWh Property Type String Description Feed-in tariff for commercial systems. The $ amount per kWh generated such that the incentive is disbursed over time based on metered production. 100% of energy generated is exported; none is used on-site. Ex: TVA Green Power Switch $0.15/kWh; We Energies $0.225/kWh Format: $0.225 [1] References ↑ DSIRE Pages using the property "Incentive/PVComFitDolKWh" Showing 25 pages using this property. (previous 25) (next 25) A Alliant Energy (Wisconsin Power and Light) - Advanced Renewables Tariff (Wisconsin) + $0.25 + C CPS Energy - Solartricity Producer Program (Texas) + $0.27 +

9

Property:Incentive/PVResFitDolKWh | Open Energy Information  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:Incentive/PVResFitDolKWh Jump to: navigation, search Property Name Incentive/PVResFitDolKWh Property Type String Description Feed-in Tariff (FIT): The $ amount per kWh generated such that the incentive is disbursed over time based on metered production. 100% of energy generated is exported; none is used on-site. Ex: TVA Green Power Switch $0.15/kWh; We Energies $0.225/kWh Format: $0.225 [1] References ↑ DSIRE Pages using the property "Incentive/PVResFitDolKWh" Showing 25 pages using this property. (previous 25) (next 25) A Alliant Energy (Wisconsin Power and Light) - Advanced Renewables Tariff (Wisconsin) + $0.25 + C CPS Energy - Solartricity Producer Program (Texas) + $0.27 +

10

Property:Incentive/PVNPFitDolKWh | Open Energy Information  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:Incentive/PVNPFitDolKWh Jump to: navigation, search Property Name Incentive/PVNPFitDolKWh Property Type String Description Feed-in tariff for non-profit and/or government systems. The $ amount per kWh generated such that the incentive is disbursed over time based on metered production. 100% of energy generated is exported; none is used on-site. Ex: TVA Green Power Switch $0.15/kWh; We Energies $0.225/kWh Format: $0.225 [1] References ↑ DSIRE Pages using the property "Incentive/PVNPFitDolKWh" Showing 25 pages using this property. (previous 25) (next 25) A Alliant Energy (Wisconsin Power and Light) - Advanced Renewables Tariff (Wisconsin) + $0.25 + C CPS Energy - Solartricity Producer Program (Texas) + $0.27 +

11

Property:IndustrialAvgRate | Open Energy Information  

Open Energy Info (EERE)

IndustrialAvgRate IndustrialAvgRate Jump to: navigation, search Property Name IndustrialAvgRate Property Type Number Description Industrial Average Rate Subproperties This property has the following 279 subproperties: A AEP Generating Company AEP Texas Central Company AEP Texas North Company AES Eastern Energy LP APN Starfirst, L.P. Accent Energy Holdings, LLC Alabama Municipal Elec Authority Alaska Electric & Energy Coop Alaska Energy Authority Alaska Power and Telephone Co Allegheny Electric Coop Inc Alliant Energy Ameren Energy Marketing Ameren Illinois Company American Electric Power Co., Inc. American Mun Power-Ohio, Inc American Samoa Power Authority American Transmission Systems Inc Anoka Electric Coop Appalachian Power Co Aquila Inc Aquila Inc (Missouri) Arizona Electric Pwr Coop Inc

12

Property:CommercialAvgRate | Open Energy Information  

Open Energy Info (EERE)

CommercialAvgRate CommercialAvgRate Jump to: navigation, search Property Name CommercialAvgRate Property Type Number Description Commercial Average Rate Subproperties This property has the following 279 subproperties: A AEP Generating Company AEP Texas Central Company AEP Texas North Company AES Eastern Energy LP APN Starfirst, L.P. Accent Energy Holdings, LLC Alabama Municipal Elec Authority Alaska Electric & Energy Coop Alaska Energy Authority Alaska Power and Telephone Co Allegheny Electric Coop Inc Alliant Energy Ameren Energy Marketing Ameren Illinois Company American Electric Power Co., Inc. American Mun Power-Ohio, Inc American Samoa Power Authority American Transmission Systems Inc Anoka Electric Coop Appalachian Power Co Aquila Inc Aquila Inc (Missouri) Arizona Electric Pwr Coop Inc

13

Property:Building/SPBreakdownOfElctrcityUseKwhM2Total | Open Energy  

Open Energy Info (EERE)

SPBreakdownOfElctrcityUseKwhM2Total" SPBreakdownOfElctrcityUseKwhM2Total" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 71.4577086539 + Sweden Building 05K0002 + 110.926946534 + Sweden Building 05K0003 + 72.9096074806 + Sweden Building 05K0004 + 66.0248923654 + Sweden Building 05K0005 + 54.8654809632 + Sweden Building 05K0006 + 65.291976787 + Sweden Building 05K0007 + 65.5403331042 + Sweden Building 05K0008 + 41.6418235453 + Sweden Building 05K0009 + 56.5413268466 + Sweden Building 05K0010 + 150.269021739 + Sweden Building 05K0011 + 27.5018481341 + Sweden Building 05K0012 + 37.9937990385 + Sweden Building 05K0013 + 68.8990371973 + Sweden Building 05K0014 + 166.794253904 + Sweden Building 05K0015 + 71.0813662687 + Sweden Building 05K0016 + 38.5267410327 +

14

Property:Building/SPPurchasedEngyPerAreaKwhM2Total | Open Energy  

Open Energy Info (EERE)

SPPurchasedEngyPerAreaKwhM2Total" SPPurchasedEngyPerAreaKwhM2Total" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 221.549575215 + Sweden Building 05K0002 + 213.701117318 + Sweden Building 05K0003 + 195.801526718 + Sweden Building 05K0004 + 174.148148148 + Sweden Building 05K0005 + 340.088495575 + Sweden Building 05K0006 + 211.255924171 + Sweden Building 05K0007 + 144.028151521 + Sweden Building 05K0008 + 171.282051282 + Sweden Building 05K0009 + 140.296360236 + Sweden Building 05K0010 + 300.961098398 + Sweden Building 05K0011 + 98.1045751634 + Sweden Building 05K0012 + 106.609793929 + Sweden Building 05K0013 + 175.776187637 + Sweden Building 05K0014 + 291.160427408 + Sweden Building 05K0015 + 174.193548387 + Sweden Building 05K0016 + 145.793794187 +

15

Property:Building/SPPurchasedEngyPerAreaKwhM2DstrtHeating | Open Energy  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:Building/SPPurchasedEngyPerAreaKwhM2DstrtHeating Jump to: navigation, search This is a property of type String. District heating Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2DstrtHeating" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 111.56331078 + Sweden Building 05K0002 + 72.7932960894 + Sweden Building 05K0003 + 111.899416255 + Sweden Building 05K0004 + 72.865497076 + Sweden Building 05K0005 + 285.840707965 + Sweden Building 05K0006 + 128.449958182 + Sweden Building 05K0007 + 63.8377147588 + Sweden Building 05K0008 + 115.128205128 + Sweden Building 05K0009 + 66.5515753129 + Sweden Building 05K0010 + 148.741418764 +

16

Property:Building/SPBreakdownOfElctrcityUseKwhM2Misc | Open Energy  

Open Energy Info (EERE)

SPBreakdownOfElctrcityUseKwhM2Misc SPBreakdownOfElctrcityUseKwhM2Misc Jump to: navigation, search This is a property of type String. Miscellaneous Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Misc" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 9.09953195331 + Sweden Building 05K0003 + 8.78442379242 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 12.9530389597 + Sweden Building 05K0008 + 6.03377747253 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 10.9950724049 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 14.2856105095 + Sweden Building 05K0014 + 27.8718727739 +

17

Property:Building/SPPurchasedEngyPerAreaKwhM2Oil-FiredBoiler | Open Energy  

Open Energy Info (EERE)

SPPurchasedEngyPerAreaKwhM2Oil-FiredBoiler SPPurchasedEngyPerAreaKwhM2Oil-FiredBoiler Jump to: navigation, search This is a property of type String. Oil-fired boiler Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2Oil-FiredBoiler" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 +

18

Property:Building/SPBreakdownOfElctrcityUseKwhM2HeatPumps | Open Energy  

Open Energy Info (EERE)

SPBreakdownOfElctrcityUseKwhM2HeatPumps SPBreakdownOfElctrcityUseKwhM2HeatPumps Jump to: navigation, search This is a property of type String. Heat pumps Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2HeatPumps" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 +

19

Property:Building/SPPurchasedEngyPerAreaKwhM2ElctrcHeating | Open Energy  

Open Energy Info (EERE)

SPPurchasedEngyPerAreaKwhM2ElctrcHeating" SPPurchasedEngyPerAreaKwhM2ElctrcHeating" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.915704329247 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.745132743363 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 25.8064516129 + Sweden Building 05K0016 + 5.89159465829 + Sweden Building 05K0017 + 0.0 + Sweden Building 05K0018 + 0.0 + Sweden Building 05K0019 + 0.0 +

20

Property:Building/SPBreakdownOfElctrcityUseKwhM2ElctrcHeating | Open Energy  

Open Energy Info (EERE)

SPBreakdownOfElctrcityUseKwhM2ElctrcHeating" SPBreakdownOfElctrcityUseKwhM2ElctrcHeating" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.915704329247 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.745132743363 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 25.8064516129 + Sweden Building 05K0016 + 5.89159465829 + Sweden Building 05K0017 + 0.0 + Sweden Building 05K0018 + 0.0 + Sweden Building 05K0019 + 0.0 +

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Property:Building/SPPurchasedEngyPerAreaKwhM2OtherElctrty | Open Energy  

Open Energy Info (EERE)

OtherElctrty OtherElctrty Jump to: navigation, search This is a property of type String. Other electricity Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2OtherElctrty" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 70.305743501 + Sweden Building 05K0002 + 95.9357541899 + Sweden Building 05K0003 + 72.2496632241 + Sweden Building 05K0004 + 65.8830409357 + Sweden Building 05K0005 + 53.5026548673 + Sweden Building 05K0006 + 58.7608028994 + Sweden Building 05K0007 + 61.5607534672 + Sweden Building 05K0008 + 40.3846153846 + Sweden Building 05K0009 + 56.4810818587 + Sweden Building 05K0010 + 152.219679634 + Sweden Building 05K0011 + 25.5555555556 + Sweden Building 05K0012 + 35.8807888323 + Sweden Building 05K0013 + 61.3267863536 +

22

Property:Building/SPBreakdownOfElctrcityUseKwhM2Pumps | Open Energy  

Open Energy Info (EERE)

Pumps Pumps Jump to: navigation, search This is a property of type String. Pumps Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Pumps" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 6.37190900733 + Sweden Building 05K0002 + 6.03888185355 + Sweden Building 05K0003 + 3.38991548528 + Sweden Building 05K0004 + 4.33303636174 + Sweden Building 05K0005 + 2.75390897598 + Sweden Building 05K0006 + 7.77750996655 + Sweden Building 05K0007 + 1.66724551261 + Sweden Building 05K0008 + 3.32543498168 + Sweden Building 05K0009 + 3.08636405861 + Sweden Building 05K0010 + 14.8373684211 + Sweden Building 05K0011 + 1.47492819795 + Sweden Building 05K0012 + 3.32673206926 + Sweden Building 05K0013 + 2.63132906976 +

23

Property:Building/SPBreakdownOfElctrcityUseKwhM2LargeComputersServers |  

Open Energy Info (EERE)

LargeComputersServers LargeComputersServers Jump to: navigation, search This is a property of type String. Large computers / servers Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2LargeComputersServers" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 2.88701226026 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 3.90838206628 + Sweden Building 05K0005 + 0.697674418605 + Sweden Building 05K0006 + 1.18332311465 + Sweden Building 05K0007 + 11.4098804421 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.556088941246 + Sweden Building 05K0010 + 10.0228832952 + Sweden Building 05K0011 + 0.471022727273 + Sweden Building 05K0012 + 0.774049003718 + Sweden Building 05K0013 + 0.0 +

24

Property:Building/SPBreakdownOfElctrcityUseKwhM2Elevators | Open Energy  

Open Energy Info (EERE)

Elevators Elevators Jump to: navigation, search This is a property of type String. Elevators Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Elevators" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.139664804469 + Sweden Building 05K0003 + 5.78356533453 + Sweden Building 05K0004 + 0.0116959064327 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.699648105982 + Sweden Building 05K0008 + 0.192307692308 + Sweden Building 05K0009 + 0.0661775284132 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.163674492353 + Sweden Building 05K0014 + 2.7497571546 +

25

Property:Building/SPBreakdownOfElctrcityUseKwhM2Fans | Open Energy  

Open Energy Info (EERE)

Fans Fans Jump to: navigation, search This is a property of type String. Fans Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Fans" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 5.21311928139 + Sweden Building 05K0002 + 18.5995610535 + Sweden Building 05K0003 + 20.3514016294 + Sweden Building 05K0004 + 8.08671679198 + Sweden Building 05K0005 + 16.0166245259 + Sweden Building 05K0006 + 10.358795651 + Sweden Building 05K0007 + 8.3953561818 + Sweden Building 05K0008 + 9.28527472527 + Sweden Building 05K0009 + 12.8398873749 + Sweden Building 05K0010 + 20.0966982674 + Sweden Building 05K0011 + 6.90408963585 + Sweden Building 05K0012 + 8.60719192175 + Sweden Building 05K0013 + 16.7539365907 +

26

Property:Building/SPBreakdownOfElctrcityUseKwhM2Copiers | Open Energy  

Open Energy Info (EERE)

Copiers Copiers Jump to: navigation, search This is a property of type String. Copiers Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Copiers" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.85593220339 + Sweden Building 05K0003 + 0.447247706422 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.897811865554 + Sweden Building 05K0008 + 0.9 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 7.78032036613 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 1.24104401228 + Sweden Building 05K0014 + 2.91414481058 + Sweden Building 05K0015 + 0.41935483871 +

27

Property:Building/SPPurchasedEngyPerAreaKwhM2ElctrtyTotal | Open Energy  

Open Energy Info (EERE)

ElctrtyTotal ElctrtyTotal Jump to: navigation, search This is a property of type String. Electricity, total Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2ElctrtyTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 71.2214478303 + Sweden Building 05K0002 + 95.9357541899 + Sweden Building 05K0003 + 72.2496632241 + Sweden Building 05K0004 + 65.8830409357 + Sweden Building 05K0005 + 54.2477876106 + Sweden Building 05K0006 + 58.7608028994 + Sweden Building 05K0007 + 61.5607534672 + Sweden Building 05K0008 + 40.3846153846 + Sweden Building 05K0009 + 56.4810818587 + Sweden Building 05K0010 + 152.219679634 + Sweden Building 05K0011 + 25.5555555556 + Sweden Building 05K0012 + 35.8807888323 + Sweden Building 05K0013 + 61.3267863536 +

28

Property:Building/SPBreakdownOfElctrcityUseKwhM2CirculationFans | Open  

Open Energy Info (EERE)

CirculationFans CirculationFans Jump to: navigation, search This is a property of type String. Circulation fans Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2CirculationFans" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 13.3422495258 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 2.80646609789 + Sweden Building 05K0004 + 8.95823904901 + Sweden Building 05K0005 + 5.55016340076 + Sweden Building 05K0006 + 6.81308969891 + Sweden Building 05K0007 + 2.02541916787 + Sweden Building 05K0008 + 0.625641025641 + Sweden Building 05K0009 + 7.59721281624 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.757191316527 + Sweden Building 05K0012 + 6.04077487892 + Sweden Building 05K0013 + 0.767224182906 +

29

Property:Building/SPPurchasedEngyPerAreaKwhM2DstrtColg | Open Energy  

Open Energy Info (EERE)

DstrtColg DstrtColg Jump to: navigation, search This is a property of type String. District cooling Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2DstrtColg" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 38.7648166048 + Sweden Building 05K0002 + 44.9720670391 + Sweden Building 05K0003 + 11.6524472384 + Sweden Building 05K0004 + 35.3996101365 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 24.0451630889 + Sweden Building 05K0007 + 18.6296832954 + Sweden Building 05K0008 + 15.7692307692 + Sweden Building 05K0009 + 17.2637030643 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 5.09803921569 + Sweden Building 05K0012 + 15.0675825393 + Sweden Building 05K0013 + 21.4822771214 +

30

Property:Building/SPBreakdownOfElctrcityUseKwhM2AirCompressors | Open  

Open Energy Info (EERE)

AirCompressors AirCompressors Jump to: navigation, search This is a property of type String. Air compressors Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2AirCompressors" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 1.33591087145 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 1.86549707602 + Sweden Building 05K0005 + 2.04651162791 + Sweden Building 05K0006 + 1.92596566524 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.970107495214 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 1.30894886364 + Sweden Building 05K0012 + 2.01978262942 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 +

31

Property:Building/SPBreakdownOfElctrcityUseKwhM2Lighting | Open Energy  

Open Energy Info (EERE)

This is a property of type String. This is a property of type String. Lighting Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Lighting" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 13.6004313481 + Sweden Building 05K0002 + 51.2740526316 + Sweden Building 05K0003 + 25.3519773429 + Sweden Building 05K0004 + 14.5539566929 + Sweden Building 05K0005 + 17.1088606195 + Sweden Building 05K0006 + 11.7758321884 + Sweden Building 05K0007 + 16.0796522459 + Sweden Building 05K0008 + 15.7053876478 + Sweden Building 05K0009 + 19.44639866 + Sweden Building 05K0010 + 37.0625 + Sweden Building 05K0011 + 12.9336787565 + Sweden Building 05K0012 + 12.985779547 + Sweden Building 05K0013 + 21.6361810339 + Sweden Building 05K0014 + 29.853732347 +

32

Property:Building/SPBreakdownOfElctrcityUseKwhM2LargeKitchens | Open Energy  

Open Energy Info (EERE)

LargeKitchens LargeKitchens Jump to: navigation, search This is a property of type String. Large kitchens Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2LargeKitchens" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.763086941039 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.409356725146 + Sweden Building 05K0005 + 2.13953488372 + Sweden Building 05K0006 + 0.383200490497 + Sweden Building 05K0007 + 3.38701556508 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.294507436313 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.177556818182 + Sweden Building 05K0012 + 0.0953379731147 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 +

33

Property:Building/SPBreakdownOfElctrcityUseKwhM2Pcs | Open Energy  

Open Energy Info (EERE)

Pcs Pcs Jump to: navigation, search This is a property of type String. PCs Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Pcs" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 26.0998626444 + Sweden Building 05K0002 + 22.2888135593 + Sweden Building 05K0003 + 4.12075688073 + Sweden Building 05K0004 + 22.9175048733 + Sweden Building 05K0005 + 6.03962790698 + Sweden Building 05K0006 + 15.790619252 + Sweden Building 05K0007 + 5.8172794947 + Sweden Building 05K0008 + 4.66333333333 + Sweden Building 05K0009 + 8.50154616404 + Sweden Building 05K0010 + 8.05491990847 + Sweden Building 05K0011 + 2.70028409091 + Sweden Building 05K0012 + 2.19353608542 + Sweden Building 05K0013 + 8.43270214944 +

34

Property:Building/SPBreakdownOfElctrcityUseKwhM2Printers | Open Energy  

Open Energy Info (EERE)

Printers Printers Jump to: navigation, search This is a property of type String. Printers Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Printers" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.928422444931 + Sweden Building 05K0002 + 1.42372881356 + Sweden Building 05K0003 + 0.412844036697 + Sweden Building 05K0004 + 0.980506822612 + Sweden Building 05K0005 + 1.76744186047 + Sweden Building 05K0006 + 1.27988963826 + Sweden Building 05K0007 + 1.12158808933 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.765719334413 + Sweden Building 05K0010 + 1.01601830664 + Sweden Building 05K0011 + 0.774147727273 + Sweden Building 05K0012 + 1.11545428544 + Sweden Building 05K0013 + 0.549891248721 +

35

Property:Building/SPBreakdownOfElctrcityUseKwhM2SmallKitchensCoffeeRms |  

Open Energy Info (EERE)

SmallKitchensCoffeeRms SmallKitchensCoffeeRms Jump to: navigation, search This is a property of type String. Small kitchens / coffee rooms Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2SmallKitchensCoffeeRms" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 1.20677966102 + Sweden Building 05K0003 + 1.46100917431 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 2.53105456775 + Sweden Building 05K0007 + 1.08639747349 + Sweden Building 05K0008 + 0.910666666667 + Sweden Building 05K0009 + 2.06390811368 + Sweden Building 05K0010 + 3.29519450801 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 1.54234902764 +

36

Property:Building/SPBreakdownOfElctrcityUseKwhM2Refrigeration | Open Energy  

Open Energy Info (EERE)

Refrigeration Refrigeration Jump to: navigation, search This is a property of type String. Refrigeration Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Refrigeration" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 2.77390577084 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 37.1080462614 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.895094880057 + Sweden Building 05K0014 + 12.4536103016 + Sweden Building 05K0015 + 0.0 +

37

Design and testing of the HTS bearing for a 10 kWh flywheel system  

Science Journals Connector (OSTI)

Flywheels are of interest for a wide range of energy storage applications, from support of renewable resources to distributed power applications and uninterruptible power systems (UPS) (Day et al 2000 Proc. EESAT 2000 (Orlando, FL, Sept. 2000)). The use of high-temperature superconducting (HTS) bearings for such systems has significant advantages for applications requiring large amounts of energy to be stored with low parasitic losses and with minimal system maintenance. As flywheel systems increase in size, it becomes a significant challenge to provide adequate stiffness in these bearings without exceeding the strength limits of rotating magnet assemblies. The Boeing Company is designing and building a prototype flywheel of 10 kWh total stored energy and has focused much effort on the HTS bearing system. This paper will describe the general structure of the bearing and the steps taken to optimize its magnetic and structural performance and show recent test results.

A C Day; M Strasik; K E McCrary; P E Johnson; J W Gabrys; J R Schindler; R A Hawkins; D L Carlson; M D Higgins; J R Hull

2002-01-01T23:59:59.000Z

38

Property:Building/SPPurchasedEngyPerAreaKwhM2DigesterLandfillGas | Open  

Open Energy Info (EERE)

DigesterLandfillGas DigesterLandfillGas Jump to: navigation, search This is a property of type String. Digester / landfill gas Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2DigesterLandfillGas" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 +

39

Property:Building/SPBreakdownOfElctrcityUseKwhM2Laundry | Open Energy  

Open Energy Info (EERE)

Laundry Laundry Jump to: navigation, search This is a property of type String. Laundry Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Laundry" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 +

40

Property:Building/SPPurchasedEngyPerAreaKwhM2WoodChips | Open Energy  

Open Energy Info (EERE)

WoodChips WoodChips Jump to: navigation, search This is a property of type String. Wood chips Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2WoodChips" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 +

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Property:Building/SPPurchasedEngyPerAreaKwhM2Pellets | Open Energy  

Open Energy Info (EERE)

Pellets Pellets Jump to: navigation, search This is a property of type String. Pellets Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2Pellets" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 +

42

Property:Building/SPPurchasedEngyPerAreaKwhM2Other | Open Energy  

Open Energy Info (EERE)

This is a property of type String. This is a property of type String. Other Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2Other" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 + Sweden Building 05K0018 + 0.0 +

43

Property:Building/SPPurchasedEngyPerAreaKwhM2Logs | Open Energy Information  

Open Energy Info (EERE)

Logs Logs Jump to: navigation, search This is a property of type String. Logs Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2Logs" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 +

44

Property:Building/SPBreakdownOfElctrcityUseKwhM2ElctrcEngineHeaters | Open  

Open Energy Info (EERE)

ElctrcEngineHeaters ElctrcEngineHeaters Jump to: navigation, search This is a property of type String. Electric engine heaters Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2ElctrcEngineHeaters" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 2.44788473329 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.353408923575 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.835160644485 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 +

45

Property:Building/SPPurchasedEngyPerAreaKwhM2TownGas | Open Energy  

Open Energy Info (EERE)

TownGas TownGas Jump to: navigation, search This is a property of type String. Town gas Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2TownGas" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 +

46

Property:Building/SPPurchasedEngyPerAreaKwhM2NaturalGas | Open Energy  

Open Energy Info (EERE)

NaturalGas NaturalGas Jump to: navigation, search This is a property of type String. Natural gas Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2NaturalGas" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 +

47

Beyond kWh and kW demand: Understanding the new real-time electric power  

NLE Websites -- All DOE Office Websites (Extended Search)

Beyond kWh and kW demand: Understanding the new real-time electric power Beyond kWh and kW demand: Understanding the new real-time electric power measurement system in LBNL Building 90 Speaker(s): Alex McEachern Date: January 14, 2010 - 12:00pm Location: 90-3122 In the Summer of 2009, LBNL researchers installed end-use sub-metering equipment and associated Energy Information System (EIS) tools to characterize energy use and comfort in Building 90. Seven of 40 key electric loads were measured using advanced meters that make sophisticated real-time measurements of dozens of power flow parameters, power disturbances, and harmonics. The talk will review some electrical engineering fundamentals, how use and interpret data measured in building 90 in real-time. The real-time data available includes power, volt-amps, VAR's, unbalance voltage and current, voltage and current distortion,

48

Acceptable Daily Intake (ADI)  

Science Journals Connector (OSTI)

Abstract The acceptable daily intake (ADI) is commonly defined as the maximum amount of a chemical to which a person can be exposed, on a daily basis over an extended period of time, usually without suffering a deleterious effect. It represents a daily intake level of a chemical in humans that is associated with minimal or no risk of adverse effects, and if the ingestion exceeds, this amount may cause toxic effects. It is a numerical estimate of daily oral exposure to the human population, including sensitive subgroups such as children, that is not likely to cause harmful effects during a lifetime. The ADI is expressed in milligrams of the chemical, as it appears in the food, per kilogram of body weight per day (mgkg?1day?1).

J. Chilakapati; H.M. Mehendale

2014-01-01T23:59:59.000Z

49

Property:Building/SPBreakdownOfElctrcityUseKwhM2HeatPumpsUsedForColg | Open  

Open Energy Info (EERE)

HeatPumpsUsedForColg HeatPumpsUsedForColg Jump to: navigation, search This is a property of type String. Heat pumps used for cooling Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2HeatPumpsUsedForColg" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.250906049624 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 +

50

Chlorine hazard evaluation for the zinc-chlorine electric vehicle battery. Final technical report. [50 kWh  

SciTech Connect

Hazards associated with conceivable accidental chlorine releases from zinc-chlorine electric vehicle batteries are evaluated. Since commercial batteries are not yet available, this hazard assessment is based on both theoretical chlorine dispersion models and small-scale and large-scale spill tests with chlorine hydrate (which is the form of chlorine storage in the charged battery). Six spill tests involving the chlorine hydrate equivalent of a 50-kWh battery indicate that the danger zone in which chlorine vapor concentrations intermittently exceed 100 ppM extends at least 23 m directly downwind of a spill onto a warm (30 to 38/sup 0/C) road surface. Other accidental chlorine release scenarios may also cause some distress, but are not expected to produce the type of life-threatening chlorine exposures that can result from large hydrate spills. Chlorine concentration data from the hydrate spill tests compare favorably with calculations based on a quasi-steady area source dispersion model and empirical estimates of the hydrate decomposition rate. The theoretical dispersion model was combined with assumed hydrate spill probabilities and current motor vehicle accident statistics in order to project expected chlorine-induced fatality rates. These calculations indicate that expected chlorine fataility rates are several times higher in a city such as Los Angeles with a warm and calm climate than in a colder and windier city such as Boston. Calculated chlorine-induced fatality rate projections for various climates are presented as a function of hydrate spill probability in order to illustrate the degree of vehicle/battery crashworthiness required to maintain chlorine-induced fatality rates below current vehicle fatality rates due to fires and asphyxiations. 37 figures, 19 tables.

Zalosh, R. G.; Bajpai, S. N.; Short, T. P.; Tsui, R. K.

1980-04-01T23:59:59.000Z

51

Daily Temperature Lag  

NLE Websites -- All DOE Office Websites (Extended Search)

Daily Temperature Lag Daily Temperature Lag Name: Shyammayi Status: teacher Grade: K-2 Country: Mauritius Date: Summer 2011 Question: At what time of the day is the temperature hottest? At what time of the day is the temperature coldest? Replies: In general, the hottest part of the day is late afternoon. The sun has passed its peak in the sky but still heats the Earth up until very late in the afternoon. The lowest temperatures are around dawn. Earth has had all night to get rid of the day's heat by radiating it into space. After sunrise, temperatures begin to climb. This can be changed by local storms, sea breezes or mountain breezes and even monsoon winds. Hope this helps. R. W. "Bob" Avakian Instructor Arts and Sciences/CRC Oklahoma State Univ. Inst. of Technology Shyammayi

52

Yesterday's Daily Summary - Hanford Site  

NLE Websites -- All DOE Office Websites (Extended Search)

Station Real Time Met Data from Around the Site Current HMS Observations Daily HMS Extremes in Met Data Met and Climate Data Summary Products Historical Weather Charts Contacts...

53

Daily Normal Precipitation - Hanford Site  

NLE Websites -- All DOE Office Websites (Extended Search)

Station Real Time Met Data from Around the Site Current HMS Observations Daily HMS Extremes in Met Data Met and Climate Data Summary Products Historical Weather Charts Contacts...

54

Unravelling daily human mobility motifs  

E-Print Network (OSTI)

Human mobility is differentiated by time scales. While the mechanism for long time scales has been studied, the underlying mechanism on the daily scale is still unrevealed. Here, we uncover the mechanism responsible for ...

Schneider, Christian M.

55

Energy Assurance Daily | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Energy Assurance Daily Energy Assurance Daily Energy Assurance Daily Energy Assurance Daily provides a summary of public information concerning current energy issues. Published Monday through Friday to inform stakeholders of developments affecting energy systems, flows, and markets, it provides highlights of energy issues rather than a comprehensive coverage. Energy Assurance Daily covers: Major energy developments Electricity, petroleum, and natural gas industries Other relevant news Energy prices The Infrastructure Security and Energy Restoration (ISER) Division cannot guarantee the accuracy of the material in the Energy Assurance Daily. Any further use is subject to the copyright restrictions of the source document. The Energy Assurance Daily has workable hypertext links to the

56

Energy Assurance Daily (EAD): June 2012  

Energy.gov (U.S. Department of Energy (DOE))

Energy Assurance Daily provides a summary of public information concerning current energy issues. Published Monday through Friday to inform stakeholders of developments affecting energy systems,...

57

Energy Assurance Daily (EAD): July 2012  

Energy.gov (U.S. Department of Energy (DOE))

Energy Assurance Daily provides a summary of public information concerning current energy issues. Published Monday through Friday to inform stakeholders of developments affecting energy systems,...

58

Energy Assurance Daily (EAD): May 2012  

Energy.gov (U.S. Department of Energy (DOE))

Energy Assurance Daily provides a summary of public information concerning current energy issues. Published Monday through Friday to inform stakeholders of developments affecting energy systems,...

59

Energy Assurance Daily (EAD): April 2012  

Energy.gov (U.S. Department of Energy (DOE))

Energy Assurance Daily provides a summary of public information concerning current energy issues. Published Monday through Friday to inform stakeholders of developments affecting energy systems,...

60

Energy Assurance Daily (EAD): January- March 2012  

Energy.gov (U.S. Department of Energy (DOE))

Energy Assurance Daily provides a summary of public information concerning current energy issues. Published Monday through Friday to inform stakeholders of developments affecting energy systems,...

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

KWhOURS | Open Energy Information  

Open Energy Info (EERE)

Zip: 1982 Sector: Services Product: Massachusetts software maker which provides mobile data collection, calculation, and report generation services that reduce cost and time...

62

Daily HMS Extremes in Met Data - Hanford Site  

NLE Websites -- All DOE Office Websites (Extended Search)

Hanford Meteorological Station > Daily HMS Extremes in Met Data Hanford Meteorological Station Real Time Met Data from Around the Site Current HMS Observations Daily HMS Extremes...

63

Daily HMS Extremes in Met Data - Hanford Site  

NLE Websites -- All DOE Office Websites (Extended Search)

Meteorological Station > Daily HMS Extremes in Met Data Hanford Meteorological Station Real Time Met Data from Around the Site Current HMS Observations Daily HMS Extremes in Met...

64

2011 Daily Log Report #: 2011-00168  

E-Print Network (OSTI)

2011 Daily Log March 2011 Report #: 2011-00168 Reported: 03/31/2011 1237 Occurred: 03/31/2011 1235 Incident: Medical Emergency Location: Outside of Student Union Disposition: Report--Closed Comments: Female transported to hospital by ambulance for medical treatment. Report #: 2011-00167 Reported: 03/31/2011 1116

Boyce, Richard L.

65

2009 Daily Log Report #: 2009-00202  

E-Print Network (OSTI)

2009 Daily Log March 2009 Report #: 2009-00202 Reported: 03/31/09 2045 Occurred: 03/29/09 1400 to 03/30/09 2000 Incident: Theft Location: Lot Q Disposition: Report--Open Comments: GPS System stolen from unlocked vehicle. Report #: 2009-00201 Reported: 03/31/09 1833 Occurred: Same Incident: Fire

Boyce, Richard L.

66

2009 Daily Log Report #: 2009-00269  

E-Print Network (OSTI)

2009 Daily Log April 2009 Report #: 2009-00269 Reported: 04/30/09 1508 Occurred: Same Incident: Traffic Crash Location: Johns Hill Road and Kenton Drive Disposition: Report--Closed Comments: Two vehicle accident; no injuries. Report #: 2009-00268 Reported: 04/30/09 1049 Occurred: Same Incident: Traffic Crash

Boyce, Richard L.

67

2011 Daily Log Report #: 2011-00229  

E-Print Network (OSTI)

2011 Daily Log April 2011 Report #: 2011-00229 Reported: 04/29/2011 2327 Occurred: 04/29/2011 2325 Incident: Medical Emergency Location: University Center Disposition: Report--Closed Comments: Female transported by ambulance to hospital for medical treatment. Report #: 2011-00228 Reported: 04/29/2011 1702

Boyce, Richard L.

68

2010 Daily Log Report #: 2010-00262  

E-Print Network (OSTI)

2010 Daily Log June 2010 Report #: 2010-00262 Reported: 06/30/10 0957 Occurred: 06/24/10 1630 to 0957 Incident: Theft Location: Founders Hall Disposition: Report--Open Comments: Several textbooks stolen from office. No Reportable Activity on 06/29/10 Report #: 2010-00261 Reported: 06/28/10 1720

Boyce, Richard L.

69

2009 Daily Log Report #: 2009-00327  

E-Print Network (OSTI)

2009 Daily Log June 2009 Report #: 2009-00327 Reported: 06/30/09 1118 Occurred: Same Incident: Fire/Smoke Alarm Location: Dorm--Kentucky Hall Disposition: Report--Closed Comments: Alarm activation caused by drywall dust from contractors; fire department responded and cleared the scene. No Reportable Activity

Boyce, Richard L.

70

2011 Daily Log Report #: 2011-00261  

E-Print Network (OSTI)

2011 Daily Log May 2011 Report #: 2011-00261 Reported: 05/31/2011 1300 Occurred: Same Incident: Medical Emergency Location: University Center Disposition: Report--Closed Comments: Male transported to hospital by ambulance for evaluation and treatment. No Reportable Activity on 05/30/2011 No Reportable

Boyce, Richard L.

71

2011 Daily Log Report #: 2011-00295  

E-Print Network (OSTI)

2011 Daily Log June 2011 Report #: 2011-00295 Reported: 6/30/2011 0813 Occurred: 6/29/2011 1430 Incident: Traffic Crash Location: Sidewalk on Plaza Level Disposition: Report--Closed Comments: Single vehicle accident; no injuries. Report #: 2011-00294 Reported: 06/29/2011 1909 Occurred: Same Incident

Boyce, Richard L.

72

2010 Daily Log Report #: 2010-00221  

E-Print Network (OSTI)

2010 Daily Log April 2010 Report #: 2010-00221 Reported: 04/30/10 1034 Occurred: Same Incident: Found/Recovered Property Location: Founders Hall Disposition: Report--Closed Comments: Small purse was found in classroom. Report #: 2010-00220 Reported: 04/30/10 1347 Occurred: 04/30/10 0820 to 0900

Boyce, Richard L.

73

2011 Daily Log Report #: 2011-00317  

E-Print Network (OSTI)

2011 Daily Log July 2011 Report #: 2011-00317 Reported: 07/30/2011 1446 Occurred: 07/30/2011 1435 Incident: Odor Related Complaint Location: Power Plant Disposition: Report--Closed Comments: Subject reported a strange odor emanating from somewhere in the vicinity; fire department responded and cleared

Boyce, Richard L.

74

DOE Solar Decathlon: 2009 Daily Journals  

NLE Websites -- All DOE Office Websites (Extended Search)

Richard King next to a deck and planter boxes. Decathlete Way and the U.S. Capitol are in the background. Richard King next to a deck and planter boxes. Decathlete Way and the U.S. Capitol are in the background. Solar Decathlon Director Richard King takes a break from the competition along Decathlete Way. Solar Decathlon 2009 Daily Journals The daily journals highlighted the events of the U.S. Department of Energy Solar Decathlon 2009. Each day, Richard King, Solar Decathlon director, covered the latest on the teams, their standings, and the events going on in the solar village. October 19, 2009 I personally believe one of the greatest discoveries in the field of energy from the 20th century is our ability to generate electricity from sunlight using photovoltaic solar cells. Read more. October 17, 2009 Solar Decathlon 2009 was intriguing and suspenseful to the very end. None

75

Climate Reference Network Daily01 Product | Data.gov  

NLE Websites -- All DOE Office Websites (Extended Search)

Daily01 Product Daily01 Product Agriculture Community Menu DATA APPS EVENTS DEVELOPER STATISTICS COLLABORATE ABOUT Agriculture You are here Data.gov » Communities » Agriculture » Data Climate Reference Network Daily01 Product Dataset Summary Description The U.S. Climate Reference Network is designed specifically to monitor national climate change with best scientific practice and adherence to the accepted principles of climate observations. USCRN daily temperature mean, maximum, and minimum, daily precipitation, daily global solar radiation, and daily average surface infrared temperature data are available in the Daily01 file set for all stations in the network. Daily mean, maximum, and minimum relative humidity are available for most stations. Tags {"Climate Reference Network",USCRN,CRN,"air temperature",temperature,precipitation,"global solar radiation"," surface temperature","surface infrared temperature","relative humidity","natural resources",water,air,"soil "}

76

Daily HMS Extremes in Met Data - Hanford Site  

NLE Websites -- All DOE Office Websites (Extended Search)

Daily HMS Extremes in Met Data Hanford Meteorological Station Real Time Met Data from Around the Site Current HMS Observations Daily HMS Extremes in Met Data Met and Climate Data...

77

Solar Decathlon 2005 Daily Event Schedule  

NLE Websites -- All DOE Office Websites (Extended Search)

DAILY EVENT SCHEDULE DAILY EVENT SCHEDULE Last updated on September 30, 2005 Note: This schedule is not part of the official Rules and Regulations and is subject to change at any time. Weds, Sept 28 12:00 AM 12:30 AM 1:00 AM 1:30 AM 2:00 AM 2:30 AM 3:00 AM 3:30 AM 4:00 AM 4:30 AM 5:00 AM 5:30 AM 6:00 AM 6:30 AM 7:00 AM 7:30 AM 8:00 AM 8:30 AM 9:00 AM 9:30 AM 10:00 AM 10:30 AM 11:00 AM 11:30 AM 12:00 PM 12:30 PM 1:00 PM 1:30 PM 2:00 PM 2:30 PM 3:00 PM 3:30 PM 4:00 PM 4:30 PM 5:00 PM 5:30 PM 6:00 PM 6:30 PM 7:00 PM 7:30 PM 8:00 PM 8:30 PM 9:00 PM 9:30 PM 10:00 PM 10:30 PM 11:00 PM 11:30 PM Registration Forrestal Bldg (DOE) Cafeteria National Mall Team/Organizer meeting and Safety Orientation Thurs, Sept 29 12:00 AM 12:30 AM 1:00 AM 1:30 AM 2:00 AM 2:30 AM 3:00 AM 3:30 AM 4:00 AM 4:30 AM 5:00 AM 5:30 AM 6:00 AM 6:30 AM 7:00

78

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

6893,36894,36894,83,83,83,800,1,2 6893,36894,36894,83,83,83,800,1,2 "Entergy",36894,36895,36895,93,93,93,800,1,2 "Entergy",36895,36896,36896,83,78.5,80.83,7200,9,4 "Entergy",36896,36899,36899,78,67,74.25,3200,4,5 "Entergy",36899,36900,36900,57,54,55.5,1600,2,4 "Entergy",36900,36901,36901,53,53,53,1600,1,2 "Entergy",36902,36903,36903,67.5,65,66.5,4000,5,3 "Entergy",36903,36906,36906,52.5,48,50.25,1600,2,3 "Entergy",36907,36908,36908,52,45,48.86,8800,11,4 "Entergy",36908,36909,36909,56,51,51.95,16800,21,6 "Entergy",36909,36910,36910,50,48.5,49.33,24000,30,7 "Entergy",36910,36913,36913,56.5,54,55.25,11200,13,7 "Entergy",36913,36914,36914,63,57,58.38,6400,8,3 "Entergy",36914,36915,36915,61.5,42,55.75,15200,19,9

79

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

449,39450,39450,180,158,161.65,26400,33,22 449,39450,39450,180,158,161.65,26400,33,22 "NEPOOL MH DA LMP",39450,39451,39451,123,108,114.27,36800,46,28 "NEPOOL MH DA LMP",39451,39454,39454,77,75.5,76.31,21600,26,17 "NEPOOL MH DA LMP",39454,39455,39455,68.25,66,67.1,41600,51,26 "NEPOOL MH DA LMP",39455,39456,39456,69.5,68,68.71,21600,27,18 "NEPOOL MH DA LMP",39456,39457,39457,81,74,75.75,30400,35,17 "NEPOOL MH DA LMP",39457,39458,39458,75,69.75,71.18,24800,31,19 "NEPOOL MH DA LMP",39458,39461,39461,80.5,77,79.38,17600,19,17 "NEPOOL MH DA LMP",39461,39462,39462,102,95,98.76,52000,64,24 "NEPOOL MH DA LMP",39462,39463,39463,90.5,87.5,88.59,34400,43,25 "NEPOOL MH DA LMP",39463,39464,39464,85,83.5,84.21,20800,26,14

80

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

815,39818,39818,43,42.5,42.75,5.17,1600,2,4 815,39818,39818,43,42.5,42.75,5.17,1600,2,4 "ERCOT-South",39818,39819,39819,40,39.5,39.88,-2.87,3200,4,3," " "ERCOT-South",39819,39820,39820,39,38,38.73,-1.15,8800,9,9 "ERCOT-South",39820,39821,39821,41.5,39,39.82,1.09,8800,11,9 "ERCOT-South",39821,39822,39822,38.75,37.5,38.03,-1.79,6400,8,10 "ERCOT-South",39822,39825,39825,43.5,43.5,43.5,5.47,800,1,2 "ERCOT-South",39825,39826,39826,55,50.5,52.95,9.45,8800,11,12,,," " "ERCOT-South",39826,39827,39827,45.5,43.5,44.44,-8.51,14400,18,18 "ERCOT-South",39827,39828,39828,45,44.25,44.68,0.24,12000,14,12 "ERCOT-South",39828,39829,39829,44,42.75,43.18,-1.5,8000,10,10 "ERCOT-South",39833,39834,39834,33,32.5,32.75,-10.43,9600,12,8

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

54.5,53.4,53.98,5.44,3200,4,7 54.5,53.4,53.98,5.44,3200,4,7 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",49,47.25,48.27,-5.71,8000,10,12 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",56,53.5,54.75,6.48,4800,6,10 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",97,87,89.96,35.21,20800,18,16 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",56.25,51,53.71,-36.25,16800,19,15 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",46.75,46,46.33,-7.38,17600,22,17

82

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

Nepool MH Da Lmp ",39815,39818,39818,65.55,65,65.44,-5.89,12000,15,9 Nepool MH Da Lmp ",39815,39818,39818,65.55,65,65.44,-5.89,12000,15,9 "Nepool MH Da Lmp",39818,39819,39819,67,65,66.22,0.78,39200,46,22 "Nepool MH Da Lmp ",39819,39820,39820,65,63.25,63.83,-2.39,20000,24,18 "Nepool MH Da Lmp ",39820,39821,39821,67.5,65.75,66.47,2.64,28000,33,16 "Nepool MH Da Lmp ",39821,39822,39822,78.5,76,77.31,10.84,21600,27,16 "Nepool MH Da Lmp ",39822,39825,39825,100,90,94.19,16.88,28800,35,19 "Nepool MH Da Lmp ",39825,39826,39826,81,72.75,74.76,-19.43,36000,44,24 "Nepool MH Da Lmp ",39826,39827,39827,101,98,99.83,25.07,16000,20,18 "Nepool MH Da Lmp",39827,39828,39828,130,117,120.32,20.49,40000,50,27 "Nepool MH Da Lmp ",39828,39829,39829,120,106,109.76,-10.56,72800,91,35

83

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

SP 15",39449,39450,39450,74.6,69.25,73.56,97200,234,36 SP 15",39449,39450,39450,74.6,69.25,73.56,97200,234,36 "SP 15",39450,39451,39452,70,63,68.49,291200,275,37 "SP 15",39451,39454,39454,75,68,69.2,140000,326,39 "SP 15",39454,39455,39455,73.25,69,71.52,144800,329,37 "SP 15",39455,39456,39456,72.25,70.25,71.32,198000,425,35 "SP 15",39456,39457,39457,73.75,70.75,72.79,157600,351,37 "SP 15",39457,39458,39459,70.25,67.25,68.46,226400,268,33 "SP 15",39458,39461,39461,75,73.25,73.77,184000,366,38 "SP 15",39461,39462,39462,78.25,75,75.77,110800,235,34 "SP 15",39462,39463,39464,88,77.5,79.42,323200,351,36 "SP 15",39463,39465,39466,79,74.25,77.52,259200,302,36 "SP 15",39464,39468,39468,84.45,77,82.35,126400,287,36

84

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

54.55,54.05,54.37,1.9,8800,20,11 54.55,54.05,54.37,1.9,8800,20,11 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",53.25,52.75,53.09,-1.28,35200,64,16 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",52,51.25,51.51,-1.58,13600,28,17 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",56.5,53.25,54.08,2.57,65600,71,17 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",51.15,50.8,51.01,-3.07,27600,53,19 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",50.75,50,50.18,-0.83,23200,39,11

85

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

084,39085,39085,62,55,55.98,10400,13,10 084,39085,39085,62,55,55.98,10400,13,10 "NEPOOL MH DA LMP",39085,39086,39086,54.75,52.75,53.53,30400,38,20 "NEPOOL MH DA LMP",39086,39087,39087,56,55,55.35,24800,31,19 "NEPOOL MH DA LMP",39087,39090,39090,58,56.5,57.08,8000,10,12 "NEPOOL MH DA LMP",39090,39091,39091,58.75,57.25,57.86,34400,41,19 "NEPOOL MH DA LMP",39091,39092,39092,60.5,59,59.8,20800,25,19 "NEPOOL MH DA LMP",39092,39093,39093,65,63.5,64.04,13600,16,15 "NEPOOL MH DA LMP",39093,39094,39094,61.25,59.75,60.82,15200,19,14 "NEPOOL MH DA LMP",39094,39097,39097,62,59,60.95,16800,21,16 "NEPOOL MH DA LMP",39097,39098,39098,69.25,67,68.25,22400,28,15 "NEPOOL MH DA LMP",39098,39099,39099,89,84.5,86.33,34400,43,26

86

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

53.5,48,50.93,,13600,17,11 53.5,48,50.93,,13600,17,11 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",57.5,52.75,55,4.07,31200,39,15 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",51.5,49.5,50.38,-4.62,3200,4,4 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",52,49.5,51.25,0.87,19200,24,12 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",46.75,45.25,45.8,-5.45,21600,27,14 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",43,39.5,41.3,-4.5,10400,13,8

87

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

1246,41247,41247,28.5,26.5,27.76,-0.16,63200,141,25 1246,41247,41247,28.5,26.5,27.76,-0.16,63200,141,25 "Mid Columbia Peak",41247,41248,41248,28.5,27,27.86,0.1,79200,187,26 "Mid Columbia Peak",41248,41249,41249,28,23.5,27.02,-0.84,76000,170,25 "Mid Columbia Peak",41249,41250,41251,23.25,21.25,22.44,-4.58,159200,191,23 "Mid Columbia Peak",41250,41253,41253,25.25,21.25,23.45,1.01,74800,176,25 "Mid Columbia Peak",41253,41254,41254,23.75,20.75,22.51,-0.94,92800,209,26 "Mid Columbia Peak",41254,41255,41255,24.5,23,23.84,1.33,100800,222,27 "Mid Columbia Peak",41255,41256,41256,28,25.5,26.88,3.04,80800,182,26 "Mid Columbia Peak",41256,41257,41258,27.75,26.5,27.13,0.25,152000,171,25 "Mid Columbia Peak",41257,41260,41260,25.75,23.25,24.43,-2.7,76000,180,25

88

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

38.75,37.25,37.95,-2.02,13600,17,14 38.75,37.25,37.95,-2.02,13600,17,14 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",43.5,40,42.39,4.44,10000,25,20 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",39.5,37.75,38.26,-4.13,9200,23,15 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",40.25,37.25,38.46,0.2,7600,19,14 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",41,38,38.93,0.47,9200,23,15 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",38.25,36.5,37.29,-1.64,13600,17,17

89

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

623,37624,37624,37.45,33.75,35.69,28800,36,19 623,37624,37624,37.45,33.75,35.69,28800,36,19 "PJM West",37624,37627,37627,48,47,47.58,28800,32,20 "PJM West",37627,37628,37628,50.5,48,49.53,33600,42,19 "PJM West",37628,37629,37629,47,44.25,45.39,35200,44,20 "PJM West",37629,37630,37630,39,37,37.73,27200,33,19 "PJM West",37630,37631,37631,43.5,41.75,42.44,25600,27,17 "PJM West",37631,37634,37634,64,56.5,58.31,20800,26,19 "PJM West",37634,37635,37635,56,54.8,55.52,19200,24,19 "PJM West",37635,37636,37636,56.5,54.9,55.51,28000,33,19 "PJM West",37636,37637,37637,53,50.25,51.89,32000,40,22 "PJM West",37637,37638,37638,54,52,52.63,30400,38,23 "PJM West",37638,37641,37641,48.25,47,47.48,26400,33,17

90

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

258,37259,37259,33.75,32.5,33.23,10400,13,12 258,37259,37259,33.75,32.5,33.23,10400,13,12 "NEPOOL",37259,37260,37260,36.25,35,35.98,24800,31,18 "NEPOOL",37260,37263,37263,34,33.25,33.66,8800,11,12 "NEPOOL",37263,37264,37264,34,33.5,33.67,10400,13,11 "NEPOOL",37264,37265,37265,32.6,31,32.04,9600,11,13 "NEPOOL",37265,37266,37266,29.5,28.7,29.1,10400,13,11 "NEPOOL",37266,37267,37267,29.25,28.25,28.75,12000,15,12 "NEPOOL",37267,37270,37270,31,30,30.24,16800,17,13 "NEPOOL",37270,37271,37271,30.5,29.75,30.09,30400,36,15 "NEPOOL",37271,37272,37272,29.5,28.65,28.98,23200,28,15 "NEPOOL",37272,37273,37273,30.4,29.8,30.02,32800,39,16 "NEPOOL",37273,37274,37274,30,29.1,29.37,11200,14,15 "NEPOOL",37274,37277,37277,30,29.25,29.72,6400,8,9

91

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

182,40183,40183,89,82.75,86.08,20.49,214400,242,55 182,40183,40183,89,82.75,86.08,20.49,214400,242,55 "PJM Wh Real Time Peak",40183,40184,40184,80.65,74.5,77.16,-8.92,270400,295,56 "PJM Wh Real Time Peak",40184,40185,40185,80.5,77.5,78.92,1.76,93600,111,47 "PJM Wh Real Time Peak",40185,40186,40186,86,78.25,80.64,1.72,278400,316,62 "PJM Wh Real Time Peak",40186,40189,40189,82.75,72,80.64,0,81600,98,36 "PJM Wh Real Time Peak",40189,40190,40190,73,65.75,67.86,-12.78,178400,205,50 "PJM Wh Real Time Peak",40190,40191,40191,55.25,53,53.89,-13.97,162400,180,50 "PJM Wh Real Time Peak",40191,40192,40192,49.75,48,48.84,-5.05,97600,109,45 "PJM Wh Real Time Peak",40192,40193,40193,46.25,43.5,44.65,-4.19,99200,117,46 "PJM Wh Real Time Peak",40193,40196,40196,46,44.95,45.38,0.73,59200,71,35

92

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

8721,38722,38722,57.5,57.5,57.5,-22.5,800,1,2 8721,38722,38722,57.5,57.5,57.5,-22.5,800,1,2 "ERCOT-South",38748,38749,38749,57,57,57,-0.5,800,1,2 "ERCOT-South",38751,38754,38754,59,59,59,2,1600,2,3 "ERCOT-South",38786,38789,38789,48,48,48,-11,800,1,2 "ERCOT-South",38803,38804,38804,52.5,50.5,51.06,3.06,6400,8,7 "ERCOT-South",38804,38805,38805,54.75,54.75,54.75,3.69,3200,2,3 "ERCOT-South",38805,38806,38806,55.25,53.5,54.21,-0.54,4800,6,5 "ERCOT-South",38806,38807,38807,58,58,58,3.79,800,1,2,,,,," " "ERCOT-South",38810,38811,38811,60,60,60,2,800,1,2 "ERCOT-South",38811,38812,38812,64,64,64,4,800,1,2 "ERCOT-South",38812,38813,38813,63,62.5,62.63,-1.37,3200,4,6 "ERCOT-South",38813,38814,38814,62,62,62,-0.63,800,1,2

93

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

546,40547,40547,51,47.5,48.71,-0.32,96800,116,39 546,40547,40547,51,47.5,48.71,-0.32,96800,116,39 "PJM Wh Real Time Peak",40547,40548,40548,49.25,47.45,48.14,-0.57,64000,67,40 "PJM Wh Real Time Peak",40548,40549,40549,53.5,51.5,52.27,4.13,55200,66,37 "PJM Wh Real Time Peak",40549,40550,40550,60.5,57,58.43,6.16,80000,93,39 "PJM Wh Real Time Peak",40550,40553,40553,63.5,57,60.43,2,105600,124,41 "PJM Wh Real Time Peak",40553,40554,40554,69.5,64.25,66.98,6.55,128800,145,44 "PJM Wh Real Time Peak",40554,40555,40555,72.25,62,67.54,0.56,158400,194,51 "PJM Wh Real Time Peak",40555,40556,40556,84,75,80.13,12.59,92800,116,46 "PJM Wh Real Time Peak",40556,40557,40557,89.5,80.5,84.09,3.96,108800,133,42 "PJM Wh Real Time Peak",40557,40560,40560,57.55,55,56.11,-27.98,88800,105,40

94

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

40182,40183,40183,52.5,51.5,51.85,0.9,67600,116,25 40182,40183,40183,52.5,51.5,51.85,0.9,67600,116,25 "SP-15 Gen DA LMP Peak",40183,40184,40184,51.75,50.5,51.01,-0.84,61600,115,25 "SP-15 Gen DA LMP Peak",40184,40185,40185,53,50.5,51.39,0.38,59600,115,24 "SP-15 Gen DA LMP Peak",40185,40186,40187,58.5,55,56.79,5.4,394400,381,29 "SP-15 Gen DA LMP Peak",40186,40189,40189,51.25,50.75,51,-5.79,59200,116,26 "SP-15 Gen DA LMP Peak",40189,40190,40190,50.25,49,49.8,-1.2,53600,102,25 "SP-15 Gen DA LMP Peak",40190,40191,40192,51.5,50.75,51.12,1.32,59200,61,19 "SP-15 Gen DA LMP Peak",40191,40193,40194,49,48.25,48.35,-2.77,77600,71,20 "SP-15 Gen DA LMP Peak",40192,40196,40196,50.5,50,50.3,1.95,38800,71,18 "SP-15 Gen DA LMP Peak",40193,40197,40197,51.35,50,50.93,0.63,66800,84,19

95

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

084,39085,39085,43,43,43,4800,6,6 084,39085,39085,43,43,43,4800,6,6 "Entergy",39085,39086,39086,40,34,38.3,4000,5,6 "Entergy",39086,39087,39087,38,37,37.5,1600,2,2 "Entergy",39087,39090,39090,41,41,41,800,1,2 "Entergy",39090,39091,39091,49,46,48.14,5600,6,6 "Entergy",39091,39092,39092,48,48,48,2400,3,4 "Entergy",39092,39093,39093,49,47,48,1600,2,3 "Entergy",39093,39094,39094,45,44,44.5,1600,2,4 "Entergy",39094,39097,39097,51,47,49.33,2400,3,5 "Entergy",39097,39098,39098,58.5,53.5,56.06,6400,8,8 "Entergy",39098,39099,39099,62,56,58.97,7200,9,9 "Entergy",39099,39100,39100,54.5,53,53.6,4000,5,5 "Entergy",39100,39101,39101,50.75,50,50.15,4000,5,9 "Entergy",39101,39104,39104,55,53,54,2400,3,3

96

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

546,40547,40547,55.25,54,54.67,7.01,27200,29,18 546,40547,40547,55.25,54,54.67,7.01,27200,29,18 "Nepool MH DA LMP",40547,40548,40548,50,48.75,49.39,-5.28,14400,16,14 "Nepool MH DA LMP",40548,40549,40549,54.25,53,53.44,4.05,24800,31,23 "Nepool MH DA LMP",40549,40550,40550,55.5,53.25,54.05,0.61,84800,80,24 "Nepool MH DA LMP",40550,40553,40553,65.5,64.75,65.01,10.96,21600,25,18 "Nepool MH DA LMP",40553,40554,40554,71,68.5,69.33,4.32,15200,18,17 "Nepool MH DA LMP",40554,40555,40555,79,72,77.51,8.18,68800,85,29 "Nepool MH DA LMP",40555,40556,40556,100.5,88,94.96,17.45,40000,49,23 "Nepool MH DA LMP",40556,40557,40557,92.25,87,87.7,-7.26,25600,31,23 "Nepool MH DA LMP",40557,40560,40560,66,63.5,65.03,-22.67,28000,30,17

97

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

355,38356,38356,41,39,40.13,6.73,12000,14,13 355,38356,38356,41,39,40.13,6.73,12000,14,13 "PJM Wh Real Time Peak",38356,38357,38357,41,40,40.57,0.44,13600,15,15 "PJM Wh Real Time Peak",38357,38358,38358,44,42,43.23,2.66,30400,35,16 "PJM Wh Real Time Peak",38358,38359,38359,46.25,44,45.07,1.84,17600,22,12 "PJM Wh Real Time Peak",38359,38362,38362,39.5,38.75,39.17,-5.9,9600,12,11 "PJM Wh Real Time Peak",38362,38363,38363,45,41.5,43.31,4.14,26400,32,17 "PJM Wh Real Time Peak",38363,38364,38364,44,41.25,41.8,-1.51,16000,19,15 "PJM Wh Real Time Peak",38364,38365,38365,39.5,38.5,39.1,-2.7,10400,13,13 "PJM Wh Real Time Peak",38365,38366,38366,51.5,47,48.26,9.16,57600,58,17 "PJM Wh Real Time Peak",38366,38369,38369,65,63,63.48,15.22,23200,21,14

98

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

34.5,34.5,34.5,3.21,1600,2,3 34.5,34.5,34.5,3.21,1600,2,3 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",35.75,35.5,35.58,1.08,2400,3,4 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",36.5,36,36.25,0.67,4000,5,7 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",36.25,36,36.13,-0.12,3200,4,4 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",44,43.5,43.75,7.62,3200,4,6 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",44.25,43.75,44.04,0.29,5600,7,8

99

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

0911,40912,40912,27,26.5,26.63,-2.76,6400,8,6 0911,40912,40912,27,26.5,26.63,-2.76,6400,8,6 "ERCOT-South",40912,40913,40913,28,27.25,27.72,1.09,8000,9,7 "ERCOT-South",40913,40914,40914,25.75,25.75,25.75,-1.97,2400,3,4 "ERCOT-South",40914,40917,40917,27,27,27,1.25,1600,2,4 "ERCOT-South",40919,40920,40920,31,31,31,4,800,1,2 "ERCOT-South",40920,40921,40921,30.25,30.25,30.25,-0.75,800,1,2 "ERCOT-South",40925,40926,40926,25.5,25.5,25.5,-4.75,800,1,2 "ERCOT-South",40926,40927,40927,23.25,23.25,23.25,-2.25,800,1,2 "ERCOT-South",40931,40932,40932,24.5,24.5,24.5,1.25,800,1,2 "ERCOT-South",40932,40933,40933,26,25.75,25.96,1.46,4800,6,4 "ERCOT-South",40933,40934,40934,28,27,27.5,1.54,1600,2,4 "ERCOT-South",40934,40935,40935,29,28.75,28.88,1.38,1600,2,4

100

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

68.5,66,67.29,5.05,28400,71,21 68.5,66,67.29,5.05,28400,71,21 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",65,62.5,63.85,-3.44,27200,66,25 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",65.25,61.75,63.39,-0.46,80800,99,26 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",65.75,63.5,64.58,1.19,49200,107,25 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",65.75,64,64.98,0.4,32400,81,24 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",65.25,62.25,63.26,-1.72,78400,96,25

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

65.75,63,64.97,4.97,29600,55,25 65.75,63,64.97,4.97,29600,55,25 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",62.25,59,61.4,-3.57,106400,109,24 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",63,59.25,60.22,-1.18,45600,102,26 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",63.5,61.75,62.26,2.04,40400,86,26 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",64.2,62,62.52,0.26,38400,75,25 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",66.45,62,63.19,0.67,45200,87,27

102

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

PJM-West Real Time Peak",41276,41277,41277,44,41.75,42.64,-6.4,60000,72,34 PJM-West Real Time Peak",41276,41277,41277,44,41.75,42.64,-6.4,60000,72,34 "PJM-West Real Time Peak",41277,41278,41278,37,36,36.53,-6.11,19200,23,23 "PJM-West Real Time Peak",41278,41281,41281,36.5,36,36.17,-0.36,41600,48,32 "PJM-West Real Time Peak",41281,41282,41282,33.05,32.5,32.61,-3.56,20800,26,18 "PJM-West Real Time Peak",41282,41283,41283,33.75,32.5,32.91,0.3,37600,43,30 "PJM-West Real Time Peak",41283,41284,41284,31,30.25,30.64,-2.27,26400,31,26 "PJM-West Real Time Peak",41284,41285,41285,29.9,29.25,29.66,-0.98,38400,26,23 "PJM-West Real Time Peak",41285,41288,41288,32.5,31.5,32.14,2.48,40000,50,28 "PJM-West Real Time Peak",41288,41289,41289,37.5,34.5,36.5,4.36,64800,74,35

103

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

182,40183,40183,100.5,95,97,19.88,33600,42,27 182,40183,40183,100.5,95,97,19.88,33600,42,27 "Nepool MH DA LMP",40183,40184,40184,95,90,92.96,-4.04,39200,49,25 "Nepool MH DA LMP",40184,40185,40185,94,83,86.45,-6.51,33600,42,30 "Nepool MH DA LMP",40185,40186,40186,90,81.5,83.19,-3.26,47200,53,27 "Nepool MH DA LMP",40186,40189,40189,91,88.75,89.88,6.69,42400,53,30 "Nepool MH DA LMP",40189,40190,40190,71,67.75,68.95,-20.93,78400,95,30 "Nepool MH DA LMP",40190,40191,40191,61.25,58.75,59.99,-8.96,52800,64,31 "Nepool MH DA LMP",40191,40192,40192,56.25,54.75,55.33,-4.66,71200,82,32 "Nepool MH DA LMP",40192,40193,40193,53.75,53,53.36,-1.97,44000,55,25 "Nepool MH DA LMP",40193,40196,40196,55.75,54.75,55.64,2.28,21600,25,12

104

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

Indiana Rt Peak",41246,41247,41247,31.5,31.5,31.5,-1.5,1600,2,3 Indiana Rt Peak",41246,41247,41247,31.5,31.5,31.5,-1.5,1600,2,3 "Indiana Rt Peak",41247,41248,41248,34,33.5,33.75,2.25,1600,2,3 "Indiana Rt Peak",41248,41249,41249,37.25,37,37.13,3.38,8000,10,9 "Indiana Rt Peak",41249,41250,41250,34.25,33.25,33.67,-3.46,2400,3,6 "Indiana Rt Peak",41250,41253,41253,38.25,37,37.5,3.83,12800,16,13 "Indiana Rt Peak",41253,41254,41254,37.75,37.5,37.63,0.13,1600,2,4 "Indiana Rt Peak",41254,41255,41255,34,34,34,-3.63,2400,3,4 "Indiana Rt Peak",41255,41256,41256,32.25,32,32.19,-1.81,3200,4,6 "Indiana Rt Peak",41256,41257,41257,31,31,31,-1.19,1600,2,3 "Indiana Rt Peak",41257,41260,41260,33,32,32.5,1.5,1600,2,4 "Indiana Rt Peak",41260,41261,41261,33.9,33.5,33.66,1.16,3200,4,7

105

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

40911,40912,40912,35.25,34,34.38,-13.52,6400,8,9 40911,40912,40912,35.25,34,34.38,-13.52,6400,8,9 "Indiana",40912,40913,40913,31,30.45,30.73,-3.65,4800,6,7 "Indiana",40913,40914,40914,31,28.75,30.27,-0.46,20000,25,14 "Indiana",40917,40918,40918,29.05,29,29.03,-1.24,1600,2,4 "Indiana",40918,40919,40919,29.5,28.5,29.02,-0.01,5600,7,8 "Indiana",40919,40920,40920,32.25,30.75,31.59,2.57,6400,8,7 "Indiana",40920,40921,40921,35,33.25,33.92,2.33,30400,37,19 "Indiana",40921,40924,40924,29.5,29,29.25,-4.67,1600,2,4 "Indiana",40924,40925,40925,31.5,29.75,30.52,1.27,7200,9,8 "Indiana",40925,40926,40926,30.25,29.5,30,-0.52,3200,4,6 "Indiana",40926,40927,40927,33.75,32,32.61,2.61,13600,17,16 "Indiana",40927,40928,40928,33.5,32.5,33,0.39,9600,12,12

106

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

37.25,35.5,36.16,3.13,27200,25,16 37.25,35.5,36.16,3.13,27200,25,16 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",32,31,31.63,-4.53,12800,15,14 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",26.25,25.5,25.86,-5.77,7200,7,10 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",39.5,38.5,39.21,13.35,20000,24,13 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",47.75,45,46.51,7.3,27200,32,19 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",43.5,42,42.79,-3.72,39200,46,20

107

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

26,25.25,25.71,-1.15,6800,16,15 26,25.25,25.71,-1.15,6800,16,15 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",24,23.25,23.63,-2.08,14400,17,14 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",23.85,22,23.36,-0.27,8800,22,16 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",21.85,19.25,20.77,-2.59,10000,25,15 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",21.75,20,21.32,0.55,9600,23,14 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",21.25,19,20.42,-0.9,7200,16,14

108

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

40.5,40.35,40.43,2.67,3200,8,3 40.5,40.35,40.43,2.67,3200,8,3 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",41,40.85,40.97,0.54,2000,2,3 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",36.25,36.25,36.25,-4.72,3200,1,2 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",39.05,39,39.02,2.77,1200,2,2 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",36.25,36.25,36.25,-2.77,3200,2,3 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",36.75,36.5,36.63,0.38,1600,4,3

109

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

258,37259,37259,31,27.5,29.51,108000,101,28 258,37259,37259,31,27.5,29.51,108000,101,28 "PJM West",37259,37260,37260,28.25,26.95,27.38,107200,96,32 "PJM West",37260,37263,37263,26.7,26.25,26.45,102400,106,29 "PJM West",37263,37264,37264,26.25,25.45,25.75,87200,81,27 "PJM West",37264,37265,37265,24.85,24.2,24.45,53600,58,27 "PJM West",37265,37266,37266,23.6,22.5,23.05,88000,87,25 "PJM West",37266,37267,37267,23.05,22.75,22.91,72000,79,24 "PJM West",37267,37270,37270,25.1,24.55,24.88,75200,82,29 "PJM West",37270,37271,37271,23.65,22.6,23.44,47200,44,22 "PJM West",37271,37272,37272,23.05,22.85,22.95,42400,47,21 "PJM West",37272,37273,37273,23.6,23.1,23.33,68000,76,27 "PJM West",37273,37274,37274,23.8,23.3,23.47,72800,73,28

110

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

50.25,49,49.68,2.51,19200,46,20 50.25,49,49.68,2.51,19200,46,20 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",49.5,48.5,49.1,-0.58,18000,43,18 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",49.25,47,48.32,-0.78,27200,63,23 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",55,50.5,52.65,4.33,23200,29,20 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",47.75,46.5,47.18,-5.47,13600,34,19 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",47.75,44.75,45.82,-1.36,13600,28,18

111

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

8,50.33,2.26,87200,193,30 8,50.33,2.26,87200,193,30 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",45.5,48.4,-1.93,70400,154,29 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",45,46.48,-1.92,62000,146,28 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",49,51.48,5,90400,108,29 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",44.5,45.53,-5.95,38800,94,28

112

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

1246,41247,41247,44.25,43.5,43.87,2.68,16400,29,14 1246,41247,41247,44.25,43.5,43.87,2.68,16400,29,14 "SP-15 Gen DA LMP Peak",41247,41248,41248,43,42,42.36,-1.51,36800,59,23 "SP-15 Gen DA LMP Peak",41248,41249,41249,40.25,39.75,40,-2.36,17200,24,11 "SP-15 Gen DA LMP Peak",41249,41250,41251,37,36.5,36.56,-3.44,31200,28,13 "SP-15 Gen DA LMP Peak",41250,41253,41253,41.25,40,40.84,4.28,12000,26,16 "SP-15 Gen DA LMP Peak",41253,41254,41254,39.5,38.5,39.08,-1.76,12400,26,15 "SP-15 Gen DA LMP Peak",41254,41255,41255,39.45,39,39.11,0.03,15600,26,13 "SP-15 Gen DA LMP Peak",41255,41256,41256,43.75,42,43.02,3.91,16000,32,20 "SP-15 Gen DA LMP Peak",41256,41257,41258,43,40.5,42.17,-0.85,38400,32,18 "SP-15 Gen DA LMP Peak",41257,41260,41260,42,41.5,41.62,-0.55,6400,10,11

113

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

7,49.6,0.49,22400,56,24 7,49.6,0.49,22400,56,24 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",54,56.09,6.49,29200,73,27 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",57.5,60.07,3.98,28400,71,26 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",50,55.19,-4.88,32800,41,20 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",52.5,56.14,0.95,20800,52,22

114

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

084,39085,39085,43.25,43.25,43.25,-1.79,800,1,2 084,39085,39085,43.25,43.25,43.25,-1.79,800,1,2 "ERCOT-South",39086,39087,39087,42.5,42.25,42.38,-0.87,1600,2,4 "ERCOT-South",39087,39090,39090,43.25,43.25,43.25,0.87,800,1,2 "ERCOT-South",39090,39091,39091,45,45,45,1.75,800,1,2 "ERCOT-South",39091,39092,39092,44.5,44.5,44.5,-0.5,800,1,2,,,," " "ERCOT-South",39099,39100,39100,62,62,62,17.5,3200,4,6 "ERCOT-South",39100,39101,39101,56.5,56,56.17,-5.83,2400,3,5 "ERCOT-South",39101,39104,39104,55,55,55,-1.17,800,1,2 "ERCOT-South",39104,39105,39105,57.25,57,57.08,2.08,2400,3,4 "ERCOT-South",39105,39106,39106,59,58,58.54,1.46,4800,6,5 "ERCOT-South",39106,39107,39107,58,57.75,57.81,-0.73,3200,4,5 "ERCOT-South",39107,39108,39108,54.5,54.5,54.5,-3.31,800,1,2

115

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

720,38721,38721,69,68,68.6,1.54,74400,63,23 720,38721,38721,69,68,68.6,1.54,74400,63,23 "PJM Wh Real Time Peak",38721,38722,38722,74.25,69,70.77,2.17,68000,68,33 "PJM Wh Real Time Peak",38722,38723,38723,77.75,73.5,76.91,6.14,61600,70,35 "PJM Wh Real Time Peak",38723,38726,38726,74,69,70.06,-6.85,55200,57,22 "PJM Wh Real Time Peak",38726,38727,38727,63,61.75,62.52,-7.54,60800,72,29 "PJM Wh Real Time Peak",38727,38728,38728,55,51,53.51,-9.01,68800,55,30 "PJM Wh Real Time Peak",38728,38729,38729,50.5,49,49.37,-4.14,56000,55,25 "PJM Wh Real Time Peak",38729,38730,38730,50.6,49.5,50.17,0.8,54400,55,25 "PJM Wh Real Time Peak",38730,38733,38733,63.5,59,60.85,10.68,36800,37,23 "PJM Wh Real Time Peak",38733,38734,38734,65,64,64.63,3.78,12000,10,13

116

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

449,39450,39450,74,72,73,1600,2,4 449,39450,39450,74,72,73,1600,2,4 "Entergy",39450,39451,39451,64,64,64,800,1,2 "Entergy",39451,39454,39454,47.5,46.5,47,2400,3,3 "Entergy",39454,39455,39455,41.5,41,41.17,2400,3,3 "Entergy",39455,39456,39456,43,43,43,800,1,2 "Entergy",39456,39457,39457,52,49,50.33,2400,3,5 "Entergy",39457,39458,39458,49,49,49,800,1,2 "Entergy",39458,39461,39461,67,67,67,800,1,2 "Entergy",39461,39462,39462,73,73,73,800,1,2 "Entergy",39462,39463,39463,69,68,68.33,2400,3,5 "Entergy",39463,39464,39464,70,64,68,2400,3,3 "Entergy",39464,39465,39465,65,65,65,1600,2,2 "Entergy",39465,39468,39468,79,75,76.67,2400,3,5 "Entergy",39468,39469,39469,74,73,73.7,4000,5,8

117

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

8720,38721,38721,51,50,50.625,3200,4,4 8720,38721,38721,51,50,50.625,3200,4,4 "Entergy",38721,38722,38722,56.5,53.5,55.3,4000,5,7 "Entergy",38722,38723,38723,60,60,60,5600,6,5 "Entergy",38723,38726,38726,59,58,58.5,1600,2,3 "Entergy",38726,38727,38727,55.5,53,54.1,4000,5,5 "Entergy",38727,38728,38728,53.5,52,53.0938,6400,8,9 "Entergy",38728,38729,38729,49,46,47.6667,9600,11,8 "Entergy",38729,38730,38730,49,47.5,48.0417,4800,6,7 "Entergy",38730,38733,38733,54.25,54.25,54.25,800,1,2 "Entergy",38733,38734,38734,53.75,53.75,53.75,800,1,2 "Entergy",38734,38735,38735,62,58,60.1,4000,5,6 "Entergy",38735,38736,38736,60,58,58.875,4800,4,5 "Entergy",38736,38737,38737,55,50,53.1944,7200,9,8

118

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

623,37624,37624,32.5,29,30.16,20800,26,20 623,37624,37624,32.5,29,30.16,20800,26,20 "Entergy",37624,37627,37627,36.75,34.75,35.54,28800,27,18 "Entergy",37627,37628,37628,38,35.5,36.31,45600,53,26 "Entergy",37628,37629,37629,35,31.25,33.69,26400,33,21 "Entergy",37629,37630,37630,33.55,32.75,33.19,22400,26,20 "Entergy",37630,37631,37631,37.75,34.5,35.51,36000,45,24 "Entergy",37631,37634,37634,43.75,38.25,41.62,36800,46,20 "Entergy",37634,37635,37635,42.5,38,40.72,17600,22,18 "Entergy",37635,37636,37636,43,42,42.61,16800,21,17 "Entergy",37636,37637,37637,43,41.25,42.02,12000,15,15 "Entergy",37637,37638,37638,50,44.15,45.85,8800,10,13 "Entergy",37638,37641,37641,41,39.25,40.1,31200,29,16 "Entergy",37641,37642,37642,41.75,38,40.09,25600,27,15

119

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

43.75,40,42.24,2.81,10000,25,19 43.75,40,42.24,2.81,10000,25,19 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",40,38.75,39.35,-2.89,12400,31,16 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",45,41.5,43.54,4.19,16000,38,20 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",44,42.25,43.09,-0.45,13600,34,19 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",41.5,40,40.64,-2.45,20000,25,16 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",42.25,41,41.35,0.71,14000,34,17

120

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

6894,36895,36895,74.5,74,74.25,1600,2,3 6894,36895,36895,74.5,74,74.25,1600,2,3 "NEPOOL",36899,36900,36900,83,81,82,1600,2,3 "NEPOOL",36900,36901,36901,89,88,88.67,2400,3,3 "NEPOOL",36901,36902,36902,77.5,73,75.25,1600,2,3 "NEPOOL",36902,36903,36903,75.75,75.75,75.75,800,1,2 "NEPOOL",36903,36906,36906,75,74,74.5,2400,3,3 "NEPOOL",36906,36907,36907,80,76.5,77.75,3200,4,3 "NEPOOL",36907,36908,36908,79.5,76,78.38,3200,4,4 "NEPOOL",36908,36909,36909,75.5,74.5,75,3200,3,4 "NEPOOL",36909,36910,36910,71.75,70.75,71.25,1600,2,3 "NEPOOL",36910,36913,36913,74.75,74,74.4,4000,5,3 "NEPOOL",36914,36915,36915,67.5,66.5,67,2400,3,3 "NEPOOL",36915,36916,36916,67,65.75,66.33,2400,3,2 "NEPOOL",36916,36917,36917,65,61.25,63.38,3200,4,3

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

1,47,48.2,3.37,9600,24,17 1,47,48.2,3.37,9600,24,17 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",56,53,55.36,7.17,9600,24,17 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",58.2,55,57.22,1.85,9200,23,17 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",52.25,49,50.04,-7.18,8400,21,19 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",45,43.5,44.24,-5.8,26400,28,22 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",52.5,50,51.46,7.22,7600,19,15

122

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

48,45.75,46.49,-0.96,30000,63,25 48,45.75,46.49,-0.96,30000,63,25 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",47.5,45,46.75,0.26,31600,79,22 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",51,45,45.83,-0.92,40000,50,24 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",51.25,47.75,48.43,2.6,26000,51,22 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",52.75,49.25,50.5,2.07,27200,68,23 "Palo Verde","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",52.5,51.5,52.02,1.52,46400,55,20

123

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

62,66.21,-0.74,44400,109,30 62,66.21,-0.74,44400,109,30 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",60,64.12,-2.09,45200,113,30 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",59,60.9,-3.22,99200,123,29 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",62,63.2,2.3,50400,114,31 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",61.75,62.98,-0.22,48800,122,31

124

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

43.25,42,42.63,4.13,1600,2,4 43.25,42,42.63,4.13,1600,2,4 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",42.65,42.65,42.65,0.02,800,1,2 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",45.25,44,44.86,2.21,5600,7,8 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",46.5,45.75,46.08,1.22,2400,3,6 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",45,45,45,-1.08,4000,4,4 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",44.75,44.75,44.75,-0.25,1600,2,4

125

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

355,38356,38356,56.85,56.25,56.7,6400,7,7 355,38356,38356,56.85,56.25,56.7,6400,7,7 "NEPOOL MH DA LMP",38356,38357,38357,55.25,55,55.0833,2400,3,3 "NEPOOL MH DA LMP",38357,38358,38358,59,59,59,800,1,2 "NEPOOL MH DA LMP",38358,38359,38359,57.5,57,57.25,2400,3,5 "NEPOOL MH DA LMP",38359,38362,38362,55.5,55.5,55.5,3200,4,6 "NEPOOL MH DA LMP",38362,38363,38363,58.75,58,58.575,9600,11,10 "NEPOOL MH DA LMP",38363,38364,38364,57.75,57.5,57.625,1600,2,4 "NEPOOL MH DA LMP",38364,38365,38365,55.75,55.25,55.4688,12800,15,11 "NEPOOL MH DA LMP",38365,38366,38366,58.5,58.25,58.4583,4800,5,6 "NEPOOL MH DA LMP",38366,38369,38369,92,85,88.7143,5600,7,8 "NEPOOL MH DA LMP",38369,38370,38370,97.5,97,97.1667,2400,3,5

126

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

22.6,23.25,-1.53,6400,14,16 22.6,23.25,-1.53,6400,14,16 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",18.25,18.97,-4.28,6400,8,9 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",18,19.32,0.35,5600,14,10 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",17,17.24,-2.08,7200,12,10 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",18,18.61,1.38,7200,17,17

127

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

988,37991,37991,38.5,38,38.29,10400,13,11 988,37991,37991,38.5,38,38.29,10400,13,11 "Entergy",37991,37992,37992,56,50.5,51.79,15200,19,13 "Entergy",37992,37993,37993,60,56,58.95,12000,15,9 "Entergy",37993,37994,37994,55,51,52.44,16800,21,14 "Entergy",37994,37995,37995,43,40.5,41.28,7200,9,9 "Entergy",37995,37998,37998,45,39,40.86,5600,7,8 "Entergy",37998,37999,37999,39.5,38,38.42,8000,10,7 "Entergy",37999,38000,38000,39,36,37.48,10400,12,9 "Entergy",38000,38001,38001,40.25,38,38.66,14400,17,10 "Entergy",38001,38002,38002,39,36.25,36.98,10400,12,9 "Entergy",38002,38005,38005,39,37,37.44,13600,12,9 "Entergy",38005,38006,38006,55,48,52.64,5600,7,10 "Entergy",38006,38007,38007,54,47,50.58,12000,15,11

128

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

65.25,63,64.48,0.53,9600,12,15 65.25,63,64.48,0.53,9600,12,15 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",59,57,57.68,-6.8,20000,23,13 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",58,57,57.45,-0.23,8800,9,9 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",57,55.75,56.53,-0.92,8000,10,12 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",57.5,56,56.46,-0.07,10400,13,10 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",59.25,56.75,58.09,1.63,20000,25,17

129

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

7988,37991,37991,62,62,62,800,1,2 7988,37991,37991,62,62,62,800,1,2 "NEPOOL MH DA LMP",37991,37992,37992,70,69,69.5,1600,2,2 "NEPOOL MH DA LMP",37992,37993,37993,75.25,72,73.81,3200,4,6 "NEPOOL MH DA LMP",37993,37994,37994,81,76,78.3,8000,10,11 "NEPOOL MH DA LMP",37994,37995,37995,85.75,81.5,84.24,12800,16,12 "NEPOOL MH DA LMP",37998,37999,37999,77,72.5,74.12,6400,8,9 "NEPOOL MH DA LMP",37999,38000,38000,120,92,104.81,16800,21,11 "NEPOOL MH DA LMP",38000,38001,38001,375,270,311.75,6400,8,8 "NEPOOL MH DA LMP",38001,38002,38002,175,170,171,4000,5,5 "NEPOOL MH DA LMP",38005,38006,38006,90,84,86.78,7200,9,7 "NEPOOL MH DA LMP",38006,38007,38007,94,81.5,87.42,10400,13,13 "NEPOOL MH DA LMP",38007,38008,38008,76,72,74.69,6400,8,8

130

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

31.9,30.75,31.02,,14000,34,10 31.9,30.75,31.02,,14000,34,10 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",28.85,28,28.3,-2.72,52000,59,13 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",31.5,31,31.22,2.92,20000,41,13 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",34.25,33.4,33.8,2.58,22000,47,13 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",30,29.75,29.9,-3.9,52800,54,16 "NP15","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",28.25,27.85,27.95,-1.95,48000,57,11

131

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

59.05,59,59.03,2.03,1600,2,3 59.05,59,59.03,2.03,1600,2,3 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",63,63,63,3.97,800,1,2 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",62.5,60,61,-2,2400,3,6 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",63.75,63,63.32,2.32,5600,7,8 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",56,55,55.5,-7.82,3200,4,5 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",55.5,55.5,55.5,0,800,1,2

132

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

815,39818,39818,58.5,55.25,56.28,5.13,40000,45,27 815,39818,39818,58.5,55.25,56.28,5.13,40000,45,27 "PJM Wh Real Time Peak",39818,39819,39819,60.25,57.75,58.92,2.64,109600,119,41 "PJM Wh Real Time Peak",39819,39820,39820,58,55,56.66,-2.26,49600,60,29 "PJM Wh Real Time Peak",39820,39821,39821,55.55,55,55.21,-1.45,48000,56,34 "PJM Wh Real Time Peak",39821,39822,39822,63,60.75,61.9,6.69,38400,46,28 "PJM Wh Real Time Peak",39822,39825,39825,69,66,67.63,5.73,62400,74,37 "PJM Wh Real Time Peak",39825,39826,39826,66.5,61,64.03,-3.6,91200,107,40 "PJM Wh Real Time Peak",39826,39827,39827,85.5,80,82.91,18.88,103200,124,50 "PJM Wh Real Time Peak",39827,39828,39828,100,88,93.22,10.31,110400,135,51 "PJM Wh Real Time Peak",39828,39829,39829,110,93,98.58,5.36,77600,93,37

133

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

988,37991,37991,43.25,36,38.11,35200,40,16 988,37991,37991,43.25,36,38.11,35200,40,16 "PJM West",37991,37992,37992,53.5,50,51.99,33600,41,24 "PJM West",37992,37993,37993,70,66.25,67.48,34400,40,25 "PJM West",37993,37994,37994,62,59.65,60.58,36000,41,19 "PJM West",37994,37995,37995,56.75,53,54.66,32800,39,23 "PJM West",37995,37998,37998,53.75,51.25,52.44,40000,47,25 "PJM West",37998,37999,37999,54,52.55,53.14,37600,47,24 "PJM West",37999,38000,38000,65.25,61.5,63.18,30400,37,20 "PJM West",38000,38001,38001,88,77,82.58,50400,57,28 "PJM West",38001,38002,38002,90,77,80.76,31200,37,20 "PJM West",38002,38005,38005,53.25,52.75,53.03,30400,38,18 "PJM West",38005,38006,38006,70,67,68.64,36000,45,24

134

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

150,150,,400,1,2 150,150,,400,1,2 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",180,180,30,2400,3,4 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",310,310,130,400,1,2 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",350,350,40,400,1,2 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",165,165,-185,800,1,2

135

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

1246,41247,41247,27.5,27.5,27.5,0.17,800,1,2 1246,41247,41247,27.5,27.5,27.5,0.17,800,1,2 "Entergy Peak",41247,41248,41248,28.5,28.5,28.5,1,800,1,2 "Entergy Peak",41248,41249,41249,30,30,30,1.5,800,1,2 "Entergy Peak",41250,41253,41253,30,29,29.5,-0.5,1600,2,3 "Entergy Peak",41253,41254,41254,30,29.75,29.88,0.38,1600,2,2 "Entergy Peak",41254,41255,41255,29.75,29.75,29.75,-0.13,800,1,2 "Entergy Peak",41269,41270,41270,32,32,32,2.25,1600,2,2 "Entergy Peak",41355,41358,41358,38.5,38.5,38.5,6.5,800,1,2 "Entergy Peak",41367,41368,41368,35,35,35,-3.5,800,1,2 "Entergy Peak",41425,41428,41428,37,37,37,2,800,1,2 "Entergy Peak",41436,41437,41437,42,42,42,5,800,1,2 "Entergy Peak",41446,41449,41449,41,41,41,-1,800,1,2

136

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

32.5,33.04,-3.33,15200,19,19 32.5,33.04,-3.33,15200,19,19 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",37,37.32,4.28,7600,19,18 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",35,35.46,-1.86,9600,24,22 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",37,38.66,3.2,14800,36,27 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",39.75,40.34,1.69,9200,23,22

137

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

0911,40912,40912,27,26.5,26.83,-2.17,8800,11,6 0911,40912,40912,27,26.5,26.83,-2.17,8800,11,6 "ERCOT Houston",40912,40913,40913,28.3,28,28.18,1.35,4800,6,7 "ERCOT Houston",40913,40914,40914,26.35,26.2,26.29,-1.89,3200,4,6 "ERCOT Houston",40914,40917,40917,27.25,27,27.13,0.84,8000,10,5 "ERCOT Houston",40917,40918,40918,27.75,27.5,27.58,0.45,2400,3,3 "ERCOT Houston",40918,40919,40919,27.5,27.5,27.5,-0.08,1600,2,2 "ERCOT Houston",40919,40920,40920,31.5,31,31.33,3.83,2400,3,4 "ERCOT Houston",40920,40921,40921,31,30.25,30.5,-0.83,2400,2,4 "ERCOT Houston",40925,40926,40926,26,25.75,25.96,-4.54,5600,7,4 "ERCOT Houston",40926,40927,40927,23.75,23.75,23.75,-2.21,2400,3,5 "ERCOT Houston",40928,40931,40931,22.15,22.15,22.15,-1.6,800,1,2

138

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

258,37259,37259,26,22.95,24.08,51200,64,19 258,37259,37259,26,22.95,24.08,51200,64,19 "Entergy",37259,37260,37260,28.25,24.5,26.09,38400,47,17 "Entergy",37260,37263,37263,22.5,17,20.72,34400,43,16 "Entergy",37263,37264,37264,25,19,20.17,19200,24,15 "Entergy",37264,37265,37265,20,19,19.55,44000,54,19 "Entergy",37265,37266,37266,23,18.75,19.31,50400,62,18 "Entergy",37266,37267,37267,19,15,18.21,45600,56,18 "Entergy",37267,37270,37270,18.85,17.4,18.21,65600,81,17 "Entergy",37270,37271,37271,21.75,18.2,19.01,24800,28,18 "Entergy",37271,37272,37272,22.35,18.95,20.98,31200,38,16 "Entergy",37272,37273,37273,22,19,21.2,49600,62,22 "Entergy",37273,37274,37274,22.5,19.5,20.93,46400,55,20 "Entergy",37274,37277,37277,19.75,18.75,19.26,36000,45,18

139

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

SP-15 Gen DA LMP Peak",39904,39905,39905,30.85,30,30.44,"na",69200,129,16 SP-15 Gen DA LMP Peak",39904,39905,39905,30.85,30,30.44,"na",69200,129,16 "SP-15 Gen DA LMP Peak",39905,39906,39907,28.7,27.5,28.03,-2.41,119200,103,17 "SP-15 Gen DA LMP Peak",39906,39909,39909,31.5,30.25,30.5,2.47,43200,89,17 "SP-15 Gen DA LMP Peak",39909,39910,39910,33.3,32.45,32.83,2.33,40800,80,20 "SP-15 Gen DA LMP Peak",39910,39911,39912,29,28,28.69,-4.14,116000,117,22 "SP-15 Gen DA LMP Peak",39911,39913,39914,27.25,26.55,26.88,-1.81,96800,110,21 "SP-15 Gen DA LMP Peak",39912,39916,39916,28.5,27.5,28.01,1.13,58000,119,19 "SP-15 Gen DA LMP Peak",39916,39917,39917,26.65,25,26.27,-1.74,26400,51,17 "SP-15 Gen DA LMP Peak",39917,39918,39918,28.25,27.7,27.97,1.7,55600,101,20

140

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

43,39.05,41.9,4.15,5600,7,8 43,39.05,41.9,4.15,5600,7,8 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",40.5,38.5,39.53,-2.37,3200,4,7 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",39.25,38.25,38.9,-0.63,13600,17,15 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",41.5,39,40,1.1,10400,13,11 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",39,37.75,38.3,-1.7,12000,14,15 "ERCOT Houston","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",44.5,43,43.4,5.1,4000,5,5

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

62.5,65.15,3.64,62800,150,34 62.5,65.15,3.64,62800,150,34 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",54.25,61.54,-3.61,153600,172,34 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",60.5,62.02,0.48,81200,188,36 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",61.75,62.73,0.71,69600,168,34 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",62.75,63.47,0.74,74400,170,34

142

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

1,45.5,-0.2,22800,57,25 1,45.5,-0.2,22800,57,25 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",43.5,45.44,-0.06,96000,198,32 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",42.25,43.27,-2.17,89600,210,33 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",39,42.7,-0.57,118400,261,35 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",42.5,43.86,1.16,169600,196,33

143

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

40182,40183,40183,60.5,60.5,60.5,7.5,800,1,2 40182,40183,40183,60.5,60.5,60.5,7.5,800,1,2 "Entergy Peak",40183,40184,40184,62.25,62.25,62.25,1.75,800,1,2 "Entergy Peak",40189,40190,40190,63.5,60.75,62.42,0.17,2400,3,3 "Entergy Peak",40190,40191,40191,46,45,45.5,-16.92,1600,2,2 "Entergy Peak",40196,40197,40197,40,40,40,-5.5,800,1,2 "Entergy Peak",40197,40198,40198,40,40,40,0,800,1,2 "Entergy Peak",40198,40199,40199,38,38,38,-2,800,1,2 "Entergy Peak",40199,40200,40200,38,38,38,0,800,1,2 "Entergy Peak",40204,40205,40205,47,47,47,9,800,1,2 "Entergy Peak",40205,40206,40206,45,45,45,-2,800,1,2 "Entergy Peak",40206,40207,40207,48,48,48,3,800,1,2 "Entergy Peak",40210,40211,40211,43,43,43,-5,800,1,2

144

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

449,39450,39450,131,114,125.81,37.67,95200,116,49 449,39450,39450,131,114,125.81,37.67,95200,116,49 "PJM Wh Real Time Peak",39450,39451,39451,106,99,102.43,-23.38,78400,96,39 "PJM Wh Real Time Peak",39451,39454,39454,54,52.5,53.44,-48.99,65600,74,34 "PJM Wh Real Time Peak",39454,39455,39455,45,41,42.69,-10.75,87200,98,48 "PJM Wh Real Time Peak",39455,39456,39456,47.5,45,46.31,3.62,47200,57,36 "PJM Wh Real Time Peak",39456,39457,39457,59.5,54.25,57.53,11.22,35200,44,34 "PJM Wh Real Time Peak",39457,39458,39458,51,46.25,48.3,-9.23,72800,88,51 "PJM Wh Real Time Peak",39458,39461,39461,76.5,70,74.88,26.58,103200,121,42 "PJM Wh Real Time Peak",39461,39462,39462,80,75.5,77.94,3.06,109600,127,40 "PJM Wh Real Time Peak",39462,39463,39463,72,68,70.47,-7.47,78400,95,35

145

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

911,40912,40912,56,52,53.84,-11.87,161600,191,55 911,40912,40912,56,52,53.84,-11.87,161600,191,55 "PJM Wh Real Time Peak",40912,40913,40913,39,38,38.7,-15.14,45600,54,30 "PJM Wh Real Time Peak",40913,40914,40914,33.25,33,33.05,-5.65,42400,53,33 "PJM Wh Real Time Peak",40914,40917,40917,37.25,36.5,36.8,3.75,43200,51,34 "PJM Wh Real Time Peak",40917,40918,40918,36,35.25,35.53,-1.27,48000,57,31 "PJM Wh Real Time Peak",40918,40919,40919,35,34.2,34.6,-0.93,32000,40,28 "PJM Wh Real Time Peak",40919,40920,40920,35.5,35,35.14,0.54,43200,48,27 "PJM Wh Real Time Peak",40920,40921,40921,40.75,38.6,39.44,4.3,108000,111,39 "PJM Wh Real Time Peak",40921,40924,40924,43.5,41.6,42.69,3.25,61600,74,39 "PJM Wh Real Time Peak",40924,40925,40925,35.25,34.5,34.68,-8.01,36000,44,23

146

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

Da LMP Peak",41246,41247,41247,48,45.75,47.16,-7.85,40000,48,21 Da LMP Peak",41246,41247,41247,48,45.75,47.16,-7.85,40000,48,21 "Nepool MH Da LMP Peak",41247,41248,41248,58.5,55,57.81,10.65,26400,32,21 "Nepool MH Da LMP Peak",41248,41249,41249,79.75,75,76.49,18.68,32800,39,18 "Nepool MH Da LMP Peak",41249,41250,41250,65,50.5,51.47,-25.02,35200,42,23 "Nepool MH Da LMP Peak",41250,41253,41253,47,45.5,46.48,-4.99,12800,16,14 "Nepool MH Da LMP Peak",41253,41254,41254,50,46,47.3,0.82,38400,44,22 "Nepool MH Da LMP Peak",41254,41255,41255,70,57,59.54,12.24,39200,49,19 "Nepool MH Da LMP Peak",41255,41256,41256,50,48.25,48.97,-10.57,53600,59,29 "Nepool MH Da LMP Peak",41256,41257,41257,39.25,38.5,38.98,-9.99,11200,14,10 "Nepool MH Da LMP Peak",41257,41260,41260,45,45,45,6.02,3200,4,6

147

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

82,75,79.66,6.43,30400,38,26 82,75,79.66,6.43,30400,38,26 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",62,58,60.11,-19.55,24000,30,22 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",45.05,43.75,44.81,-15.3,24000,28,17 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",38,36,36.89,-7.92,35200,39,17 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",44,41.5,42.84,5.95,32000,39,23 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",48,44,46.44,3.6,22400,28,20

148

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

46,48.6,-4.22,46000,115,33 46,48.6,-4.22,46000,115,33 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",46.5,49.21,0.61,51600,120,30 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",45.75,46.71,-2.5,123200,150,36 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",46.5,49.35,2.64,63600,151,36 "Mid Columbia Peak","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",47.3,49.44,0.09,65600,163,34

149

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

39815,39818,39818,42,39,41,4.5,2400,3,4 39815,39818,39818,42,39,41,4.5,2400,3,4 "Entergy Peak",39818,39819,39819,44.5,44.5,44.5,3.5,800,1,2 "Entergy Peak",39819,39820,39820,44.5,44,44.25,-0.25,1600,2,4 "Entergy Peak",39820,39821,39821,46,45,45.5,1.25,2400,3,6 "Entergy Peak",39821,39822,39822,45,45,45,-0.5,800,1,2 "Entergy Peak",39822,39825,39825,45,40,42.5,-2.5,1600,2,3 "Entergy Peak",39825,39826,39826,48,48,48,5.5,1600,2,3 "Entergy Peak",39827,39828,39828,55,53,54,6,1600,2,4 "Entergy Peak",39828,39829,39829,56,53,54.33,0.33,2400,3,5 "Entergy Peak",39832,39833,39833,42.5,42.5,42.5,-11.83,800,1,2 "Entergy Peak",39833,39834,39834,43,42,42.5,0,1600,2,4 "Entergy Peak",39836,39839,39839,40,38,39,-3.5,1600,2,3

150

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

1246,41247,41247,30,30,30,-2.63,1600,2,2 1246,41247,41247,30,30,30,-2.63,1600,2,2 "ERCOT Houston",41250,41253,41253,33,33,33,3,800,1,2 "ERCOT Houston",41260,41261,41261,27,26.9,26.98,-6.02,4000,5,4 "ERCOT Houston",41263,41264,41264,28.5,28.25,28.33,1.35,2400,3,4 "ERCOT Houston",41270,41271,41271,26.5,26.5,26.5,-1.83,800,1,2 "ERCOT Houston",41288,41289,41289,34.25,34,34.13,7.63,1600,2,3 "ERCOT Houston",41289,41290,41290,33.85,33.75,33.78,-0.35,2400,3,4 "ERCOT Houston",41338,41339,41339,34.75,34.25,34.58,0.8,2400,3,3 "ERCOT Houston",41372,41373,41373,42.75,42.75,42.75,8.17,800,1,2 "ERCOT Houston",41381,41382,41382,35.55,35.55,35.55,-7.2,800,1,2 "ERCOT Houston",41386,41387,41387,37.5,37.5,37.5,1.95,800,1,2

151

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

60.75,57.5,59.33,7.47,34400,42,23 60.75,57.5,59.33,7.47,34400,42,23 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",58.5,55,56.62,-2.71,36800,45,25 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",65,62.25,63.61,6.99,76000,86,34 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",66.5,60,63.84,0.23,43200,52,26 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",58.5,55,57.1,-6.74,36000,41,21 "Indiana","application/vnd.ms-excel","application/vnd.ms-excel","application/vnd.ms-excel",48,44,46.02,-11.08,33600,42,27

152

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

546,40547,40547,37,37,37,0,800,1,2 546,40547,40547,37,37,37,0,800,1,2 "Entergy Peak",40547,40548,40548,36,36,36,-1,800,1,2 "Entergy Peak",40548,40549,40549,33.75,33.75,33.75,-2.25,1600,2,2 "Entergy Peak",40550,40553,40553,42,42,42,8.25,800,1,2 "Entergy Peak",40555,40556,40556,52.75,49,50.88,8.88,1600,2,3 "Entergy Peak",40562,40563,40563,38.5,38,38.1,-12.78,4000,5,4 "Entergy Peak",40563,40564,40564,39,39,39,0.9,800,1,2 "Entergy Peak",40567,40568,40568,39,39,39,0,800,1,2 "Entergy Peak",40568,40569,40569,38,38,38,-1,800,1,2 "Entergy Peak",40571,40574,40574,36,36,36,-2,800,1,2 "Entergy Peak",40574,40575,40575,39.5,39.5,39.5,3.5,800,1,2 "Entergy Peak",40575,40576,40576,37,36.5,36.75,-2.75,1600,2,2

153

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Change","Daily Volume MWh","Number of Trades","Number of Counterparties"  

U.S. Energy Information Administration (EIA) Indexed Site

DA LMP",40911,40912,40912,92,84.75,87.16,-14.07,46400,56,29 DA LMP",40911,40912,40912,92,84.75,87.16,-14.07,46400,56,29 "Nepool MH DA LMP",40912,40913,40913,49,46,47.55,-39.61,78400,77,24 "Nepool MH DA LMP",40913,40914,40914,39.75,39.25,39.57,-7.98,12000,15,10 "Nepool MH DA LMP",40914,40917,40917,39,38,38.39,-1.18,8800,11,9 "Nepool MH DA LMP",40917,40918,40918,38.25,38,38.14,-0.25,8000,9,11 "Nepool MH DA LMP",40918,40919,40919,41.5,39.9,40.88,2.74,70400,83,25 "Nepool MH DA LMP",40919,40920,40920,37.25,36.75,36.83,-4.05,20000,23,16 "Nepool MH DA LMP",40920,40921,40921,44,43.5,43.73,6.9,11200,11,12 "Nepool MH DA LMP",40921,40924,40924,67,65.5,66.35,22.62,16800,21,15 "Nepool MH DA LMP",40924,40925,40925,50.75,50,50.24,-16.11,11200,14,12

154

"Price Hub","Trade Date","Delivery Start Date","Delivery End Date","High Price $/MWh","Low Price $/MWh","Wtd Avg Price $/MWh","Daily Volume MWh","Number of Trades","Number of Companies"  

U.S. Energy Information Administration (EIA) Indexed Site

6893,36894,36894,65.5,64.5,65,1600,2,2 6893,36894,36894,65.5,64.5,65,1600,2,2 "PJM West",36894,36895,36895,63,59.5,61.25,3200,4,2 "PJM West",36895,36896,36896,60,58.5,59.12,4800,6,4 "PJM West",36899,36900,36900,59.5,59.5,59.5,800,1,2 "PJM West",36900,36901,36901,58,55.5,56.61,5600,7,6 "PJM West",36901,36902,36902,50.5,49,49.75,3200,4,4 "PJM West",36902,36903,36903,47,46,46.33,4800,6,3 "PJM West",36903,36906,36906,45.5,45,45.12,3200,4,6 "PJM West",36906,36907,36907,46,42,44.21,5600,7,6 "PJM West",36907,36908,36908,42.5,42,42.4,4000,4,7 "PJM West",36908,36909,36909,41,39,39.56,7200,7,6 "PJM West",36909,36910,36910,39.5,39,39.25,2400,3,5 "PJM West",36910,36913,36913,51,50,50.43,5600,5,6

155

MCBRIDE, GRAHAM B. Simple calculation of daily photosynthesis ...  

Science Journals Connector (OSTI)

Simple calculation of daily photosynthesis by means of five photosynthesis-light equations. Abstract-The performance of five well-known photosynthesis-light...

2000-03-19T23:59:59.000Z

156

Predicting Daily Net Radiation Using Minimum Climatological Data1  

E-Print Network (OSTI)

Predicting Daily Net Radiation Using Minimum Climatological Data1 S. Irmak, M.ASCE2 ; A. Irmak3 ; J for predicting daily Rn have been widely used. However, when the paucity of detailed climatological data with National Weather Service climatological datasets that only record Tmax and Tmin on a regular basis. DOI: 10

157

SCIENTIFIC NOTE Variations in daily quality assurance dosimetry from device  

E-Print Network (OSTI)

SCIENTIFIC NOTE Variations in daily quality assurance dosimetry from device levelling, feet procedures are an essential part of radiotherapy medical physics. Devices such as the Sun Nuclear, DQA3 are effective tools for analysis of daily dosimetry including flatness, symmetry, energy, field size and central

Yu, K.N.

158

Backstage at the Daily Show | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Backstage at the Daily Show Backstage at the Daily Show Backstage at the Daily Show Addthis Description Backstage footage from Secretary Chu's appearance on the Daily Show where he discuses the green room candy dish and possible lighting considerations. Speakers Secretary Steven Chu Duration 1:32 Topic Energy Efficiency Credit Energy Department Video SECRETARY STEVEN CHU: I'm in the famous green room of the Jon Stewart show. If you look around, I have all these games: Monopoly, a Rubik's Cube, Pictureka! Now if - this is to amuse myself, but in actual fact, the most famous part of this room is this. There's enough chocolate here to put you on a high that - (chuckles) - will really get you going. This is my wife, Jean. JEAN CHU: (Chuckles.) I'm - (chuckles) - edit this out! (Begin recorded segment.)

159

Daily Reporting Rainfall Station HERBERT RIVER Manual Heavy Rainfall Station  

E-Print Network (OSTI)

Daily Reporting Rainfall Station HERBERT RIVER Manual Heavy Rainfall Station Manual River Station Central Mill AL Tung Oil AL Corsis AL Innisfail Clump Point Tide TM Mourilyan Harbour TM 0 10 kilometres

Greenslade, Diana

160

Invisible Science: Lab Breakthroughs in Our Daily Lives | Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Invisible Science: Lab Breakthroughs in Our Daily Lives Invisible Science: Lab Breakthroughs in Our Daily Lives Invisible Science: Lab Breakthroughs in Our Daily Lives April 24, 2012 - 2:30pm Addthis The Lab Breakthroughs video series focuses on the array of technological advancements and discoveries that stem from research performed in the National Labs, including improvements in industrial processes, discoveries in fundamental scientific research, and innovative medicines. See the Lab Breakthroughs topic page for the most recent videos and Q&As with researchers. The Lab Breakthroughs video series focuses on the array of technological advancements and discoveries that stem from research performed in the National Labs, including improvements in industrial processes, discoveries

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Daylighter Daily Solar Roof Light | Open Energy Information  

Open Energy Info (EERE)

Daylighter Daily Solar Roof Light Daylighter Daily Solar Roof Light Jump to: navigation, search Name Daylighter Daily Solar Roof Light Address 1991 Crocker Road, Suite 600 Place Cleveland, Ohio Zip 44145 Sector Solar Product Installation; Manufacturing Phone number 440-892-3312 Website http://www.SolarLightisFree.co Coordinates 41.4648875°, -81.9506519° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":41.4648875,"lon":-81.9506519,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

162

Warm Weather and the Daily Commute | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Warm Weather and the Daily Commute Warm Weather and the Daily Commute Warm Weather and the Daily Commute May 7, 2013 - 12:02pm Addthis Biking to work helps you get some exercise while reducing your carbon footprint. | Photo courtesy of iStockphoto.com/olaser Biking to work helps you get some exercise while reducing your carbon footprint. | Photo courtesy of iStockphoto.com/olaser Elizabeth Spencer Communicator, National Renewable Energy Laboratory How can I participate? Check out options for busing or carpooling in your area or, if you live close, try walking or biking to work. You know the weather is starting to warm up when you start hearing about those "bike, bus, or walk to work" challenges. And while my local news just started drumming up publicity for theirs, I've seen these events pop up in

163

E-Print Network 3.0 - annual average daily traffic Sample Search...  

NLE Websites -- All DOE Office Websites (Extended Search)

Data Systems 2000. Annual Average Daily Truck Traffic on the California State... Lockout and Non-Lockout Weekdays Average Daily Traffic Volume (vehday) All Cars Trucks ......

164

E-Print Network 3.0 - average daily traffic Sample Search Results  

NLE Websites -- All DOE Office Websites (Extended Search)

Data Systems 2000. Annual Average Daily Truck Traffic on the California State... Lockout and Non-Lockout Weekdays Average Daily Traffic Volume (vehday) All Cars Trucks...

165

Daily Cycle of Precipitation over the Northern Coast of Brazil  

Science Journals Connector (OSTI)

The daily cycle of precipitation (DCP) in the austral autumn on the northern coast of Brazil (NCB) is examined in detail. The Tropical Rainfall Measuring Mission 3B42 dataset was used to obtain the DCP, and the intradaily variability was measured ...

Sheila Santana de Barros Brito; Marcos Daisuke Oyama

2014-11-01T23:59:59.000Z

166

Generating Multiyear Gridded Daily Rainfall over New Zealand  

Science Journals Connector (OSTI)

Daily rainfall totals are a key input for hydrological models that are designed to simulate water and pollutant flow through both soil and waterways. Within New Zealand there are large areas and many river catchments where no long-term rainfall ...

Andrew Tait; Richard Turner

2005-09-01T23:59:59.000Z

167

Modelling Daily Multivariate Pollutant Data at Multiple Sites  

E-Print Network (OSTI)

. In conducting such time series studies to investigate the relationship between air pollution and a health investigating the health effects of daily changes in air pollution, the exposures are essentially treated effects of air pollution. Alternative objectives include the design problem of the positioning of a new

Washington at Seattle, University of

168

A Feasibility Study: Mining Daily Traces for Home Heating Control  

E-Print Network (OSTI)

savings as well as 14.9%­59.2% reduction in miss time. Keywords Energy, home heating, daily traces, prediction 1. INTRODUCTION Heating, ventilation and cooling (HVAC) contributes most to a home's energy bills, accounting for 48% of residential energy consumption in the U.S. and 61% in the U.K., 64% in Canada where

Whitehouse, Kamin

169

ENVIRONMENTAL LEADER: THE EXECUTIVE'S DAILY GREEN BRIEFING APRIL 25, 2008  

E-Print Network (OSTI)

ENVIRONMENTAL LEADER: THE EXECUTIVE'S DAILY GREEN BRIEFING APRIL 25, 2008 Green Business Experts at MMA Renewable Ventures, a renewable energy firm in San Francisco and formerly the Business Solutions Fellow for the Pew Center on Global Climate Change. http://www.environmentalleader.com/2008/04/25/green-business

Hoffman, Andrew J.

170

KWH_APS_DPP07_1Page.ppt  

NLE Websites -- All DOE Office Websites (Extended Search)

Ion-Temperature and Rotation-Velocity Profiles from a Spatially Resolving X-Ray Crystal Spectrometer on Alcator C-Mod Ion-Temperature and Rotation-Velocity Profiles from a Spatially Resolving X-Ray Crystal Spectrometer on Alcator C-Mod K. W. Hill, 1 M. Bitter, 1 P. Beiersdorfer, 3 Ch. Broennimann, 4 E. F. Eikenberry, 4 A. Ince-Cushman, 2 Ming-Feng Gu, 3 S. G. Lee, 5 M. Reinke, 2 J. E. Rice, 2 S. D. Scott, 1 and B. Stratton 1 1 Princeton Plasma Physics Laboratory, Princeton, NJ 2 MIT Plasma Science and Fusion Center, Cambridge, MA 3 LLNL, Livermore, CA 4 DECTRIS Ltd., 5232 Villigen-PSI, Switzerland 5 NFRC, Korea Basic Science Institute, Daejeon, Korea Abstract A new x-ray crystal spectrometer capable of providing spatially (~1.5 cm) and temporally (~10 ms) resolved, high resolution spectra of He-like Ar Kα lines has been installed on Alcator C-Mod. The imaging spectrometer consists of a

171

kWh Analytics: Quality Ratings for PV  

Energy.gov (U.S. Department of Energy (DOE))

This presentation summarizes the information given during the SunShot Grand Challenge Summit and Technology Forum, June 13-14, 2012.

172

Comparing Mainframe and Windows Server Transactions per kWh  

E-Print Network (OSTI)

........................................................................................14 Appendix A. Platform Comparison and Conversion Factors...............................................................................................................15 Conversion Factors............................................................................................................................3 Objective: Estimate Energy Consumption for Similar Uses

Narasayya, Vivek

173

Do Diurnal Aerosol Changes Affect Daily Average Radiative Forcing?  

SciTech Connect

Strong diurnal variability of aerosol has been observed frequently for many urban/industrial regions. How this variability may alter the direct aerosol radiative forcing (DARF), however, is largely unknown. To quantify changes in the time-averaged DARF, we perform an assessment of 29 days of high temporal resolution ground-based data collected during the Two-Column Aerosol Project (TCAP) on Cape Cod, which is downwind of metropolitan areas. We demonstrate that strong diurnal changes of aerosol loading (about 20% on average) have a negligible impact on the 24-h average DARF, when daily averaged optical properties are used to find this quantity. However, when there is a sparse temporal sampling of aerosol properties, which may preclude the calculation of daily averaged optical properties, large errors (up to 100%) in the computed DARF may occur. We describe a simple way of reducing these errors, which suggests the minimal temporal sampling needed to accurately find the forcing.

Kassianov, Evgueni I.; Barnard, James C.; Pekour, Mikhail S.; Berg, Larry K.; Michalsky, Joseph J.; Lantz, K.; Hodges, G. B.

2013-06-17T23:59:59.000Z

174

Yearly-averaged daily usefulness efficiency of heliostat surfaces  

SciTech Connect

An analytical expression for estimating the instantaneous usefulness efficiency of a heliostat surface is obtained. A systematic procedure is then introduced to calculate the usefulness efficiency even when overlapping of blocking and shadowing on a heliostat surface exist. For possible estimation of the reflected energy from a given field, the local yearly-averaged daily usefulness efficiency is calculated. This efficiency is found to depend on site latitude angle, radial distance from the tower measured in tower heights, heliostat position azimuth angle and the radial spacing between heliostats. Charts for the local yearly-averaged daily usefulness efficiency are presented for {phi} = 0, 15, 30, and 45 N. These charts can be used in calculating the reflected radiation from a given cell. Utilization of these charts is demonstrated.

Elsayed, M.M.; Habeebuallah, M.B.; Al-Rabghi, O.M. (King Abdulaziz Univ., Jeddah (Saudi Arabia))

1992-08-01T23:59:59.000Z

175

IEP - Water-Energy Interface: Total Maximum Daily Load Page  

NLE Websites -- All DOE Office Websites (Extended Search)

Total Maximum Daily Loads (TMDLs) Total Maximum Daily Loads (TMDLs) The overall goal of the Clean Water Act is to "restore and maintain the chemical, physical, and biological integrity of the Nation’s waters." In 1999, EPA proposed changes to Section 303(d), to establish Total Maximum Daily Loads (TMDLs) for watersheds that do not meet this goal. The TMDL is the highest amount of a given pollutant that is permissible in that body of water over a given period of time. TMDLs include both waste load allocation (WLA) for point sources and load allocations for non-point sources. In Appalachia, acid mine drainage (AMD) is the single most damaging non-point source. There is also particular concern of the atmospheric deposition of airborne sulfur, nitrogen, and mercury compounds. States are currently in the process of developing comprehensive lists of impaired waters and establishing TMDLs for those waters. EPA has recently proposed a final rule that will require states to develop TMDLs and implement plans for improving water quality within the next 10 years. Under the new rule, TMDL credits could be traded within a watershed.

176

Daily Dialysis Lessons from a Randomized, Controlled Trial  

Science Journals Connector (OSTI)

...as urea, which rapidly equilibrate among body-fluid compartments. With thrice-weekly hemodialysis, the relatively long interval between dialysis sessions results in a "peak-and-valley" effect characterized by fluctuations in the levels of toxins and body-fluid volume, affecting the ability of patients... The frequency of dialysis was established at three times a week in 1965,1 and this frequency has been used in most centers around the world. Soon after the establishment of this dialysis schedule, an analogue simulation concluded that daily (also known as ...

Twardowski Z.J.; Misra M.

2010-12-09T23:59:59.000Z

177

Climbing and the daily energy cost of locomotion in wild chimpanzees: implications for hominoid locomotor evolution  

E-Print Network (OSTI)

Climbing and the daily energy cost of locomotion in wild chimpanzees: implications for hominoid in a population of wild chimpanzees and used published equations to calculate the relative daily energy costs, specifically whether arboreal adaptations serve to minimize daily locomotor energy costs by decreasing

Pontzer, Herman

178

Form EIA-930 HOURLY AND DAILY BALANCING AUTHORITY OPERATIONS REPORT  

U.S. Energy Information Administration (EIA) Indexed Site

930 930 HOURLY AND DAILY BALANCING AUTHORITY OPERATIONS REPORT INSTRUCTIONS Due Date: mm/dd/yyyy Approved: OMB No. 1905-0129 Approval Expires: 10/31/2016 Burden: 0.19 hours Page 1 Draft for Discussion only PURPOSE Form EIA-930 requires Internet posting of hourly balancing authority operating data. The posted data are used to monitor the current status and trends of the electric power industry, and to support enhancement of electric system operations. REQUIRED RESPONDENTS For the contiguous United States: all entities that are listed in NERC's Compliance Registry as a balancing authority must post balancing authority operating information required by this survey. Other than the Midwest ISO (MISO), registered balancing authorities that are parties

179

DEMOGRAPHIC PROFILE CLARKE CO. GEORGIA TOTAL Avg. Co. in GA  

E-Print Network (OSTI)

Median household income, 2010 model-based estimate $34,000 $46,252 $39,196 Persons below poverty level,633,596 9,450 % Black 53.9 38.4 35.1 % White 18.6 43.1 53.7 % Hispanic 21.6 12.0 7.3 % students absent > 15

Teskey, Robert O.

180

McGinness Hills Well 27A-10 Daily Drilling Report Data  

SciTech Connect

This data should be used with the daily drilling record and other data which can be obtained from the contact listed below

Knudsen, Steven

2014-03-25T23:59:59.000Z

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

McGinness Hills Well 27A-10 Daily Drilling Report Data  

DOE Data Explorer (OSTI)

This data should be used with the daily drilling record and other data which can be obtained from the contact listed below

Knudsen, Steven

182

E-Print Network 3.0 - amplitude daily geomagnetic Sample Search...  

NLE Websites -- All DOE Office Websites (Extended Search)

level of geomagnetic disturbances. The anomalies were registered daily... -speed solar wind, mag- netic field disturbances in the interplanetary space and in the geomagnetic...

183

Future projections of daily precipitation and its extremes in simulations of 21st century climate change.  

E-Print Network (OSTI)

??The current generation of climate models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) is used to assess the future changes in daily precipitation (more)

Yin, Lei

2013-01-01T23:59:59.000Z

184

Arctic daily temperature and precipitation extremes: Observed and simulated physical behavior.  

E-Print Network (OSTI)

??ARCTIC DAILY TEMPERATURE AND PRECIPITATION EXTREMES: OBSERVED AND SIMULATED PHYSICAL BEHAVIOR Justin M. Glisan Department of Geological and Atmospheric Sciences, Iowa State University, Ames, Iowa (more)

Glisan, Justin Michael

2012-01-01T23:59:59.000Z

185

Daily torpor in mice: high foraging costs trigger energy-saving hypothermia  

Science Journals Connector (OSTI)

...high foraging costs trigger energy-saving hypothermia Kristin A. Schubert...the use of daily torpor as an energy-saving strategy. The finding that daily...metabolic rate over time represented energy savings which ranged from 1-8 kJ d1...

2010-01-01T23:59:59.000Z

186

Daily routines of body mass gain in birds: 2. An experiment with reduced food availability  

E-Print Network (OSTI)

; published online 31 July 2006; MS. number: 8608R) Theoretical models predict that small birds should adjust daily patterns of body mass gain in response to environmental and internal factors. In a companion paper, we described a model on daily fattening that allows the analysis of precise changes in the shape

Carrascal, Luis M.

187

Intra-daily variations in volatility and transaction costs in the Credit Default Swap market  

E-Print Network (OSTI)

Intra-daily variations in volatility and transaction costs in the Credit Default Swap market Andras : Credit Default Swap, Intra-daily patterns, Stochastic transaction costs, Volatility, Interdealer market on the Microstructure of Financial Markets in Hong Kong, the 2008 Credit conference in Venice, the Third Annual Risk

Del Moral , Pierre

188

Statistical Characteristics of Daily Precipitation: Comparisons of Gridded and Point Datasets  

E-Print Network (OSTI)

Statistical Characteristics of Daily Precipitation: Comparisons of Gridded and Point Datasets Gauge Dataset (URD) and those of its nearest (rain gauge) station. To further examine differences between the two datasets, return periods of daily precipitation were calculated over a region encompassing

Roy Chowdhury, Rinku

189

ELPIS-JP: a dataset of local-scale daily climate change scenarios for Japan  

Science Journals Connector (OSTI)

...the advanced research WRF version 3Boulder, CONational...Semenov1991A serial approach to local stochastic weather modelsEcol...ELPIS-JP: a dataset of local-scale daily climate...developed a dataset of local-scale daily climate...relative humidity; and wind speed) at 938 sites in...

2012-01-01T23:59:59.000Z

190

Changes in daily temperature and precipitation extremes in central and south Asia  

E-Print Network (OSTI)

Changes in daily temperature and precipitation extremes in central and south Asia A. M. G. Klein in indices of climate extremes are studied on the basis of daily series of temperature and precipitation, the indices of temperature extremes indicate warming of both the cold tail and the warm tail

Klein Tank, Albert

191

Principal Investigators: Long-Term Daily and Monthly Climate Records from  

NLE Websites -- All DOE Office Websites (Extended Search)

Principal Investigators: Long-Term Daily and Monthly Climate Records from Principal Investigators: Long-Term Daily and Monthly Climate Records from Stations Across the Contiguous United States M.J. Menne, C.N. Williams, Jr., and R.S. Vose National Climatic Data Center National Oceanic and Atmospheric Administration CDIAC and the USHCN PIs encourage users to make this site their main source for obtaining USHCN data, where you can take advantage of data plotting, and, for daily data, user-friendly station-specific downloading. This site will update both daily and monthly data near the beginning of each year, so as to include data through December of the previous year. However, if you need real-time data updates, you should visit the NCDC website. For NCDC-updated daily data please use the Global Historical Climatology Network (GHCN) website where you will find a directory of USHCN stations.

192

Today in Energy - Daily Prices - Prices - U.S. Energy Information  

Gasoline and Diesel Fuel Update (EIA)

December 20, 2013Daily Prices December 20, 2013Daily Prices Daily wholesale and retail prices for various energy products are shown below, including spot prices and select futures prices at national or regional levels. Prices are updated each weekday (excluding federal holidays), typically between 7:30 and 8:30 a.m. This page is meant to provide a snapshot of selected daily prices only. Prices are republished by EIA with permission as follows: Wholesale Spot Petroleum Prices from Thomson Reuters, Retail Petroleum Prices from AAA Fuel Gauge Report, Prompt-Month Energy Futures from CME Group, and Select Spot Prices from SNL Energy. Daily Prices Wholesale Spot Petroleum Prices, 12/19/13 Close Product Area Price Percent Change* Crude Oil ($/barrel) WTI 98.40 +0.8 Brent 110.78 +1.1 Louisiana Light 108.27 +4.9

193

Get Daily Energy Analysis Delivered to Your Website | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Get Daily Energy Analysis Delivered to Your Website Get Daily Energy Analysis Delivered to Your Website Get Daily Energy Analysis Delivered to Your Website August 8, 2011 - 3:39pm Addthis Get Daily Energy Analysis Delivered to Your Website Matthew Loveless Matthew Loveless Data Integration Specialist, Office of Public Affairs How can I participate? Go to EIA's outreach page for Today in Energy widgets, badges and banners. Now everyone can feature the U.S. Energy Information Administration's (EIA) Today in Energy content on their website and favorite social networking sites. Today in Energy, the agency's education product published every weekday, highlights current energy issues, topics, and data trends in short articles written in plain language. EIA has banners and widgets in different colors and sizes to fit many different websites.

194

Background: Long-Term Daily and Monthly Climate Records from Stations  

NLE Websites -- All DOE Office Websites (Extended Search)

Background: Long-Term Daily and Monthly Climate Records from Stations Background: Long-Term Daily and Monthly Climate Records from Stations Across the Contiguous United States The United States Historical Climatology Network (USHCN) is a high-quality data set of daily and monthly records of basic meteorological variables from 1218 observing stations across the 48 contiguous United States. Daily data include observations of maximum and minimum temperature, precipitation amount, snowfall amount, and snow depth; monthly data consist of monthly-averaged maximum, minimum, and mean temperature and total monthly precipitation. Most of these stations are U.S. Cooperative Observing Network stations located generally in rural locations, while some are National Weather Service First-Order stations that are often located in more urbanized environments. The USHCN has been developed over the years at

195

A stochastic model for the daily coordination of pumped storage hydro plants and wind power plants  

Science Journals Connector (OSTI)

We propose a stochastic model for the daily operation scheduling of a generation system including pumped storage hydro plants and wind power plants, where the uncertainty is represented by the hourly wind power p...

Maria Teresa Vespucci; Francesca Maggioni

2012-03-01T23:59:59.000Z

196

U.S. Daily Temperatures: The Meaning of Extremes in the Context of Nonnormality  

Science Journals Connector (OSTI)

Variations in extreme daily temperatures are explored in relation to changes in seasonal mean temperature using 1218 high-quality U.S. temperature stations spanning 19002012. Extreme temperatures are amplified (or damped) by as much as 50% ...

P. Huybers; K. A. McKinnon; A. Rhines; M. Tingley

2014-10-01T23:59:59.000Z

197

Daily Reporting Rainfall Station TULLY & JOHNSTONE RIVERS Manual Heavy Rainfall Station  

E-Print Network (OSTI)

Daily Reporting Rainfall Station TULLY & JOHNSTONE RIVERS Manual Heavy Rainfall Station Manual Tide TM Bulgun Ck AL Bingil Bay The Boulders TM Nerada AL Tung Oil AL Fishers Ck TM Corsis AL Russell

Greenslade, Diana

198

Daily Reporting Rainfall Station TULLY & JOHNSTONE RIVERS Manual Heavy Rainfall Station  

E-Print Network (OSTI)

Daily Reporting Rainfall Station TULLY & JOHNSTONE RIVERS Manual Heavy Rainfall Station Manual The Boulders TM Nerada AL Tung Oil AL Fishers Ck TM Corsis AL RussellR Babinda Clyde Rd AL Central Mill AL

Greenslade, Diana

199

LCA comparison of windrow composting of yard wastes with use as alternative daily cover (ADC)  

E-Print Network (OSTI)

LCA comparison of windrow composting of yard wastes with use as alternative daily cover (ADC) Rob Assessment was made using the SimaPro LCA software and showed that the ADC scenario is more beneficial

Columbia University

200

Nanotechnology in our Daily Life Iridescent car paint: Based on interference colors  

E-Print Network (OSTI)

Nanotechnology in our Daily Life Iridescent car paint: Based on interference colors (like a butterly, no bleaching after 5 years Miami) #12;Nanotechnology on our Desktops Hard Disk Sensor Medium

Himpsel, Franz J.

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Daily torpor in mice: high foraging costs trigger energy-saving hypothermia  

Science Journals Connector (OSTI)

...strategies to save energy. Facultative daily...between environmental quality, foraging behaviour...environmental quality|foraging costs|energy balance| 1. Introduction...foraging costs in poor quality habitat. As an...strategy to maintain energy balance, natural...

2010-01-01T23:59:59.000Z

202

Developing hourly weather data for locations having only daily weather data  

SciTech Connect

A methodology was developed to modify an hourly TMY weather tape to be representative of a location for which only average daily weather parameters were avilable. Typical hourly and daily variations in solar flux, and other parameters, were needed to properly exercise a computer model to predict the transient performance of a solar controlled greenhouse being designed for Riyadh, Saudi Arabia. The starting point was a TMY tape for Yuma, Arizona, since the design temperatures for summer and winter are nearly identical for Yuma and Riyadh. After comparing six of the most important weather variables, the hourly values on the Yuma tape were individually adjusted to give the same overall daily average conditions as existed in the long-term Riyadh data. Finally, a statistical analysis was used to confirm quantitatively that the daily variations between the long term average values for Riyadh and the modified TMY weather tape for Yuma matched satisfactorily.

Talbert, S.G.; Herold, K.E.; Jakob, F.E.; Lundstrom, D.K.

1983-06-01T23:59:59.000Z

203

Cakewalking into representation : Gabriele Mnter's America travels (1898-1900) and art of dailiness  

E-Print Network (OSTI)

This study explores the fashioning of Gabriele Mnter as a German modernist with a focus on the eclipse of her struggles in coming to representation, the rich complexity of her processes, and the importance of dailiness ...

Bible, Ann Vollmann

2008-01-01T23:59:59.000Z

204

Dynamic Shape Modeling of Consumers Daily Load Based on Data Mining  

Science Journals Connector (OSTI)

The shape characteristic of daily power consumption of consumers can be applied to guide their power consumption behaviors and improve load structures of power system. It is also the basis to obtain the shape cha...

Lianmei Zhang; Shihong Chen; Qiping Hu

2005-01-01T23:59:59.000Z

205

Micro-simulation of daily activity-travel patterns for travel demand forecasting  

Science Journals Connector (OSTI)

The development and initial validation results of a micro-simulator for the generation of daily activity-travel patterns are presented in this paper. The simulator assumes a sequential history and time-of-day ...

Ryuichi Kitamura; Cynthia Chen; Ram M. Pendyala; Ravi Narayanan

206

African Press International (API) This is your "Daily Online News Channel".  

E-Print Network (OSTI)

African Press International (API) This is your "Daily Online News Channel". Home A:Contact us powerful as before ­ Is this good for new Kenya? (api) The travelling man: Pope Benedict XVI is due

207

Review of Methods to Map Peoples Daily Activity Application for Smart Homes  

Science Journals Connector (OSTI)

Peoples daily activity in their home has widespread implications, including health and energy ... the winter of 2012. Within a smart home, these methods could potentially be used to...

Stephanie Gauthier; David Shipworth

2013-01-01T23:59:59.000Z

208

Automation: A Step toward Improving the Quality of Daily Temperature Data Produced by Climate Observing Networks  

Science Journals Connector (OSTI)

The research documented in this manuscript demonstrates that undeniable differences exist between values of daily temperature recorded by the National Weather Service Cooperative Observer Program network and data recorded by the Oklahoma Mesonet. ...

Christopher A. Fiebrich; Kenneth C. Crawford

2009-07-01T23:59:59.000Z

209

Grid History: A Geostationary Satellite Technique for Estimating Daily Rainfall in the Tropics  

Science Journals Connector (OSTI)

A new technique is described for estimating daily rainfall by means of visible and infrared geostationary satellite imagery. It is designed for the tropics and warm-season midlatitudes. Because it operates on a grid of points and measures time ...

David W. Martin; Michael R. Howland

1986-02-01T23:59:59.000Z

210

Combined Total Amount of Oil and Gas Recovered Daily from the...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

XLS Combined Total Amount of Oil and Gas Recovered Daily from the Top Hat and Choke Line oil recovery systems - XLS Updated through 12:00 AM on July 16, 2010. 52Item84Recovery...

211

Combined Total Amount of Oil and Gas Recovered Daily from the...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

ODS format Combined Total Amount of Oil and Gas Recovered Daily from the Top Hat and Choke Line oil recovery systems - ODS format Updated through 12:00 AM on July 16, 2010....

212

Two photo permits are available: Daily Photographer Permit and Annual Photographer Permit. Daily Photographer Permit is $75 and includes gate admission for up to 15 adults and photographer. To reserve  

E-Print Network (OSTI)

Two photo permits are available: Daily Photographer Permit and Annual Photographer Permit. Daily of the photo session will be $75 plus a $25 processing fee. Your Daily Photo Badge can be picked up the business day before. Any permits purchased on the day of the photo session will be $225 and subject

Netoff, Theoden

213

The potential of different artificial neural network (ANN) techniques in daily global solar radiation modeling based on meteorological data  

SciTech Connect

The main objective of present study is to predict daily global solar radiation (GSR) on a horizontal surface, based on meteorological variables, using different artificial neural network (ANN) techniques. Daily mean air temperature, relative humidity, sunshine hours, evaporation, and wind speed values between 2002 and 2006 for Dezful city in Iran (32 16'N, 48 25'E), are used in this study. In order to consider the effect of each meteorological variable on daily GSR prediction, six following combinations of input variables are considered: (I)Day of the year, daily mean air temperature and relative humidity as inputs and daily GSR as output. (II)Day of the year, daily mean air temperature and sunshine hours as inputs and daily GSR as output. (III)Day of the year, daily mean air temperature, relative humidity and sunshine hours as inputs and daily GSR as output. (IV)Day of the year, daily mean air temperature, relative humidity, sunshine hours and evaporation as inputs and daily GSR as output. (V)Day of the year, daily mean air temperature, relative humidity, sunshine hours and wind speed as inputs and daily GSR as output. (VI)Day of the year, daily mean air temperature, relative humidity, sunshine hours, evaporation and wind speed as inputs and daily GSR as output. Multi-layer perceptron (MLP) and radial basis function (RBF) neural networks are applied for daily GSR modeling based on six proposed combinations. The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data. The comparison of obtained results from ANNs and different conventional GSR prediction (CGSRP) models shows very good improvements (i.e. the predicted values of best ANN model (MLP-V) has a mean absolute percentage error (MAPE) about 5.21% versus 10.02% for best CGSRP model (CGSRP 5)). (author)

Behrang, M.A.; Assareh, E. [Department of Mechanical Engineering, Young Researchers Club, Islamic Azad University, Dezful Branch (Iran); Ghanbarzadeh, A.; Noghrehabadi, A.R. [Department of Mechanical Engineering, Engineering Faculty, Shahid Chamran University, Ahvaz (Iran)

2010-08-15T23:59:59.000Z

214

Price hub","Trade date","Delivery start date","Delivery  

U.S. Energy Information Administration (EIA) Indexed Site

MWh","Low price MWh","Wtd avg price MWh","Change","Daily volume MWh","Number of trades","Number of counterparties" "ERCOT North 345KV Peak","applicationvnd.ms-excel","applicat...

215

Development of a Model Specification for Performance Monitoring Systems for Commercial Buildings  

E-Print Network (OSTI)

OA Damper Fraction 7. Whole Bldg Electric EUI; Whole bldgHVAC electric only EUI; Whole BldgNatural Gas EUI , Whole Bldg Water EUI vs. Avg. Daily OA

2008-01-01T23:59:59.000Z

216

Detecting Eating Using a Wrist Mounted Device During Normal Daily Activities  

E-Print Network (OSTI)

Detecting Eating Using a Wrist Mounted Device During Normal Daily Activities Yujie Dong1, Adam method for automated monitoring of eating. Our method uses a single sensor that is worn on the wrist, similar in form to a watch. Wrist orientation was captured at a rate of 60 Hz for an entire day while four

Hoover, Adam

217

The Daily Princetonian -International fusion project will use Princeton physics lab Summer Program  

E-Print Network (OSTI)

to determine the viability of exploiting cold fusion as an energy source around the world. Much of the researchThe Daily Princetonian - International fusion project will use Princeton physics lab Summer Program | Previous | Next | Calendar International fusion project will use Princeton physics lab By ABBY WILLIAMS

218

Home Science One fish, two fish, dumb fish, dead fish DAILY SECTIONS  

E-Print Network (OSTI)

Home Science One fish, two fish, dumb fish, dead fish Home DAILY SECTIONS News Sports Opinion Arts America! Study Spanish & Volunteer ONE FISH, TWO FISH, DUMB FISH, DEAD FISH | Print | E- mail Written scientists say fish are capable of deducing how they stack up against the competition by simply watching

Fernald, Russell

219

A Model for Predicting Daily Peak Visitation and Implications for Recreation Management and Water Quality: Evidence  

E-Print Network (OSTI)

A Model for Predicting Daily Peak Visitation and Implications for Recreation Management and Water carrying capacity. Keywords Visitation model Á Recreation management Á Water quality Á River visitation Á Clark, Fort Collins, Colorado 80523, USA 123 Environmental Management DOI 10.1007/s00267-008-9079-5 #12

220

Using daily satellite observations to estimate emissions of short-lived  

E-Print Network (OSTI)

Chapter 4 Using daily satellite observations to estimate emissions of short-lived air pollutants on a mesoscopic scale Abstract Emission inventories of air pollutants are crucial information for pol- icy makers and form important input data for air quality models. Using satellite observations for emission estimates

Haak, Hein

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Biomass burning emission inventory with daily resolution: Application to aircraft observations of Asian outflow  

E-Print Network (OSTI)

Biomass burning emission inventory with daily resolution: Application to aircraft observations for biomass burning using AVHRR satellite observations of fire activity corrected for data gaps and scan angle biomass burning in SE Asia was a major contributor to the outflow of Asian pollution observed in TRACE

Palmer, Paul

222

Water Research 37 (2003) 37563766 Seasonal and daily variations in concentrations of methyl-  

E-Print Network (OSTI)

by volume to gasoline from November to February, and blending 11% MTBE by volume during the rest of the year; accepted 24 March 2003 Abstract Methyl-tertiary-butyl ether (MTBE), an additive used to oxygenate gasoline of gasoline-powered watercraft. This paper documents and explains both seasonal and daily variations in MTBE

Toran, Laura

223

Northwestern Researchers Develop Bistable Nanoswitch Science Daily --Carbon nanotubes (CNT) have been under intense study by  

E-Print Network (OSTI)

Northwestern Researchers Develop Bistable Nanoswitch Science Daily -- Carbon nanotubes (CNT) have been under intense study by scientists all over the world for more than a decade and are being thought with high-aspect ratio, carbon nanotubes have emerged as a promising material because of their many

Espinosa, Horacio D.

224

Daily foraging patterns in free-living birds: exploring the predationstarvation trade-off  

Science Journals Connector (OSTI)

...day, possibly in response to a low but non-trivial...predictable, high-energy food, we failed...feeders with greater frequency on colder days is...between gaining energy and avoiding predation...Daily patterns of energy storage in food-caching...

2013-01-01T23:59:59.000Z

225

Modeling and Generating Daily Changes in Market Variables Using A Multivariate Mixture of Normal Distributions  

E-Print Network (OSTI)

Modeling and Generating Daily Changes in Market Variables Using A Multivariate Mixture of Normal Distributions Jin Wang Department of Mathematics and Computer Science Valdosta State University Valdosta, GA 31698-0040 January 28, 2000 Abstract The mixture of normal distributions provides a useful extension

Wang, Jin

226

Daily snow depth measurements from 195 stations in the United States  

SciTech Connect

This document describes a database containing daily measurements of snow depth at 195 National Weather Service (NWS) first-order climatological stations in the United States. The data have been assembled and made available by the National Climatic Data Center (NCDC) in Asheville, North Carolina. The 195 stations encompass 388 unique sampling locations in 48 of the 50 states; no observations from Delaware or Hawaii are included in the database. Station selection criteria emphasized the quality and length of station records while seeking to provide a network with good geographic coverage. Snow depth at the 388 locations was measured once per day on ground open to the sky. The daily snow depth is the total depth of the snow on the ground at measurement time. The time period covered by the database is 1893--1992; however, not all station records encompass the complete period. While a station record ideally should contain daily data for at least the seven winter months (January through April and October through December), not all stations have complete records. Each logical record in the snow depth database contains one station`s daily data values for a period of one month, including data source, measurement, and quality flags.

Allison, L.J. [ed.] [Oak Ridge National Lab., TN (United States). Carbon Dioxide Information Analysis Center; Easterling, D.R.; Jamason, P.; Bowman, D.P.; Hughes, P.Y.; Mason, E.H. [National Oceanic and Atmospheric Administration, Asheville, NC (United States). National Climatic Data Center

1997-02-01T23:59:59.000Z

227

Image Source: http://activefiremaps.fs.fed.us Daily Wildfire Update  

E-Print Network (OSTI)

Page 1 Image Source: http://activefiremaps.fs.fed.us Daily Wildfire Update June 14, 2011 Current Large Fires in Colorado TRACK FIRE (Updated 12:00 p.m., June 14, 2011) Fire Jurisdiction: CSFS of approximately 500 people. Closures: In Colorado, Interstate 25 is currently closed south of Exit 11. Injuries

228

Geophysical Fluid Dynamics Laboratory Daily to decadal variability in sources of  

E-Print Network (OSTI)

over the western U.S.: Stratospheric intrusions, Asian pollution, and wildfires Meiyun Lin WESTAR.g. stratospheric [Langford et al., 2009]; wildfires [Pfister et al. 2008] 2. Rising Asian emissions [e.g., Jacob et.66) (Range ~100km) Daily max 8-hr surface O3 at Boulder (~2 km a.s.l.), Colorado Insights from satellite

Jacob, Daniel J.

229

Supervised Classification of Activities of Daily Living in Health Smart Homes using SVM  

E-Print Network (OSTI)

Supervised Classification of Activities of Daily Living in Health Smart Homes using SVM Anthony studies of our laboratory focus on the monitoring of elderly people at home. This aims at detect, as early Home is used to achieve this goal. This flat includes different sensors. The data from the various

Paris-Sud XI, Université de

230

Resting and daily energy expenditures of free-living field voles are positively correlated but reflect  

E-Print Network (OSTI)

, University of Oslo, P.O. Box 1050 Blindern, 0316 Oslo, Norway; Aberdeen Centre for Energy RegulationResting and daily energy expenditures of free-living field voles are positively correlated and Obesity, Division of Energy Balance and Obesity, Rowett Research Institute, Bucksburn, Aberdeen AB24 9SB

Lambin, Xavier

231

Time of birth and daily activity mediated by feeding rhythms in the pregnant rat  

E-Print Network (OSTI)

Time of birth and daily activity mediated by feeding rhythms in the pregnant rat M. J. BOSC, Agnès studied in rats submitted to different feeding rhythms. Animals, put under 14 h of light and 10 h to one of five groups. Group C was fed ad libitum, and groups 2PF, 9PF, 14PF and 21 PF had food available

Boyer, Edmond

232

Effect of Alfaprostol, Lasalocid and Once Daily Suckling on postpartum interval in Brahman and Brahman crossbred cattle  

E-Print Network (OSTI)

by age, breed and date of calving to one of 8 treatments (Table 1): 1) Control; 2) Lasalocid (Hoffmann-LaRoche, Inc. , Nutley, N. J. ); 3) Once daily suckling; 4) Alfaprostol (Hoffmann-LaRoche, Inc. , Nutley, N. J. ); 5) Lasalocid and once daily... by age, breed and date of calving to one of 8 treatments (Table 1): 1) Control; 2) Lasalocid (Hoffmann-LaRoche, Inc. , Nutley, N. J. ); 3) Once daily suckling; 4) Alfaprostol (Hoffmann-LaRoche, Inc. , Nutley, N. J. ); 5) Lasalocid and once daily...

Del Vecchio, Ronald Paul

2012-06-07T23:59:59.000Z

233

A cyclic time-dependent Markov process to model daily patterns in wind turbine power production  

E-Print Network (OSTI)

Wind energy is becoming a top contributor to the renewable energy mix, which raises potential reliability issues for the grid due to the fluctuating nature of its source. To achieve adequate reserve commitment and to promote market participation, it is necessary to provide models that can capture daily patterns in wind power production. This paper presents a cyclic inhomogeneous Markov process, which is based on a three-dimensional state-space (wind power, speed and direction). Each time-dependent transition probability is expressed as a Bernstein polynomial. The model parameters are estimated by solving a constrained optimization problem: The objective function combines two maximum likelihood estimators, one to ensure that the Markov process long-term behavior reproduces the data accurately and another to capture daily fluctuations. A convex formulation for the overall optimization problem is presented and its applicability demonstrated through the analysis of a case-study. The proposed model is capable of r...

Scholz, Teresa; Estanqueiro, Ana

2013-01-01T23:59:59.000Z

234

Operating experience with a daily-dispatched LM-5000 STIG cogeneration plant  

SciTech Connect

The Yuba City Cogeneration Plant is a unique facility as it is a daily-dispatched LM-5000 steam injected gas turbine (STIG) that operates only during the peak summer months. This paper discusses the unique design, operation and maintenance requirements of the LM-5000 STIG. Engine operating history and maintenance problems are discussed. Reliability and availability data for the first three summer peak seasons are presented and compared with other cogeneration plant performance data. Calculations are based on North American Reliability Council/Generating Availability Data System (NERC/GADS) as a basis for operating statistic comparisons (1990). The LM-5000 STIG has demonstrated operating reliability and availability under daily cycling operation that is comparable to other base loaded aero-derivative cogeneration plants.

Peltier, R.V. [Stewart and Stevenson Services, Inc., Houston, TX (United States). Gas Turbine Productions Division; Swanekamp, R.C. [Power Magazine, New York, NY (United States)

1994-12-31T23:59:59.000Z

235

Daily Stress Recognition from Mobile Phone Data, Weather Conditions and Individual Traits  

E-Print Network (OSTI)

Research has proven that stress reduces quality of life and causes many diseases. For this reason, several researchers devised stress detection systems based on physiological parameters. However, these systems require that obtrusive sensors are continuously carried by the user. In our paper, we propose an alternative approach providing evidence that daily stress can be reliably recognized based on behavioral metrics, derived from the user's mobile phone activity and from additional indicators, such as the weather conditions (data pertaining to transitory properties of the environment) and the personality traits (data concerning permanent dispositions of individuals). Our multifactorial statistical model, which is person-independent, obtains the accuracy score of 72.28% for a 2-class daily stress recognition problem. The model is efficient to implement for most of multimedia applications due to highly reduced low-dimensional feature space (32d). Moreover, we identify and discuss the indicators which have stron...

Bogomolov, Andrey; Ferron, Michela; Pianesi, Fabio; Alex,; Pentland,

2014-01-01T23:59:59.000Z

236

Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2.  

SciTech Connect

More information: http://daymet.ornl.gov Presenter: Ranjeet Devarakonda Environmental Sciences Division Oak Ridge National Laboratory (ORNL) Daymet: Daily Surface Weather Data and Climatological Summaries provides gridded estimates of daily weather parameters for North America, including daily continuous surfaces of minimum and maximum temperature, precipitation occurrence and amount, humidity, shortwave radiation, snow water equivalent, and day length. The current data product (Version 2) covers the period January 1, 1980 to December 31, 2013 [1]. The prior product (Version 1) only covered from 1980-2008. Data are available on a daily time step at a 1-km x 1-km spatial resolution in Lambert Conformal Conic projection with a spatial extent that covers the conterminous United States, Mexico, and Southern Canada as meteorological station density allows. Daymet data can be downloaded from 1) the ORNL Distributed Active Archive Center (DAAC) search and order tools (http://daac.ornl.gov/cgi-bin/cart/add2cart.pl?add=1219) or directly from the DAAC FTP site (http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1219) and 2) the Single Pixel Tool [2] and THREDDS (Thematic Real-time Environmental Data Services) Data Server [3]. The Single Pixel Data Extraction Tool allows users to enter a single geographic point by latitude and longitude in decimal degrees. A routine is executed that translates the (lon, lat) coordinates into projected Daymet (x,y) coordinates. These coordinates are used to access the Daymet database of daily-interpolated surface weather variables. Daily data from the nearest 1 km x 1 km Daymet grid cell are extracted from the database and formatted as a table with one column for each Daymet variable and one row for each day. All daily data for selected years are returned as a single (long) table, formatted for display in the browser window. At the top of this table is a link to the same data in a simple comma-separated text format, suitable for import into a spreadsheet or other data analysis software. The Single Pixel Data Extraction Tool also provides the option to download multiple coordinates programmatically. A multiple extractor script is freely available to download at http://daymet.ornl.gov/files/daymet.zip. The ORNL DAAC s THREDDS data server (TDS) provides customized visualization and access to Daymet time series of North American mosaics. Users can subset and download Daymet data via a variety of community standards, including OPeNDAP, NetCDF Subset service, and Open Geospatial Consortium (OGC) Web Map/Coverage Service. The ORNL DAAC TDS also exposes Daymet metadata through its ncISO service to facilitate harvesting Daymet metadata records into 3rd party catalogs. References: [1] Thornton, P.E., M.M. Thornton, B.W. Mayer, N. Wilhelmi, Y. Wei, R. Devarakonda, and R.B. Cook. 2014. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2. Data set. Available on-line [http://daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA. [2] Devarakonda R., et al. 2012. Daymet: Single Pixel Data Extraction Tool. Available on-line [http://daymet.ornl.go/singlepixel.html]. [3] Wei Y., et al. 2014. Daymet: Thematic Real-time Environmental Data Services. Available on-line [http://daymet.ornl.gov/thredds_tiles.html].

Thornton, Peter E [ORNL; Thornton, Michele M [ORNL; Mayer, Benjamin W [ORNL; Wilhelmi, Nate [National Center for Atmospheric Research (NCAR); Wei, Yaxing [ORNL; Devarakonda, Ranjeet [ORNL; Cook, Robert B [ORNL

2014-01-01T23:59:59.000Z

237

LLaannggeerrhhaannss LLaabb PPrroottooccoollss Live Fish Care Daily Checklist.docx revised 8/9/13 Page 1 of 1  

E-Print Network (OSTI)

LLaannggeerrhhaannss LLaabb PPrroottooccoollss Live Fish Care Daily Checklist.docx revised 8/9/13 Page 1 of 1 Live Fish Care Daily Checklist D. Clark Labs rooms G-06 & G-08 morning visit: Turn) eggs from fridge in room 382; feed the live fish there Feed hatched Artemia (=brine shrimp) to fry

Langerhans, Brian

238

Patterns in the daily diary of the 41st president, George Bush  

E-Print Network (OSTI)

fulfillment of the requirements for the degree of MASTER OF SCIENCE Approved by: Chair of Committee, Frank M. Shipman, III Committee Members, Richard K. Furuta Lauren Cifuentes Head of Department, Valerie E. Taylor December 2005 Major... Subject: Computer Science iii ABSTRACT Patterns in the Daily Diary of the 41st President, George Bush. (December 2005) Shreyas Kumar, B. Arch., I.I.T. Roorkee Chair of Advisory Committee: Dr. Frank M. Shipman, III This thesis explores interfaces...

Kumar, Shreyas

2007-04-25T23:59:59.000Z

239

Infectious Disease Updates To minimize the risk of any infectious disease, practice these daily preventive  

E-Print Network (OSTI)

these daily preventive measures: · Cover your nose and mouth with a tissue when you cough or sneeze. Throw seconds), especially after you cough or sneeze. Alcohol-based hand cleaners are an alternative://www.sjsu.edu/studenthealth/cold_flu/index.html http://www.cdph.ca.gov/healthinfo/discond/pages/influenza(flu).aspx 2) Pertussis (Whooping Cough) http://www.sjsu.edu/studenthealth/docs/whooping_cough

Su, Xiao

240

Daily Thermal Predictions of the AGR-1 Experiment with Gas Gaps Varying with Time  

SciTech Connect

A new daily as-run thermal analysis was performed at the Idaho National Laboratory on the Advanced Gas Reactor (AGR) test experiment number one at the Advanced Test Reactor (ATR). This thermal analysis incorporates gas gaps changing with time during the irradiation experiment. The purpose of this analysis was to calculate the daily average temperatures of each compact to compare with experimental results. Post irradiation examination (PIE) measurements of the graphite holder and fuel compacts showed the gas gaps varying from the beginning of life. The control temperature gas gap and the fuel compact graphite holder gas gaps were linearly changed from the original fabrication dimensions, to the end of irradiation measurements. A steady-state thermal analysis was performed for each daily calculation. These new thermal predictions more closely match the experimental data taken during the experiment than previous analyses. Results are presented comparing normalized compact average temperatures to normalized log(R/B) Kr-85m. The R/B term is the measured release rate divided by the predicted birth rate for the isotope Kr-85m. Correlations between these two normalized values are presented.

Grant Hawkes; James Sterbentz; John Maki; Binh Pham

2012-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Prediction of clock time hourly global radiation from daily values over  

Open Energy Info (EERE)

Prediction of clock time hourly global radiation from daily values over Prediction of clock time hourly global radiation from daily values over Bangladesh Dataset Summary Description (Abstract): A need for predicting hourly global radiation exists for many locations particularly in Bangladesh for which measured values are not available and daily values have to be estimated from sunshine data. The CPRG model has been used to predict values of hourly Gh for Dhaka (23.770N, 90.380E), Chittagong (22.270N, 91.820E) and Bogra (24.850N, 89.370E) for = ±7.50, ±22.50, ±37.50, ±52.50, ±67.50, ±82.50 and ±97.50 i.e., for ±1/2, ±3/2, ±5/2, ±7/2, ±9/2, ±11/2, ±13/2 hours before and after solar noon and the computed values for different months are symmetrical about solar noon whereas for many months experimental data show a clear asymmetry. To obtain improved

242

A method to estimate the effect of deformable image registration uncertainties on daily dose mapping  

SciTech Connect

Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of the errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties.

Murphy, Martin J.; Salguero, Francisco J.; Siebers, Jeffrey V.; Staub, David; Vaman, Constantin [Department of Radiation Oncology, Virginia Commonwealth University, Richmond Virginia 23298 (United States)

2012-02-15T23:59:59.000Z

243

Daily Modulation as a Smoking Gun of Dark Matter with Significant Stopping  

E-Print Network (OSTI)

We point out that for a range of parameters, the flux of DM may be stopped significantly by its interactions with the Earth. This can significantly degrade the sensitivity of direct detection experiments to DM candidates with large interactions with terrestrial nuclei. We find that a significant region of parameter space remains unconstrained for DM $\\lesssim $ a few GeV. For DM candidates with moderate levels of stopping power, the flux of DM may be blocked from below but not above a detector thereby producing a novel daily modulation. This can be explored by low threshold detectors placed on the surface or in shallow sites in the south hemisphere.

Chris Kouvaris; Ian M. Shoemaker

2014-05-07T23:59:59.000Z

244

Daily Modulation as a Smoking Gun of Dark Matter with Significant Stopping  

E-Print Network (OSTI)

We point out that for a range of parameters, the flux of DM may be stopped significantly by its interactions with the Earth. This can significantly degrade the sensitivity of direct detection experiments to DM candidates with large interactions with terrestrial nuclei. We find that a significant region of parameter space remains unconstrained for DM $\\lesssim $ a few GeV. For DM candidates with moderate levels of stopping power, the flux of DM may be blocked from below but not above a detector thereby producing a novel daily modulation. This can be explored by low threshold detectors placed on the surface or in shallow sites in the south hemisphere.

Kouvaris, Chris

2014-01-01T23:59:59.000Z

245

Daily prediction of short-term trends of crude oil prices using neural networks exploiting multimarket dynamics  

Science Journals Connector (OSTI)

This paper documents a systematic investigation on the predictability of short-term trends of crude oil prices on a daily basis. In stark contrast with longer-term predictions of crude oil prices, short-term pred...

Heping Pan; Imad Haidar; Siddhivinayak Kulkarni

2009-06-01T23:59:59.000Z

246

Circulation patterns, daily precipitation in Portugal and implications for climate change simulated by the second Hadley Centre GCM  

Science Journals Connector (OSTI)

Based on principal component analysis (PCA) and a k...-means clustering algorithm, daily mean sea level pressure (MSLP) fields over the northeastern Atlantic and Western Europe, simulated by the Hadley Centre's ...

J. Corte-Real; B. Quian; H. Xu

1999-12-01T23:59:59.000Z

247

EIA - Daily Report 9/13/05 - Hurricane Katrina's Impact on U.S. Oil &  

U.S. Energy Information Administration (EIA) Indexed Site

Tuesday, September 13, 4:00 pm Tuesday, September 13, 4:00 pm According to the Minerals Management Service (MMS), as of 11:30 September 12, Gulf of Mexico oil production was reduced by 846,720 barrels per day as a result of Hurricane Katrina, equivalent to 56.45 percent of daily Gulf of Mexico oil production (which had been1.5 million barrels per day). The MMS also reported that 3.720 billion cubic feet per day of natural gas production was shut in, equivalent to 37.20 percent of daily Gulf of Mexico natural gas production (which had been 10 billion cubic feet per day). EIA released its monthly Short-Term Energy Outlook on Wednesday, September 7. Because considerable uncertainty remains regarding the extent of Katrina's damage, EIA established three basic recovery scenarios to represent a range of plausible outcomes for oil and natural gas supply over the next several months and through 2006: (1) Fast Recovery, which assumes a very favorable set of circumstances for getting supplies back to normal; (2) Slow Recovery, which assumes that significant outages in oil and natural gas production and delivery from the Gulf area continue at least into November; and (3) Medium Recovery, which assumes a path in between Slow and Fast Recovery.

248

Daily movements of female white-tailed deer relative to parturition and breeding.  

SciTech Connect

Abstract: To assess how white-tailed deer (Odocoileus virginianus) herd demographics influence reproductive behaviors, we examined 24-h diel movements of female whitetailed deer relative to parturition and breeding in a low-density population with a near even sex ratio at the Savannah River Site (SRS), South Carolina. We conducted a series of intensive, 24-h radio-tracking periods of 13 females during spring and fall 2002. We compared daily range (ha), rate of travel (m/h), and distance between extreme daily locations (m), among the periods of pre-parturition and post-parturition and pre-, peak-, and post-rut. From pre-parturition to post-parturition, we observed decreases in diel range size (?¢????38.2%), distance between extreme diel locations (?¢????17.0%), and diel rate of travel (?¢????18.2%). Diel range size, distance between extreme diel locations, and diel rate of travel during the pre-rut and rut exceeded those observed during post-rut. We further identified substantial increases in mobility during 12 24-h diel periods for eight females during our fall monitoring. Our data suggest that female white-tailed deer reduce mobility post-fawning following exaggerated movements during pre-parturition. Furthermore, despite a near equal sex ratio, estrous does may be required to actively seek potential mates due to low population density.

Gino J. D'Angelo; Christopher E. Comer; John C. Kilgo; Cory D. Drennan; David A. Osborn; Karl V. Miller

2005-10-01T23:59:59.000Z

249

Daily dispersion model calculations of the Kuwait oil fire smoke plume  

SciTech Connect

The Atmospheric Release Advisory Capability (ARAC) provided daily forecasts of the position and spatial character of the Kuwait oil fire smoke plume to the NSF-coordinated research aircraft missions in the Persian Gulf. ARAC also provided daily plume dispersion products to various nations in the Persian Gulf region under the auspices of the World Meteorological Organization for a period of nearly 5 months. Forecasted three dimensional winds were provided to ARAC from the US Air Force Global Weather Central`s Relocatable Wind Model (RWM). The RWM winds were spaced approximately 90 km in the horizontal and were located at the surface, 1000 ft., 2000 ft, 5000 ft and every 5000 ft up to 30,000 ft elevation. The forecast periods were 0, 6, 24, and 36 hours from both 0000 and 1200 UTC. A wind field model (MATHEW) corrected for terrain influences on the wind. The smoke plume was dispersed using a three dimensional particle-in-cell code (ADPIC) with buoyant plume rise capability. Multiple source locations were used to represent the burning oil fields. Improved estimates of the source term and emission factors for the smoke were incorporated into the ADPIC calculations as the field measurement data were made available.

Ellis, J.S.; Foster, C.S.; Foster, K.T.; Sullivan, T.J. [Lawrence Livermore National Lab., CA (United States); Baskett, R.L.; Nasstrom, J.S.; Schalk, W.W. III [EG and G Energy Measurements, Inc., Pleasanton, CA (United States); Greenly, G.D. [IT Corp., Irvine, CA (United States)

1992-03-26T23:59:59.000Z

250

Daily dispersion model calculations of the Kuwait oil fire smoke plume  

SciTech Connect

The Atmospheric Release Advisory Capability (ARAC) provided daily forecasts of the position and spatial character of the Kuwait oil fire smoke plume to the NSF-coordinated research aircraft missions in the Persian Gulf. ARAC also provided daily plume dispersion products to various nations in the Persian Gulf region under the auspices of the World Meteorological Organization for a period of nearly 5 months. Forecasted three dimensional winds were provided to ARAC from the US Air Force Global Weather Central's Relocatable Wind Model (RWM). The RWM winds were spaced approximately 90 km in the horizontal and were located at the surface, 1000 ft., 2000 ft, 5000 ft and every 5000 ft up to 30,000 ft elevation. The forecast periods were 0, 6, 24, and 36 hours from both 0000 and 1200 UTC. A wind field model (MATHEW) corrected for terrain influences on the wind. The smoke plume was dispersed using a three dimensional particle-in-cell code (ADPIC) with buoyant plume rise capability. Multiple source locations were used to represent the burning oil fields. Improved estimates of the source term and emission factors for the smoke were incorporated into the ADPIC calculations as the field measurement data were made available.

Ellis, J.S.; Foster, C.S.; Foster, K.T.; Sullivan, T.J. (Lawrence Livermore National Lab., CA (United States)); Baskett, R.L.; Nasstrom, J.S.; Schalk, W.W. III (EG and G Energy Measurements, Inc., Pleasanton, CA (United States)); Greenly, G.D. (IT Corp., Irvine, CA (United States))

1992-03-26T23:59:59.000Z

251

EIA - Daily Report 9/15/05 - Hurricane Katrina's Impact on U.S. Oil &  

U.S. Energy Information Administration (EIA) Indexed Site

Thursday, September 15, 3:00 pm Thursday, September 15, 3:00 pm According to the Minerals Management Service (MMS), as of 11:30 September 15, Gulf of Mexico oil production was reduced by 842,091 barrels per day as a result of Hurricane Katrina, equivalent to 56.14 percent of daily Gulf of Mexico oil production (which had been 1.5 million barrels per day). The MMS also reported that 3.411 billion cubic feet per day of natural gas production was shut in, equivalent to 34.11 percent of daily Gulf of Mexico natural gas production (which had been 10 billion cubic feet per day). EIA released its monthly Short-Term Energy Outlook on Wednesday, September 7, taking into consideration three Hurricane Katrina recovery scenarios. Petroleum As of the close of trading on Thursday, September 15, crude oil and petroleum product prices were lower, compared to the closing prices from Wednesday, September 14. The gasoline near-month futures price was down by 3.9 cents per gallon from Wednesday, settling at 189.9 cents per gallon, while the heating oil near-month futures price was down 1.3 cents per gallon, settling at 191.2 cents per gallon. The NYMEX West Texas Intermediate (WTI) crude oil futures price was down $0.34 per barrel from Wednesday, settling at $64.75.

252

EIA - Daily Report 9/12/05 - Hurricane Katrina's Impact on U.S. Oil &  

U.S. Energy Information Administration (EIA) Indexed Site

2, 5:00 pm 2, 5:00 pm According to the Minerals Management Service (MMS), as of 11:30 September 12, Gulf of Mexico oil production was reduced by 860,636 barrels per day as a result of Hurricane Katrina, equivalent to 57.38 percent of daily Gulf of Mexico oil production (which is 1.5 million barrels per day). The MMS also reported that 3.784 billion cubic feet per day of natural gas production was shut in, equivalent to 37.84 percent of daily Gulf of Mexico natural gas production (which is 10 billion cubic feet per day). EIA released its monthly Short-Term Energy Outlook on Wednesday, September 7. Because considerable uncertainty remains regarding the extent of Katrina's damage, EIA established three basic recovery scenarios to represent a range of plausible outcomes for oil and natural gas supply over the next several months and through 2006: (1) Fast Recovery, which assumes a very favorable set of circumstances for getting supplies back to normal; (2) Slow Recovery, which assumes that significant outages in oil and natural gas production and delivery from the Gulf area continue at least into November; and (3) Medium Recovery, which assumes a path in between Slow and Fast Recovery.

253

Spatial and temporal variability of the frequency of extreme daily rainfall regime in the La Plata Basin during the 20th century  

Science Journals Connector (OSTI)

We analyzed trends, interdecadal variability, and the quantification of the changes in the frequency of daily rainfall for two thresholds: 0.1mm and percentile 75th, using high quality daily series from 52 st...

Olga C. Penalba; Federico A. Robledo

2010-02-01T23:59:59.000Z

254

EIA - Daily Report 9/16/05 - Hurricane Katrina's Impact on U.S. Oil &  

U.S. Energy Information Administration (EIA) Indexed Site

16, 4:00 pm 16, 4:00 pm Hurricane Katrina in Perspective (see figures below) While the peak crude oil production loss from Hurricane Katrina was similar to Hurricane Ivan last year and even less than Hurricane Dennis earlier this year, the pace of restoration is expected to be much more similar to Hurricane Ivan than any of the other recent hurricanes. For example, while the peak daily loss in crude oil production during Hurricane Dennis was slightly more than suffered following Hurricane Katrina, within a week of the peak loss, crude oil production following Hurricane Dennis was back to normal while it will likely be months before crude oil production is back to normal following Hurricane Katrina. Graph of Gulf of Mexico Shut-In Oil & Natural Gas Production due to hurricanes in 2004 & 2005

255

Daily Temperature and Precipitation Data from 223 Former-USSR Stations  

NLE Websites -- All DOE Office Websites (Extended Search)

Climate Variables » Temperature » 223 Former-USSR Stations Climate Variables » Temperature » 223 Former-USSR Stations Daily Temperature and Precipitation Data for 223 Former-USSR Stations graphics Graphics data Data Investigators V. N. Razuvaev, E. B. Apasova, R. A. Martuganov All-Russian Research Institute of Hydrometeorological Information-World Data Centre Obninsk, Russia DOI 10.3334/CDIAC/cli.ndp040 Period of Record 1881 - 2001 (depending on station) Background Over the past several decades, many climate datasets have been exchanged directly between the principal climate data centers of the United States (NOAA's National Climatic Data Center (NCDC)) and the former-USSR/Russia (All-Russian Research Institute for Hydrometeorological Information (RIHMI)). This data exchange has its roots in a bilateral initiative known

256

Testing for price response asymmetries in the Spanish fuel market. New evidence from daily data  

Science Journals Connector (OSTI)

In this work we use daily data to examine pattern asymmetries in the speed of transmission of international wholesale oil prices to Spanish retail fuel prices. Results are robust to two alternative specifications of an asymmetric error correction model, for which the presence of autoregressive conditional heteroskedasticity for disturbances is modeled by a GARCH(1,1) process. Evidence indicates that the short-term transmission of wholesale prices to retail prices is quite symmetric for both gasoline and diesel fuel. Nevertheless, in contrast to some of the results provided for an earlier period, we did not find asymmetries in the speed of retail price responses toward long-run equilibrium. Our evidence also suggests that the use of weekly (or lower frequency) data is one of the possible explanations for some of the seemingly contradictory results concerning this issue.

Jacint Balaguer; Jordi Ripolls

2012-01-01T23:59:59.000Z

257

Incorporating daily flood control objectives into a monthly stochastic dynamic programming model for a hydroelectric complex  

SciTech Connect

A monthly stochastic dynamic programing model was recently developed and implemented at British Columbia (B.C.) Hydro to provide decision support for short-term energy exports and, if necessary, for flood control on the Peace River in northern British Columbia. The model established the marginal cost of supplying energy from the B.C. Hydro system, as well as a monthly operating policy for the G.M. Shrum and Peace Canyon hydroelectric plants and the Williston Lake storage reservoir. A simulation model capable of following the operating policy then determines the probability of refilling Williston Lake and possible spill rates and volumes. Reservoir inflows are input to both models in daily and monthly formats. The results indicate that flood control can be accommodated without sacrificing significant export revenue.

Druce, D.J. (British Columbia Hydro and Power Authority, Vancouver, British Columbia (Canada))

1990-01-01T23:59:59.000Z

258

EIA - Daily Report 9/19/05 - Hurricane Katrina's Impact on U.S. Oil &  

U.S. Energy Information Administration (EIA) Indexed Site

Monday, September 19, 5:00 pm Monday, September 19, 5:00 pm Hurricane Katrina in Perspective (see figures below). While the peak crude oil production loss from Hurricane Katrina was similar to 2004's Hurricane Ivan and even less than Hurricane Dennis earlier this year, the pace of restoration is expected to be much more similar to Hurricane Ivan than any of the other recent hurricanes. For example, while the peak daily loss in crude oil production during Hurricane Dennis was slightly more than suffered following Hurricane Katrina, within a week of the peak loss, crude oil production following Hurricane Dennis was back to normal while it will likely be months before crude oil production is back to normal following Hurricane Katrina. New York Mercantile Exchange (NYMEX) prices increased initially following the hurricane. Since early September, product prices generally have declined (increasing on September 19 with news of Tropical Storm Rita approaching the Gulf of Mexico).

259

EIA - Daily Report 9/7/05 - Hurricane Katrina's Impact on U.S. Oil &  

U.S. Energy Information Administration (EIA) Indexed Site

7, 3:00 pm 7, 3:00 pm According to the Minerals Management Service (MMS), as of 11:30 September 7, Gulf of Mexico oil production was reduced by 861,000 barrels per day as a result of Hurricane Katrina, equivalent to 57.37 percent of daily Gulf of Mexico oil production (which is 1.5 million barrels per day). The MMS also reported that 4.0360 billion cubic feet per day of natural gas production was shut in, equivalent to 40.36 percent of daily Gulf of Mexico natural gas production (which is 10 billion cubic feet per day). EIA released its monthly Short-Term Energy Outlook on Wednesday, September 7. Because considerable uncertainty remains regarding the specific extent of Katrina's damage, it is difficult to provide a single forecast for the upcoming winter and subsequent months as is typical in Outlook. More detailed damage assessments should be forthcoming over the next several weeks, which should clarify our forecast. For the September Outlook, EIA established three basic scenarios to represent a range of plausible outcomes for oil and natural gas supply over the next several months and through 2006: (1) Fast Recovery, which assumes a very favorable set of circumstances for getting supplies back to normal; (2) Slow Recovery, which assumes that significant outages in oil and natural gas production and delivery from the Gulf area continue at least into November; and (3) Medium Recovery, which assumes a path in between Slow and Fast Recovery. In all cases, return to normal operations, in terms of oil and natural gas production and distribution, is achieved or nearly achieved by December. By the end of September all but about 0.9 million barrels per day of crude oil refining capacity is expected to be back at full rates under the Medium Recovery case.

260

Forecasting of preprocessed daily solar radiation time series using neural networks  

SciTech Connect

In this paper, we present an application of Artificial Neural Networks (ANNs) in the renewable energy domain. We particularly look at the Multi-Layer Perceptron (MLP) network which has been the most used of ANNs architectures both in the renewable energy domain and in the time series forecasting. We have used a MLP and an ad hoc time series pre-processing to develop a methodology for the daily prediction of global solar radiation on a horizontal surface. First results are promising with nRMSE {proportional_to} 21% and RMSE {proportional_to} 3.59 MJ/m{sup 2}. The optimized MLP presents predictions similar to or even better than conventional and reference methods such as ARIMA techniques, Bayesian inference, Markov chains and k-Nearest-Neighbors. Moreover we found that the data pre-processing approach proposed can reduce significantly forecasting errors of about 6% compared to conventional prediction methods such as Markov chains or Bayesian inference. The simulator proposed has been obtained using 19 years of available data from the meteorological station of Ajaccio (Corsica Island, France, 41 55'N, 8 44'E, 4 m above mean sea level). The predicted whole methodology has been validated on a 1.175 kWc mono-Si PV power grid. Six prediction methods (ANN, clear sky model, combination..) allow to predict the best daily DC PV power production at horizon d + 1. The cumulated DC PV energy on a 6-months period shows a great agreement between simulated and measured data (R{sup 2} > 0.99 and nRMSE < 2%). (author)

Paoli, Christophe; Muselli, Marc; Nivet, Marie-Laure [University of Corsica, CNRS UMR SPE, Corte (France); Voyant, Cyril [University of Corsica, CNRS UMR SPE, Corte (France); Hospital of Castelluccio, Radiotherapy Unit, Ajaccio (France)

2010-12-15T23:59:59.000Z

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Assessing Energy Impact of Plug-In Hybrid Electric Vehicles: Significance of Daily Distance Variation over Time and Among Drivers  

SciTech Connect

Accurate assessment of the impact of plug-in hybrid electric vehicles (PHEVs) on petroleum and electricity consumption is a necessary step toward effective policies. Variations in daily vehicle miles traveled (VMT) over time and among drivers affect PHEV energy impact, but the significance is not well understood. This paper uses a graphical illustration, a mathematical derivation, and an empirical study to examine the cause and significance of such an effect. The first two methods reveal that ignoring daily variation in VMT always causes underestimation of petroleum consumption and overestimation of electricity consumption by PHEVs; both biases increase as the assumed PHEV charge-depleting (CD) range moves closer to the average daily VMT. The empirical analysis based on national travel survey data shows that the assumption of uniform daily VMT over time and among drivers causes nearly 68% underestimation of expected petroleum use and nearly 48% overestimation of expected electricity use by PHEVs with a 40-mi CD range (PHEV40s). Also for PHEV40s, consideration of daily variation in VMT over time but not among drivers similar to the way the utility factor curve is derived in SAE Standard SAE J2841 causes underestimation of expected petroleum use by more than 24% and overestimation of expected electricity use by about 17%. Underestimation of petroleum use and overestimation of electricity use increase with larger-battery PHEVs.

Lin, Zhenhong [ORNL; Greene, David L [ORNL

2012-01-01T23:59:59.000Z

262

Reducing Open Cell Landfill Methane Emissions with a Bioactive Alternative Daily  

SciTech Connect

Methane and carbon dioxide are formed in landfills as wastes degrade. Molecule-for-molecule, methane is about 20 times more potent than carbon dioxide at trapping heat in the earth's atmosphere, and thus, it is the methane emissions from landfills that are scrutinized. For example, if emissions composed of 60% methane and 40% carbon dioxide were changed to a mix that was 40% methane and 60% carbon dioxide, a 30% reduction in the landfill's global warming potential would result. A 10% methane, 90% carbon dioxide ratio will result in a 75% reduction in global warming potential compared to the baseline. Gas collection from a closed landfill can reduce emissions, and it is sometimes combined with a biocover, an engineered system where methane oxidizing bacteria living in a medium such as compost, convert landfill methane to carbon dioxide and water. Although methane oxidizing bacteria merely convert one greenhouse gas (methane) to another (carbon dioxide), this conversion can offer significant reductions in the overall greenhouse gas contribution, or global warming potential, associated with the landfill. What has not been addressed to date is the fact that methane can also escape from a landfill when the active cell is being filled with waste. Federal regulations require that newly deposited solid waste to be covered daily with a 6 in layer of soil or an alternative daily cover (ADC), such as a canvas tarp. The aim of this study was to assess the feasibility of immobilizing methane oxidizing bacteria into a tarp-like matrix that could be used for alternative daily cover at open landfill cells to prevent methane emissions. A unique method of isolating methanotrophs from landfill cover soil was used to create a liquid culture of mixed methanotrophs. A variety of prospective immobilization techniques were used to affix the bacteria in a tarp-like matrix. Both gel encapsulation of methanotrophs and gels with liquid cores containing methanotrophs were readily made but prone to rapid desiccation. Bacterial adsorption onto foam padding, natural sponge, and geotextile was successful. The most important factor for success appeared to be water holding capacity. Prototype biotarps made with geotextiles plus adsorbed methane oxidizing bacteria were tested for their responses to temperature, intermittent starvation, and washing (to simulate rainfall). The prototypes were mesophilic, and methane oxidation activity remained strong after one cycle of starvation but then declined with repeated cycles. Many of the cells detached with vigorous washing, but at least 30% appeared resistant to sloughing. While laboratory landfill simulations showed that four-layer composite biotarps made with two different types of geotextile could remove up to 50% of influent methane introduced at a flux rate of 22 g m{sup -2} d{sup -1}, field experiments did not yield high activity levels. Tests revealed that there were high hour-to-hour flux variations in the field, which, together with frequent rainfall events, confounded the field testing. Overall, the findings suggest that a methanotroph embedded biotarp appears to be a feasible strategy to mitigate methane emission from landfill cells, although the performance of field-tested biotarps was not robust here. Tarps will likely be best suited for spring and summer use, although the methane oxidizer population may be able to shift and adapt to lower temperatures. The starvation cycling of the tarp may require the capacity for intermittent reinoculation of the cells, although it is also possible that a subpopulation will adapt to the cycling and become dominant. Rainfall is not expected to be a major factor, because a baseline biofilm will be present to repopulate the tarp. If strong performance can be achieved and documented, the biotarp concept could be extended to include interception of other compounds beyond methane, such as volatile aromatic hydrocarbons and chlorinated solvents.

Helene Hilger; James Oliver; Jean Bogner; David Jones

2009-03-31T23:59:59.000Z

263

Daily load profile and monthly power peaks evaluation of the urban substation of the capital of Jordan Amman  

Science Journals Connector (OSTI)

The hourly recorded power of an urban substation of the National Electric Power Company (NEPCO) in the capital of Jordan Amman is used to calculate the diversity and conversion factors of the substation. These factors are used to estimate the daily load power profile and the monthly peak power of the substation. The results show that the conversion factors are almost independent of the number of feeders in the substation, while the diversity factors vary in substations that have six feeders or less. The results show a good correlation between the estimated and actual recorded data of the daily load profile with less than 5% percentage error.

Nabeel I.A. Tawalbeh

2012-01-01T23:59:59.000Z

264

Sub-daily Statistical Downscaling of Meteorological Variables Using Neural Networks  

SciTech Connect

A new open source neural network temporal downscaling model is described and tested using CRU-NCEP reanal ysis and CCSM3 climate model output. We downscaled multiple meteorological variables in tandem from monthly to sub-daily time steps while also retaining consistent correlations between variables. We found that our feed forward, error backpropagation approach produced synthetic 6 hourly meteorology with biases no greater than 0.6% across all variables and variance that was accurate within 1% for all variables except atmospheric pressure, wind speed, and precipitation. Correlations between downscaled output and the expected (original) monthly means exceeded 0.99 for all variables, which indicates that this approach would work well for generating atmospheric forcing data consistent with mass and energy conserved GCM output. Our neural network approach performed well for variables that had correlations to other variables of about 0.3 and better and its skill was increased by downscaling multiple correlated variables together. Poor replication of precipitation intensity however required further post-processing in order to obtain the expected probability distribution. The concurrence of precipitation events with expected changes in sub ordinate variables (e.g., less incident shortwave radiation during precipitation events) were nearly as consistent in the downscaled data as in the training data with probabilities that differed by no more than 6%. Our downscaling approach requires training data at the target time step and relies on a weak assumption that climate variability in the extrapolated data is similar to variability in the training data.

Kumar, Jitendra [ORNL] [ORNL; Brooks, Bjrn-Gustaf J. [University of Illinois, Urbana-Champaign] [University of Illinois, Urbana-Champaign; Thornton, Peter E [ORNL] [ORNL; Dietze, Michael [University of Illinois, Urbana-Champaign] [University of Illinois, Urbana-Champaign

2012-01-01T23:59:59.000Z

265

The interaction of daily lighting period and light intensity on growth of some greenhouse plants  

Science Journals Connector (OSTI)

The effect of lighting period and light intensity on the growth of Begonia, Chrysanthemum, Hedera, Kalanchoe and Pelargonium was investigated. The growth of the plants usually increased more when the lighting period was extended from 12 to 18 h or 16 to 20 h than from 18 to 24 or 20 to 24 h when using a constant flux density. When using the same daily (photosynthetic active radiation) PAR the growth was best when the light was given in 20 h, instead of 16 or 24 h. Increasing the light intensity from 14 to 42 or 70 ?mol m?2 s?1 the plant growth increased and usually more when it was increased from 14 to 42 than when it was increased to 70 ?mol m?2 s?1. There was for Begonia and Kalanchoe a significant interaction between lighting period and light intensity on the dry-matter production, but not for the other plants. For Begonia there was a significant increase in number of buds and flowers when increasing the lighting period from 16 to 20 or 24 h a day, while this had no influence on number of days to flowering for either Begonia or Pelargonium. Number of days to flowering and number of buds for Begonia was significantly affected with increasing light intensity from 14 to 42 ?mol m?2 s?1, but there was no effect with a further increase.

H.R. Gislerd; I.M. Eidsten; L.M. Mortensen

1989-01-01T23:59:59.000Z

266

Statistical correlation between hourly and daily values of solar radiation on horizontal surface at sea level in the Italian climate  

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219- Statistical correlation between hourly and daily values of solar radiation on horizontal- nalières du rayonnement solaire. Abstract. 2014 The knowledge of hourly data of solar radiation is required data measured in Italian stations and propose a method to estimate hourly solar radiation

Boyer, Edmond

267

Climatic Resources for Tourism in Europe An Application of the Tourism Climatic Index on a Daily Basis  

E-Print Network (OSTI)

Climatic Resources for Tourism in Europe An Application of the Tourism Climatic Index on a Daily - Use of the "Tourism Climatic Index" by Mieczkowski (1985) as a metric for "favourable climate" for tourism - Calculation of the potential future change in index by means of climate model projections from

Fischlin, Andreas

268

Influence of daily feeding within a limited time on weight, digestive transit and cholesterol turnover in adult rats  

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turnover in adult rats T. MAGOT, F. CHEVALLIER Laboratoire de Physiologie de la Nutrition (*),), Université de Paris-Sud, Bâtiment 447 91405 Orsay Cedex, France. Summary. Rats were trained to a single daily the first hour. This value defined the average volumic capacity of the full stomach of our rats. Body weight

Paris-Sud XI, Université de

269

Locoregional Outcomes of Inflammatory Breast Cancer Patients Treated With Standard Fractionation Radiation and Daily Skin Bolus in the Taxane Era  

SciTech Connect

Purpose: To assess locoregional outcomes of inflammatory breast cancer (IBC) patients who received standard fractionation radiation with daily skin bolus and taxanes as part of combined-modality therapy (CMT). Methods and Materials: We retrospectively reviewed the charts of 107 patients diagnosed with IBC between January 1995 and March 2006 who presented to our department for adjuvant radiation therapy (RT). Results: All patients received chemotherapy (95% anthracycline and 95% taxane), modified radical mastectomy, and RT to the chest wall and regional lymphatics using standard fractionation to 50 Gy and daily skin bolus. The RT to the chest wall was delivered via electrons (55%) or photons (45%) in daily fractions of 180 cGy (73%) or 200 cGy (27%). Scar boost was performed in 11%. A majority (84%) of patients completed the prescribed treatment. Median follow-up was 47 months (range, 10-134 months). Locoregional control (LRC) at 3 years and 5 years was 90% and 87%, respectively. Distant metastases-free survival (DMFS) at 3 years and 5 years was 61% and 47%, respectively. Conclusions: Excellent locoregional control was observed in this population of IBC patients who received standard fractionation radiation with daily skin bolus and taxanes as part of combined-modality therapy. Distant metastases-free survival remains a significant therapeutic challenge.

Damast, Shari, E-mail: damasts@mskcc.or [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Ho, Alice Y. [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Montgomery, Leslie [Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Fornier, Monica N. [Department of Breast Cancer Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Ishill, Nicole; Elkin, Elena [Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Beal, Kathryn; McCormick, Beryl [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY (United States)

2010-07-15T23:59:59.000Z

270

Estimation of Rectal Dose Using Daily Megavoltage Cone-Beam Computed Tomography and Deformable Image Registration  

SciTech Connect

Purpose: The actual dose delivered to critical organs will differ from the simulated dose because of interfractional organ motion and deformation. Here, we developed a method to estimate the rectal dose in prostate intensity modulated radiation therapy with consideration to interfractional organ motion using daily megavoltage cone-beam computed tomography (MVCBCT). Methods and Materials: Under exemption status from our institutional review board, we retrospectively reviewed 231 series of MVCBCT of 8 patients with prostate cancer. On both planning CT (pCT) and MVCBCT images, the rectal contours were delineated and the CT value within the contours was replaced by the mean CT value within the pelvis, with the addition of 100 Hounsfield units. MVCBCT images were rigidly registered to pCT and then nonrigidly registered using B-Spline deformable image registration (DIR) with Velocity AI software. The concordance between the rectal contours on MVCBCT and pCT was evaluated using the Dice similarity coefficient (DSC). The dose distributions normalized for 1 fraction were also deformed and summed to estimate the actual total dose. Results: The DSC of all treatment fractions of 8 patients was improved from 0.750.04 (mean SD) to 0.90 0.02 by DIR. Six patients showed a decrease of the generalized equivalent uniform dose (gEUD) from total dose compared with treatment plans. Although the rectal volume of each treatment fraction did not show any correlation with the change in gEUD (R{sup 2}=0.180.13), the displacement of the center of gravity of rectal contours in the anterior-posterior (AP) direction showed an intermediate relationship (R{sup 2}=0.610.16). Conclusion: We developed a method for evaluation of rectal dose using DIR and MVCBCT images and showed the necessity of DIR for the evaluation of total dose. Displacement of the rectum in the AP direction showed a greater effect on the change in rectal dose compared with the rectal volume.

Akino, Yuichi, E-mail: akino@radonc.med.osaka-u.ac.jp [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka (Japan); Department of Radiology, Osaka University Hospital, Suita, Osaka (Japan); Yoshioka, Yasuo [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka (Japan); Fukuda, Shoichi [Department of Radiation Oncology, Osaka General Medical Center, Osaka (Japan); Maruoka, Shintaroh [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka (Japan); Takahashi, Yutaka [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka (Japan); Department of Radiation Oncology, University of Minnesota, Minneapolis, Minnesota (United States); Yagi, Masashi [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka (Japan); Mizuno, Hirokazu [Department of Radiology, Osaka University Hospital, Suita, Osaka (Japan); Isohashi, Fumiaki [Oncology Center, Osaka University Hospital, Suita, Osaka (Japan); Ogawa, Kazuhiko [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka (Japan)

2013-11-01T23:59:59.000Z

271

Daily digestible protein and energy requirements for growth and maintenance of sub-adult Pacific white shrimp (Litopenaeus vannamei)  

E-Print Network (OSTI)

weight-gain and were 1.03 g DP kg-1 BW d-1 for shrimp fed the 25% protein diet and 1.87 g DP kg-1 BW d-1 for shrimp fed the 35% protein diet. Mean apparent daily DE requirement for shrimp fed the 25% protein diet was 402.62 kJ DE kg-1 BW d-1 while the 35...

Siccardi, Anthony Joseph, III

2009-06-02T23:59:59.000Z

272

A Novel Markerless Technique to Evaluate Daily Lung Tumor Motion Based on Conventional Cone-Beam CT Projection Data  

SciTech Connect

Purpose: In this study, we present a novel markerless technique, based on cone beam computed tomography (CBCT) raw projection data, to evaluate lung tumor daily motion. Method and Materials: The markerless technique, which uses raw CBCT projection data and locates tumors directly on every projection, consists of three steps. First, the tumor contour on the planning CT is used to create digitally reconstructed radiographs (DRRs) at every projection angle. Two sets of DRRs are created: one showing only the tumor, and another with the complete anatomy without the tumor. Second, a rigid two-dimensional image registration is performed to register the DRR set without the tumor to the CBCT projections. After the registration, the projections are subtracted from the DRRs, resulting in a projection dataset containing primarily tumor. Finally, a second registration is performed between the subtracted projection and tumor-only DRR. The methodology was evaluated using a chest phantom containing a moving tumor, and retrospectively in 4 lung cancer patients treated by stereotactic body radiation therapy. Tumors detected on projection images were compared with those from three-dimensional (3D) and four-dimensional (4D) CBCT reconstruction results. Results: Results in both static and moving phantoms demonstrate that the accuracy is within 1 mm. The subsequent application to 22 sets of CBCT scan raw projection data of 4 lung cancer patients includes about 11,000 projections, with the detected tumor locations consistent with 3D and 4D CBCT reconstruction results. This technique reveals detailed lung tumor motion and provides additional information than conventional 4D images. Conclusion: This technique is capable of accurately characterizing lung tumor motion on a daily basis based on a conventional CBCT scan. It provides daily verification of the tumor motion to ensure that these motions are within prior estimation and covered by the treatment planning volume.

Yang Yin; Zhong Zichun; Guo Xiaohu [Department of Computer Science, University of Texas at Dallas, Richardson, TX (United States); Wang Jing; Anderson, John; Solberg, Timothy [Department of Radiation Oncology, University of Texas Southwestern Medical Center at Dallas, Dallas, TX 75390 (United States); Mao Weihua, E-mail: weihua.mao@utsouthwestern.edu [Department of Radiation Oncology, University of Texas Southwestern Medical Center at Dallas, Dallas, TX 75390 (United States)

2012-04-01T23:59:59.000Z

273

Adaptive Liver Stereotactic Body Radiation Therapy: Automated Daily Plan Reoptimization Prevents Dose Delivery Degradation Caused by Anatomy Deformations  

SciTech Connect

Purpose: To investigate how dose distributions for liver stereotactic body radiation therapy (SBRT) can be improved by using automated, daily plan reoptimization to account for anatomy deformations, compared with setup corrections only. Methods and Materials: For 12 tumors, 3 strategies for dose delivery were simulated. In the first strategy, computed tomography scans made before each treatment fraction were used only for patient repositioning before dose delivery for correction of detected tumor setup errors. In adaptive second and third strategies, in addition to the isocenter shift, intensity modulated radiation therapy beam profiles were reoptimized or both intensity profiles and beam orientations were reoptimized, respectively. All optimizations were performed with a recently published algorithm for automated, multicriteria optimization of both beam profiles and beam angles. Results: In 6 of 12 cases, violations of organs at risk (ie, heart, stomach, kidney) constraints of 1 to 6 Gy in single fractions occurred in cases of tumor repositioning only. By using the adaptive strategies, these could be avoided (<1 Gy). For 1 case, this needed adaptation by slightly underdosing the planning target volume. For 2 cases with restricted tumor dose in the planning phase to avoid organ-at-risk constraint violations, fraction doses could be increased by 1 and 2 Gy because of more favorable anatomy. Daily reoptimization of both beam profiles and beam angles (third strategy) performed slightly better than reoptimization of profiles only, but the latter required only a few minutes of computation time, whereas full reoptimization took several hours. Conclusions: This simulation study demonstrated that replanning based on daily acquired computed tomography scans can improve liver stereotactic body radiation therapy dose delivery.

Leinders, Suzanne M. [Erasmus Medical Center-Daniel den Hoed Cancer Center, Rotterdam (Netherlands); Delft University of Technology, Delft (Netherlands); Breedveld, Sebastiaan; Mndez Romero, Alejandra [Erasmus Medical Center-Daniel den Hoed Cancer Center, Rotterdam (Netherlands); Schaart, Dennis [Delft University of Technology, Delft (Netherlands); Seppenwoolde, Yvette, E-mail: y.seppenwoolde@erasmusmc.nl [Erasmus Medical Center-Daniel den Hoed Cancer Center, Rotterdam (Netherlands); Heijmen, Ben J.M. [Erasmus Medical Center-Daniel den Hoed Cancer Center, Rotterdam (Netherlands)

2013-12-01T23:59:59.000Z

274

The Impacts of Wind Power Integration on Sub-Daily Variation in River Flows Downstream of Hydroelectric Dams  

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The Impacts of Wind Power Integration on Sub-Daily Variation in River Flows Downstream of Hydroelectric Dams ... Due to their operational flexibility, hydroelectric dams are ideal candidates to compensate for the intermittency and unpredictability of wind energy production. ... In this paper, we examine the effects of increased (i.e., 5%, 15%, and 25%) wind market penetration on prices for electricity and reserves, and assess the potential for altered price dynamics to disrupt reservoir release schedules at a hydroelectric dam and cause more variable and unpredictable hourly flow patterns (measured in terms of the Richards-Baker Flashiness (RBF) index). ...

Jordan D. Kern; Dalia Patino-Echeverri; Gregory W. Characklis

2014-07-25T23:59:59.000Z

275

A comparative study of factors related to carrying out physical activities of daily living (PADL) among 75-year-old men and women in two nordic localities  

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The aim of this cross-sectional and cross-national study was to describe and compare the ability to carry out physical activities of daily living (PADL) and examine factors that might explain variation in this...

P. Laukkanen M.D.; E. Heikkinen; M. Schroll

1997-08-01T23:59:59.000Z

276

A new HBMO algorithm for multiobjective daily Volt/Var control in distribution systems considering Distributed Generators  

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In recent years, Distributed Generators (DGs) connected to the distribution network have received increasing attention. The connection of enormous \\{DGs\\} into existing distribution network changes the operation of distribution systems. Because of the small X/R ratio and radial structure of distribution systems, \\{DGs\\} affect the daily Volt/Var control. This paper presents a new algorithm for multiobjective daily Volt/Var control in distribution systems including Distributed Generators (DGs). The objectives are costs of energy generation by \\{DGs\\} and distribution companies, electrical energy losses and the voltage deviations for the next day. A new optimization algorithm based on a Chaotic Improved Honey Bee Mating Optimization (CIHBMO) is proposed to determine the active power values of DGs, reactive power values of capacitors and tap positions of transformers for the next day. Since objectives are not the same, a fuzzy system is used to calculate the best solution. The plausibility of the proposed algorithm is demonstrated and its performance is compared with other methods on a 69-bus distribution feeder. Simulation results illustrate that the proposed algorithm has better outperforms the other algorithms.

Taher Niknam

2011-01-01T23:59:59.000Z

277

4/5/2014 Micro-windmill Charger | DailyHome Decor Ideas http://www.dailyhomedecorideas.com/stunning-ideas/micro-windmill-charger/ 1/4  

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://www.dailyhomedecorideas.com/stunning-ideas/micro-windmill-charger/ 1/4 Daily Home Decor Ideas Micro-windmill Charger VersiCharge EV Charger usa Blowout Sale #12;4/5/2014 Micro-windmill Charger | DailyHome Decor Ideas http://www.dailyhomedecorideas.com/stunning-ideas/micro-windmill-charger/ 4/4 Wireless EV Charging Stations Hiding As Manhole Covers Implantable Piezoelectric Nano- ribbon

Chiao, Jung-Chih

278

Forecasting the daily outbreak of topic-level political risk from social media using hidden Markov model-based techniques  

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Abstract Nowadays, as an arena of politics, social media ignites political protests, so analyzing topics discussed negatively in the social media has increased in importance for detecting a nation's political risk. In this context, this paper designs and examines an automatic approach to forecast the daily outbreak of political risk from social media at a topic level. It evaluates the forecasting performances of topic features, investigated among the previous works that analyze social media data for politics, hidden Markov model (HMM)-based techniques, widely used for the anomaly detection with time-series data, and detection models, into which the topic features and the detection techniques are combined. When applied to South Korea's Web forum, Daum Agora, statistical comparisons with the constraints of false positive rate of political risk, and eventually the predictive governance benefits the people.

Jong Hwan Suh

2014-01-01T23:59:59.000Z

279

A new approach based on ant colony optimization for daily Volt/Var control in distribution networks considering distributed generators  

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This paper presents a new approach to daily Volt/Var control in distribution systems with regard to distributed generators (DGs). Due to the small X/R ratio and radial configuration of distribution systems, \\{DGs\\} have much impact on this problem. A cost-based compensation methodology is proposed as a proper signal to encourage owners of \\{DGs\\} in active and reactive power generation. An evolutionary method based on ant colony optimization (ACO) is used to determine the active and reactive power values of DGs, reactive power values of capacitors and tap positions of transformers for the next day. The results indicate that the proposed encouraging factor has improved the performance of distribution networks on a large scale.

Taher Niknam

2008-01-01T23:59:59.000Z

280

Interactive multiobjective daily volt/var control of distribution networks considering wind power and fuel-cell power plants  

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This paper deals with a multiobjective daily volt/var control (MDVVC) for radial distribution feeders integrated renewable energy sources (RES) by means of the tap position of the under load tap changer (ULTC) transformers shunt capacitors and active and reactive power of RES. The multiple objective functions to be minimized are the electrical energy losses the voltage deviations and the total emissions of RES and substations. Discrete behavior of equipments in the distribution systems and nonlinear power flow equations change the VVC problem into a mixed integer non-linear programming (MINLP). Hence a new optimization method based upon the shuffled frog leaping algorithm (SFLA) is presented to solve the optimization problem. The SFLA is modified for resolving the disadvantages of the original algorithm. Besides of accurately passing local optima the MSFLA takes less time to achieve the optimal response. Furthermore the tribe-MSFLA is proposed through using the concept of the tribe. Dealing with the multiobjective optimization problem an interactive fuzzy satisfying method is used while the objective functions are formulated by a fuzzy set theory. An 85-bus radial distribution system is used to test and assess the performance of the proposed algorithm.

Taher Niknam; Mohsen Zare; Jamshid Aghaei; Rasoul Azizipanah-Abarghooee

2012-01-01T23:59:59.000Z

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281

Guidance on the establishment of acceptable daily exposure limits (ADE) to support Risk-Based Manufacture of Pharmaceutical Products  

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Health-based limits for active pharmaceutical ingredients (API) referred to as acceptable daily exposures (ADEs) are necessary to the pharmaceutical industry and used to derive acceptance limits for cleaning validation purposes and evaluating cross-carryover. \\{ADEs\\} represent a dose of an API unlikely to cause adverse effects if an individual is exposed, by any route, at or below this dose every day over a lifetime. Derivations of \\{ADEs\\} need to be consistent with ICH Q9 as well as other scientific approaches for the derivation of health-based limits that help to manage risks to both product quality and operator safety during the manufacture of pharmaceutical products. Previous methods for the establishment of acceptance limits in cleaning validation programs are considered arbitrary and have largely ignored the available clinical and toxicological data available for a drug substance. Since the ADE utilizes all available pharmaceutical data and applies scientifically acceptable risk assessment methodology it is more holistic and consistent with other quantitative risk assessments purposes such derivation of occupational exposure limits. Processes for hazard identification, dose response assessment, uncertainty factor analysis and documentation are reviewed.

Edward V. Sargent; Ellen Faria; Thomas Pfister; Robert G. Sussman

2013-01-01T23:59:59.000Z

282

CAH and Shared Services Transition Plan CAH will move seven servers that provide daily operational services such as user authentication and access, central file  

E-Print Network (OSTI)

CAH and Shared Services Transition Plan CAH will move seven servers that provide daily operational the university's NET domain. Domains provide user authentication, access, and management to resources divide the transition plan, and each phase has goals and a deadline. The overall goal is to continue

Wu, Shin-Tson

283

The Daily Tar Heel URL: http://www.dailytarheel.com/index.php/article/2010/09/grant_money_to_help_scholars  

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The Daily Tar Heel URL: http://www.dailytarheel.com/index.php/article/2010/09/grant_money_to_help_scholars Current Date: Sun, 26 Sep 2010 13:05:26 -0400 Grant money to help scholars To benefit biomedical students in biology, physics and chemistry, as well as high-level math and applied sciences courses. The grant money

Sekelsky, Jeff

284

Tougher than Kevlar: Researchers create new high-performance fiber Posted In: Editors Picks | R&D Daily | Carbon Nanotubes & Graphene | Materials Science |  

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and satellites. To create the new fiber, researchers began with carbon nanotubes--cylindrical-shaped carbonTougher than Kevlar: Researchers create new high-performance fiber Posted In: Editors Picks | R&D Daily | Carbon Nanotubes & Graphene | Materials Science | Nanotechnology | Engineering | Material

Espinosa, Horacio D.

285

> REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 1 Abstract--The HelioClim-1 database contains daily values of  

E-Print Network (OSTI)

-meteorology, solar energy, ocean, health, architecture, air quality, GEOSS. I. INTRODUCTION HE surface solar-- The HelioClim-1 database contains daily values of the solar radiation reaching the ground. This GEOSS-CORE) covers Europe, Africa and the Atlantic Ocean, from 1985 to 2005. It is freely accessible at no cost

Paris-Sud XI, Université de

286

SPACE WAR SPACE DAILY TERRA DAILY MARS DAILY SPACE MART SPACE TRAVEL GPS DAILY ENERGY DAILY Unique Porous Copper Structure  

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Unique Porous Copper Structure Enables New Generation Of Military Micro-Detonators by Staff Writers Athens GA (SPX) Dec 19, 2007 Tiny copper structures with pores at both the nanometer and micron size, the highly-uniform copper structures will be incorporated into integrated circuits - then chemically

Bennett, Gisele

287

Spatial and Quantitative Approach to Incorporating Stakeholder Values into Total Maximum Daily Loads: Dominguez Channel Case Study  

SciTech Connect

The Federal Clean Water Act (CWA) Section 303(d)(1)(A) requires each state to identify those waters that are not achieving water quality standards. The result of this assessment is called the 303(d) list. The CWA also requires states to develop and implement Total Maximum Daily Loads (TMDLs) for these waters on the 303(d) list. A TMDL specifies the maximum amount of a pollutant that a water body can receive and still meet water quality standards, and allocates the pollutant loadings to point and non-point sources. Nationwide, over 34,900 segments of waterways have been listed as impaired by the Environmental Protection Agency (EPA 2006). The EPA enlists state agencies and local communities to submit TMDL plans to reduce discharges by specified dates or have them developed by the EPA. The Department of Energy requested Lawrence Livermore National Laboratory (LLNL) to develop appropriate tools to assist in improving the TMDL process. An investigation of this process by LLNL found that plans to reduce discharges were being developed based on a wide range of site investigation methods. Our investigation found that given the resources available to the interested and responsible parties, developing a quantitative stakeholder input process and using visualization tools to display quantitative information could improve the acceptability of TMDL plans. We developed a stakeholder allocation model (SAM) which uses multi-attribute utility theory to quantitatively structure the preferences of the major stakeholder groups. We then applied GIS to display allocation options in maps representing economic activity, community groups, and city agencies. This allows allocation options and stakeholder concerns to be represented in both space and time. The primary goal of this tool is to provide a quantitative and visual display of stakeholder concerns over possible TMDL options.

Stewart, J S; Baginski, T A; Greene, K G; Smith, A; Sicherman, A

2006-06-23T23:59:59.000Z

288

Savings Analysis of Utility Bills for Unmonitored Sites, Volume II: Detailed Savings Calculations, Texas LoanSTAR Monitoring and Analysis Program  

E-Print Network (OSTI)

= 83830 Saved = 5423 +- 7238 (i.e. +- 133.46%) Avg savings =301.3 +- 402.12 Total saved = 5423 x 30.5 = 165,402 kWh 1 Non-School Year Model Electricity Model: Un-grouped Mean.kWh N = 6 Ymean = 4875.50 Std Dev = 327.74 CV-StDev = 6.7% Savings calculations... Measured = 90 Saved = -21 Avg savings =-1.17 Total saved = -21 x 30.5 = -641 Mcf 3 Non-School Year Model Gas Model: Un-grouped Mean.Mcf N = 5 Ymean = 0.54 Std Dev = 0.25 CV-StDev = 46.5% Savings calculations for Model: Un -group Mean. Mcf Baseline = 3...

Wei, G.; Eggebrecht, J.; Saman, N. F.; Claridge, D. E.

1995-01-01T23:59:59.000Z

289

RTOG 0913: A Phase 1 Study of Daily Everolimus (RAD001) in Combination With Radiation Therapy and Temozolomide in Patients With Newly Diagnosed Glioblastoma  

SciTech Connect

Purpose: To determine the safety of the mammalian target of rapamycin inhibitor everolimus (RAD001) administered daily with concurrent radiation and temozolomide in newly diagnosed glioblastoma patients. Methods and Materials: Everolimus was administered daily with concurrent radiation (60 Gy in 30 fractions) and temozolomide (75 mg/m{sup 2} per day). Everolimus was escalated from 2.5 mg/d (dose level 1) to 5 mg/d (dose level 2) to 10 mg/d (dose level 3). Adjuvant temozolomide was delivered at 150 to 200 mg/m{sup 2} on days 1 to 5, every 28 days, for up to 12 cycles, with concurrent everolimus at the previously established daily dose of 10 mg/d. Dose escalation continued if a dose level produced dose-limiting toxicities (DLTs) in fewer than 3 of the first 6 evaluable patients. Results: Between October 28, 2010, and July 2, 2012, the Radiation Therapy Oncology Group 0913 protocol initially registered a total of 35 patients, with 25 patients successfully meeting enrollment criteria receiving the drug and evaluable for toxicity. Everolimus was successfully escalated to the predetermined maximum tolerated dose of 10 mg/d. Two of the first 6 eligible patients had a DLT at each dose level. DLTs included gait disturbance, febrile neutropenia, rash, fatigue, thrombocytopenia, hypoxia, ear pain, headache, and mucositis. Other common toxicities were grade 1 or 2 hypercholesterolemia and hypertriglyceridemia. At the time of analysis, there was 1 death reported, which was attributed to tumor progression. Conclusions: Daily oral everolimus (10 mg) combined with both concurrent radiation and temozolomide followed by adjuvant temozolomide is well tolerated, with an acceptable toxicity profile. A randomized phase 2 clinical trial with mandatory correlative biomarker analysis is currently under way, designed to both determine the efficacy of this regimen and identify molecular determinants of response.

Chinnaiyan, Prakash, E-mail: prakash.chinnaiyan@moffitt.org [Department of Radiation Oncology, Experimental Therapeutics and Cancer Imaging and Metabolism, H. Lee Moffitt Cancer Center, Tampa, Florida (United States); Won, Minhee [Radiation Therapy Oncology Group, Philadelphia, Pennsylvania (United States); Wen, Patrick Y. [Center for Neuro-Oncology, Dana-Farber/Brigham and Women's Cancer Center, Boston, Massachusetts (United States); Rojiani, Amyn M. [Department of Pathology, Medical College of Georgia, Augusta, Georgia (United States); Wendland, Merideth [Radiation Oncology, US Oncology-Willamette Valley Cancer Institute, Eugene, Oregon (United States); Dipetrillo, Thomas A. [Department of Radiation Oncology, Rhode Island Hospital, Providence, Rhode Island (United States); Corn, Benjamin W. [Department of Radiation Oncology, Tel Aviv Medical Center, Tel Aviv (Israel); Mehta, Minesh P. [Department of Radiation Oncology, University of Maryland, Baltimore, Maryland (United States)

2013-08-01T23:59:59.000Z

290

The dosimetric impact of daily setup error on target volumes and surrounding normal tissue in the treatment of prostate cancer with intensity-modulated radiation therapy  

SciTech Connect

The purpose of this study was to evaluate the impact of daily setup error and interfraction organ motion on the overall dosimetric radiation treatment plans. Twelve patients undergoing definitive intensity-modulated radiation therapy (IMRT) treatments for prostate cancer were evaluated in this institutional review board-approved study. Each patient had fiducial markers placed into the prostate gland before treatment planning computed tomography scan. IMRT plans were generated using the Eclipse treatment planning system. Each patient was treated to a dose of 8100 cGy given in 45 fractions. In this study, we retrospectively created a plan for each treatment day that had a shift available. To calculate the dose, the patient would have received under this plan, we mathematically 'negated' the shift by moving the isocenter in the exact opposite direction of the shift. The individualized daily plans were combined to generate an overall plan sum. The dose distributions from these plans were compared with the treatment plans that were used to treat the patients. Three-hundred ninety daily shifts were negated and their corresponding plans evaluated. The mean isocenter shift based on the location of the fiducial markers was 3.3 {+-} 6.5 mm to the right, 1.6 {+-} 5.1 mm posteriorly, and 1.0 {+-} 5.0 mm along the caudal direction. The mean D95 doses for the prostate gland when setup error was corrected and uncorrected were 8228 and 7844 cGy (p < 0.002), respectively, and for the planning target volume (PTV8100) was 8089 and 7303 cGy (p < 0.001), respectively. The mean V95 values when patient setup was corrected and uncorrected were 99.9% and 87.3%, respectively, for the PTV8100 volume (p < 0.0001). At an individual patient level, the difference in the D95 value for the prostate volume could be >1200 cGy and for the PTV8100 could approach almost 2000 cGy when comparing corrected against uncorrected plans. There was no statistically significant difference in the D35 parameter for the surrounding normal tissue except for the dose received by the penile bulb and the right hip. Our dosimetric evaluation suggests significant underdosing with inaccurate target localization and emphasizes the importance of accurate patient setup and target localization. Further studies are needed to evaluate the impact of intrafraction organ motion, rotation, and deformation on doses delivered to target volumes.

Algan, Ozer, E-mail: oalgan@ouhsc.edu [Department of Radiation Oncology, Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK (United States); Jamgade, Ambarish; Ali, Imad; Christie, Alana; Thompson, J. Spencer; Thompson, David; Ahmad, Salahuddin; Herman, Terence [Department of Radiation Oncology, Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK (United States)

2012-01-01T23:59:59.000Z

291

Organ Preservation With Daily Concurrent Chemoradiotherapy Using Superselective Intra-Arterial Infusion via a Superficial Temporal Artery for T3 and T4 Head and Neck Cancer  

SciTech Connect

Purpose: To evaluate the therapeutic results and rate of organ preservation in patients with advanced head and neck cancer treated with superselective intra-arterial chemotherapy via a superficial temporal artery and daily concurrent radiotherapy. Methods and Materials: Between April 2002 and March 2006, 30 patients with T3 or T4a squamous cell carcinoma of the head and neck underwent intra-arterial chemoradiotherapy. Treatment consisted of superselective intra-arterial infusions (docetaxel, total 60 mg/m{sup 2}; cisplatin, total 150 mg/m{sup 2}) and daily concurrent radiotherapy (total, 60 Gy) for 6 weeks. Results: The median follow-up for all patients was 46.2 months (range, 10-90 months). The median follow-up for living patients was 49.7 months (range, 36-90 months). After intra-arterial chemoradiotherapy was administered, primary site complete response was achieved in 30 (100%) of 30 cases. Seven patients (23.3%) died. Using the Kaplan-Meier method, 1-year, 3-year, and 5-year survival rates were 96.7%, 83.1%, and 70.2%, respectively, while 1-year, 3-year, and 5-year local control rates were 83.3%, 79.7%, and 73.0%, respectively. Grade 3 or 4 mucositis occurred in 20 cases (66.7%). Grade 3 toxicities included dysphagia in 20 cases (66.7%), dermatitis in 6 cases (20%), nausea/vomiting in 2 cases (6.7%), and neutropenia and thrombocytopenia in 1 case (3.3%). No osteoradionecrosis of mandible and maxillary bones developed during follow-up. Conclusions: Intra-arterial chemoradiotherapy using a superficial temporal artery provided good overall survival and local control rates. This combination chemoradiotherapy approach can preserve organs and minimize functional disturbance, thus contributing to patients' quality of life.

Mitsudo, Kenji, E-mail: mitsudo@yokohama-cu.ac.j [Department of Oral and Maxillofacial Surgery, Yokohama City University Graduate School of Medicine, Yokohama (Japan); Shigetomi, Toshio [Department of Oral and Maxillofacial Surgery, Nagoya University Graduate School of Medicine, Nagoya (Japan); Fujimoto, Yasushi [Department of Otolaryngology, Nagoya University Graduate School of Medicine, Nagoya (Japan); Nishiguchi, Hiroaki; Yamamoto, Noriyuki; Furue, Hiroki; Ueda, Minoru [Department of Oral and Maxillofacial Surgery, Nagoya University Graduate School of Medicine, Nagoya (Japan); Itoh, Yoshiyuki [Department of Radiology, Nagoya University Graduate School of Medicine, Nagoya (Japan); Fuwa, Nobukazu [Department of Radiation Oncology, Southern Tohoku Proton Therapy Center, Koriyama (Japan); Tohnai, Iwai [Department of Oral and Maxillofacial Surgery, Yokohama City University Graduate School of Medicine, Yokohama (Japan)

2011-04-01T23:59:59.000Z

292

A comprehensive power loss, efficiency, reliability and cost calculation of a 1MW/500kWh battery based energy storage system for frequency regulation application  

Science Journals Connector (OSTI)

Abstract Battery based energy storage system (ESS) has tremendous diversity of application with an intense focus on frequency regulation market. An ESS typically comprised of a battery and a power conversion system. A calculation of performance parameters is performed in this research. The aim is to formulate an in-depth analysis of the ESS in terms of power losses of the semiconductor and electrical devices, efficiency, reliability and cost which would foster various research groups and industries around the globe to improve their future product. In view of this, a relation between the operating conditions and power losses is established to evaluate the efficiency of the system. The power loss calculation presented in this paper has taken into account the conduction and switching losses of the semiconductor devices. Afterwards, the Arrhenius Life Stress relation is adopted to calculate the reliability of the system by considering temperature as a covariate. And finally, a cost calculation is executed and presented as a percentage of total cost of the ESS. It has been found that the power loss and efficiency of the ESS at rated power is 146kW and 85% respectively. Furthermore, the mean time between failures of the ESS is 8 years and reliability remains at 73% after a year. The major cost impact observed is for battery and PCS as 58% and 16% respectively. Finally, it has been determined that further research is necessary for higher efficient and lower cost system for high penetration of energy storage system in the market.

Md Arifujjaman

2015-01-01T23:59:59.000Z

293

Daily Texan October 31, 2013  

E-Print Network (OSTI)

inside of the building by identifying the places to install the air barrier to seal," Guzman said. "These in the brick where air-conditioned air was escaping from the building. Tony Guzman, project manager from Project Management and Construction Services, said the discovery of the leaked air was unexpected

Johnston, Daniel

294

Klein, L.C., Bennett, J.M., Whetzel, C.A., & Ritter, F.E. (2008). Daily caffeine use impacts neuroendocrine and cardiovascular responses to laboratory stress in healthy  

E-Print Network (OSTI)

-reported daily caffeine use significantly predicted baseline heart rate and salivary alpha amylase, a surrogate.e., cortisol, DHEA-S, alpha amylase) but not cardiovascular (i.e., blood pressure, heart rate) responses and 15-min after the stressor to determine cortisol, dehydroepiandrosterone-sulfate (DHEA-S), and alpha

Ritter, Frank

295

Infrastructure systems, such as buildings, schools, roads, bridges, water lines, sewage systems, communication systems, and power plants, are a fundamental part of daily life. Both rapid and gradual climate changes can affect  

E-Print Network (OSTI)

and gradual climate changes can affect these systems and have significant impacts on society. Extreme weather infrastructure sector make practical decisions in order to adapt to climate changes and variations systems, communication systems, and power plants, are a fundamental part of daily life. Both rapid

296

Advanced chemistry-transport modeling and observing systems allow daily air quality observations, short-term forecasts, and real-time analyses of air quality at the global and  

E-Print Network (OSTI)

Advanced chemistry-transport modeling and observing systems allow daily air quality observations, short-term forecasts, and real-time analyses of air quality at the global and European scales control measures that could be taken for managing such episodes, European-scale air quality forecasting

Paris-Sud XI, Université de

297

03/01/2006 09:51 AMLoading "People's Daily Online --Chinese experimental thermonuclear reactor on discharge test in July" Page 1 of 1http://english.people.com.cn/200603/01/print20060301_247035.html  

E-Print Network (OSTI)

03/01/2006 09:51 AMLoading "People's Daily Online -- Chinese experimental thermonuclear reactor experimental thermonuclear reactor on discharge test in July China's new generation experimental Tokamak fusion and the former Soviet Union launched a 10 billion- euro ambitious plan, the International Thermonuclear

298

Case Study of Two MBCx Projects: Using M&V to Track Energy Performance  

E-Print Network (OSTI)

operation Re-establish supply air temperature set point reset control in AHU1 Other measures Approximately 483,000 kWh (10%), 2.7M lbs/yr steam (51%) #0;? Estimated using DOE 2 analysis Cost reduction $84,000 (14%), Payback 0.7 years 13 Soda Hall... 006 3/ 24/ 2 006 3/ 26/ 2 00 6 3/ 28/ 2 00 6 3/ 3 0/ 2 006 Date kW h 0 10 20 30 40 50 60 70 80 De g F AHU 1 Daily kWh AHU 3 Daily kWh AHU 4 Daily kWh OAT Daily Average AHU 1 supply fan malf. begins here. Same date as economizer fix. 17 M...

Jump, D.

2007-01-01T23:59:59.000Z

299

External Beam Accelerated Partial-Breast Irradiation Using 32 Gy in 8 Twice-Daily Fractions: 5-Year Results of a Prospective Study  

SciTech Connect

Purpose: External beam accelerated partial breast irradiation (APBI) is an increasingly popular technique for treatment of patients with early stage breast cancer following breast-conserving surgery. Here we present 5-year results of a prospective trial. Methods and Materials: From October 2003 through November 2005, 98 evaluable patients with stage I breast cancer were enrolled in the first dose step (32 Gy delivered in 8 twice-daily fractions) of a prospective, multi-institutional, dose escalation clinical trial of 3-dimensional conformal external beam APBI (3D-APBI). Median age was 61 years; median tumor size was 0.8 cm; 89% of tumors were estrogen receptor positive; 10% had a triple-negative phenotype; and 1% had a HER-2-positive subtype. Median follow-up was 71 months (range, 2-88 months; interquartile range, 64-75 months). Results: Five patients developed ipsilateral breast tumor recurrence (IBTR), for a 5-year actuarial IBTR rate of 5% (95% confidence interval [CI], 1%-10%). Three of these cases occurred in patients with triple-negative disease and 2 in non-triple-negative patients, for 5-year actuarial IBTR rates of 33% (95% CI, 0%-57%) and 2% (95% CI, 0%-6%; P<.0001), respectively. On multivariable analysis, triple-negative phenotype was the only predictor of IBTR, with borderline statistical significance after adjusting for tumor grade (P=.0537). Conclusions: Overall outcomes were excellent, particularly for patients with estrogen receptor-positive disease. Patients in this study with triple-negative breast cancer had a significantly higher IBTR rate than patients with other receptor phenotypes when treated with 3D-APBI. Larger, prospective 3D-APBI clinical trials should continue to evaluate the effect of hormone receptor phenotype on IBTR rates.

Pashtan, Itai M. [Harvard Radiation Oncology Program, Boston, Massachusetts (United States)] [Harvard Radiation Oncology Program, Boston, Massachusetts (United States); Recht, Abram [Department of Radiation Oncology, Beth Israel Deaconess Medical Center, Boston, Massachusetts (United States)] [Department of Radiation Oncology, Beth Israel Deaconess Medical Center, Boston, Massachusetts (United States); Ancukiewicz, Marek [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States)] [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); Brachtel, Elena [Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts (United States)] [Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts (United States); Abi-Raad, Rita F. [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States)] [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); D'Alessandro, Helen A. [Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts (United States)] [Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts (United States); Levy, Antonin; Wo, Jennifer Y. [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States)] [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); Hirsch, Ariel E. [Department of Radiation Oncology, Boston Medical Center, Boston University School of Medicine, Boston, Massachusetts (United States)] [Department of Radiation Oncology, Boston Medical Center, Boston University School of Medicine, Boston, Massachusetts (United States); Kachnic, Lisa A. [Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts (United States)] [Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts (United States); Goldberg, Saveli [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States)] [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); Specht, Michelle; Gadd, Michelle; Smith, Barbara L. [Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts (United States)] [Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts (United States); Powell, Simon N. [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States)] [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); Taghian, Alphonse G., E-mail: ataghian@partners.org [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States)

2012-11-01T23:59:59.000Z

300

Measurements of daily urinary uranium excretion in German peacekeeping personnel and residents of the Kosovo region to assess potential intakes of depleted uranium (DU)  

Science Journals Connector (OSTI)

Following the end of the Kosovo conflict, in June 1999, a study was instigated to evaluate whether there was a cause for concern of health risk from depleted uranium (DU) to German peacekeeping personnel serving in the Balkans. In addition, the investigations were extended to residents of Kosovo and southern Serbia, who lived in areas where DU ammunitions were deployed. In order to assess a possible DU intake, both the urinary uranium excretion of volunteer residents and water samples were collected and analysed using inductively coupled plasma-mass spectrometry (ICP-MS). More than 1300 urine samples from peacekeeping personnel and unexposed controls of different genders and age were analysed to determine uranium excretion parameters. The urine measurements for 113 unexposed subjects revealed a daily uranium excretion rate with a geometric mean of 13.9ng/d (geometric standard deviation (GSD)=2.17). The analysis of 1228 urine samples from the peacekeeping personnel resulted in a geometric mean of 12.8 ng/d (GSD=2.60). It follows that both unexposed controls and peacekeeping personnel excreted similar amounts of uranium. Inter-subject variation in uranium excretion was high and no significant age-specific differences were found. The second part of the study monitored 24h urine samples provided by selected residents of Kosovo and adjacent regions of Serbia compared to controls from Munich, Germany. Total uranium and isotope ratios were measured in order to determine DU content. 235U/238U ratios were within 0.3% of the natural value, and 236U/238U was less than 2נ10?7, indicating no significant DU in any of the urine samples provided, despite total uranium excretion being relatively high in some cases. Measurements of ground and tap water samples from regions where DU munitions were deployed did not show any contamination with DU, except in one sample. It is concluded that both peacekeeping personnel and residents serving or living in the Balkans, respectively, were not exposed to significant amounts of DU.

U. Oeh; N.D. Priest; P. Roth; K.V. Ragnarsdottir; W.B. Li; V. Hllriegl; M.F. Thirlwall; B. Michalke; A. Giussani; P. Schramel; H.G. Paretzke

2007-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Technology and System Level Demonstration of Highly Efficient...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

AvgGust: 6.5 mphsteady Temp MinAvgMax: 546368F Wind AvgGust: 2340 mph 20 Aerodynamic Improvements - Technical Progress Configurations Demo 2 - 24% Target Demo 1 - 14%...

302

Welcome to FUPWG Fall 2012  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

WELCOME TO MOBILE WELCOME TO MOBILE Presented by: Greg Reardon Energy Services Manager Alabama Power Company  Alabama Power Georgia Power  Gulf Power  Mississippi Power  Southern Power  Southern Company Services  Southern Telecom  Southern Linc 2 Operating Revenue - $17,657 Million Net Income - $ 2,203 Million EPS - 2.40 Shares Outstanding - 857 Million Ret on Avg Com Eqty - 13.04% Total Assets - $57,267 Million *257 CONSECUTIVE QUARTERS OF DIVIDENDS DATING TO 1948 *11 CONSECUTIVE YEARS OF DIVIDEND INCREASES 3 Customers Number of Customers Millions of kWh Sales Residential 3,809,000 53,341 Commercial 579,000 55,855

303

Parameterization of daily solar irradiance variability  

Science Journals Connector (OSTI)

The effects of solar systems operation can be compared only under very similar weather conditions. Diagnostics of the solar systems requires unequivocal determination of solar irradiation. Development of a method for precise identification of solar radiation day time profile is needed, as the methods used so far in the cloud cover determination are not satisfactory. The paper presents two optional methods, developed by the authors, for identification of the solar radiation profile. Advantages and disadvantages of the methods are also specified.

D. Czekalski; A. Chochowski; P. Obstawski

2012-01-01T23:59:59.000Z

304

Daily Wildfire Update June 11, 2012  

E-Print Network (OSTI)

, then back west to include Wilderness Ridge Way, Rist Creek Road, Spring Valley Road and CR41 and all Forest Service/Larimer County Location/County: Approximately 15 miles west of Fort Collins, Larimer Road 27E to Bellvue. 2. Areas south and west of Bellvue to include the Lory State Park area

305

Shanghai Daily wangyong@shanghaidaily.com  

E-Print Network (OSTI)

for an aging population and an obesity epidemic, sustainable clean water, re- duced air and water pollution: high air pollution and resulting diseases (eg, asthma, other lung diseases, cancer, etc); water pollution; climate change and risks to health; obesity, which is now of epidemic proportions among children

306

Energy Assurance Daily | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

issues. Published Monday through Friday to inform stakeholders of developments affecting energy systems, flows, and markets, it provides highlights of energy issues rather than a...

307

Daily Flight Planning and Operations Schedule  

NLE Websites -- All DOE Office Websites (Extended Search)

to aircraft close at 9:45AM Return to Ponca City 2PM (depending on mission) Afternoon: review observations, plan for next day If 2PM take-off move aircraft out of hangar late...

308

Fall 2013 BOSTONIA Last year, the Daily  

E-Print Network (OSTI)

this system on a model minicity in his lab. SMARTER HVAC BU engineers have designed software that, once uploaded to a building's HVAC system, would measure airflow room by room and revise it to meet minimum standards, decreasing energy costs while keeping occupants happy. The invention earned Michael Gevelber

Spence, Harlan Ernest

309

Daily life support : building a collective neighborhood  

E-Print Network (OSTI)

Do the house forms and residential neighborhoods commonly found in the U.S. accommodate the present needs and lifestyles of the people who live in them? The single-family detached house and multi-family units like the ...

Hamanaka, Leslie K. (Leslie Kinu)

1990-01-01T23:59:59.000Z

310

EIA-930 Hourly and Daily Balancing ...  

Annual Energy Outlook 2012 (EIA)

not change from day-to-day or hour-to-hour, as specified in the immediately preceding section. For each hour of the day, hourly integrated demand is to be posted within ten...

311

ARM - General Changes in Daily Lives  

NLE Websites -- All DOE Office Websites (Extended Search)

more about the scientific predictions about the climate changes due to the greenhouse effect, and so have the opportunity to contribute to future planning and policy making....

312

ARRA521 Recovery Act - Project Daily Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Spend Plan Spend Plan Obligated to Contracts Payments to Date Unpaid Balance Argonne National Laboratory $79,000,000 $79,000,000 $78,471,376 $528,624 Brookhaven National Laboratory $70,810,000 $70,809,616 $70,809,616 $0 Energy Technology Engineering Center $51,675,000 $51,675,000 $51,675,000 $0 Hanford (Office of River Protection) $326,035,000 $325,999,617 $325,999,617 $0 Hanford (Richland) $1,634,500,000 $1,633,901,799 $1,633,277,979 $623,821 Idaho $467,875,000 $467,840,907 $467,840,907 $0 Los Alamos National Laboratory $211,975,000 $211,954,781 $211,954,781 $0 Moab $108,350,000 $108,350,000 $108,204,128 $145,872 Mound $17,900,000 $17,525,587 $17,525,587 $0 Nevada Nuclear Security Site $44,325,000 $44,300,871 $44,300,869 $2 Oak Ridge $755,110,000 $754,990,004 $739,849,558 $15,140,447 Paducah $80,400,000 $80,400,000

313

Dissertations Circulating from University Libraries, Virginia Tech as of Feb. 1996 and Feb. 1998  

E-Print Network (OSTI)

in branches main+branch 1863 5953 3.20 libraries avg. no. circ's per item on campus off-site 1911 216 0.11 avg. no. circ's per item off-site all sites 3774 6169 1.63 avg.no. circ's per item as of Feb. 1996 in branches main+branch 1918 8221 4.29 libraries avg. no. circ's per item on campus off-site 2272 217 0.10 avg

Beex, A. A. "Louis"

314

Biofuels development in Maine: Using trees to oil the wheels of sustainability -Maine news, sports, obituaries, weather -Bangor Daily News http://bangordailynews.com/2013/03/12/opinion/biofuels-development-in-maine-using-trees-to-oil-the-wheels-of-sustain  

E-Print Network (OSTI)

Biofuels development in Maine: Using trees to oil the wheels of sustainability - Maine news, sports, obituaries, weather - Bangor Daily News http://bangordailynews.com/2013/03/12/opinion/biofuels-development-in-maine-using-trees-to-oil-the-wheels-of-sustainability/print/[3/13/2013 1:54:43 PM] Biofuels development

Thomas, Andrew

315

26/03/2009 12:58NO SUCH THING AS ARSEHOLE BEES, SAY EXPERTS -The Daily Mash Page 1 of 2http://www.thedailymash.co.uk/animals/animals-headlines/no-such-thing-as-arsehole-bees%2c-say-experts-200903241660/  

E-Print Network (OSTI)

SATAN MAKES ROOM FOR PARENTS WHO COMPLAINED ABOUT DISABLED TV ADHOLE2 Your email address Enter search HEADLINES Via RSS: Via Twitter: ADHOLE1 MASH TV: MASH TV: SEARCH THE DAILY MASH Go TOP TEN THIS MONTH PUT term... Bees and Bee Keeping Bees, Bee Keeping and Bee Products Know More about It! www

Gardner, Andy

316

Potential for Higher Treatment Failure in Obese Patients: Correlation of Elevated Body Mass Index and Increased Daily Prostate Deviations From the Radiation Beam Isocenters in an Analysis of 1,465 Computed Tomographic Images  

SciTech Connect

Purpose: Recent clinical outcome studies on prostate cancer have reported the influence of patient's obesity on the biochemical failure rates after various treatment modalities. In this study, we investigated the effect of patient's physical characteristics on prostate shift in external beam radiotherapy (EBRT) and hypothesized that there maybe a correlation between patient physique and tumor shift. Methods and Materials: A retrospective analysis was performed using data for 117 patients who received image-guided radiation therapy (IGRT) for prostate cancer between January 2005 and April 2007. A total of 1,465 CT scans were analyzed. The standard deviations (SDs) of prostate shifts for all patients, along with patient weight, body mass index (BMI), and subcutaneous adipose-tissue thickness (SAT), were determined. Spearman rank correlation analysis was performed. Results: Of the 117 patients, 26.5% were considered normal weight, 48.7% were overweight, 17.9% were mildly obese, and 6.9% were moderately to severely obese. Notably 1.3%, 1.5%, 2.0%, and 21.2% of the respective shifts were greater than 10 mm in the left-right (LR) direction for the four patient groups, whereas in the anterior-posterior direction the shifts are 18.2%, 12.6%, 6.7%, and 21.0%, respectively. Strong correlations were observed between SAT, BMI, patient weight, and SDs of daily shifts in the LR direction (p < 0.01). Conclusions: The strong correlation between obesity and shift indicates that without image-guided radiation therapy, the target volume (prostate with or without seminal vesicles) may not receive the intended dose for patients who are moderate to severely obese. This may explain the higher recurrence rate with conventional external beam radiation therapy.

Wong, James R. [Department of Radiation Oncology, Carol G. Simon Cancer Center, Morristown Memorial Hospital, Morristown, NJ (United States)], E-mail: jackie.vizoso@atlantichealth.org; Gao Zhanrong; Merrick, Scott; Wilson, Paula [Department of Radiation Oncology, Carol G. Simon Cancer Center, Morristown Memorial Hospital, Morristown, NJ (United States); Uematsu, Minoru [Radiation Oncology, Uematsu-Atsuchi-Serendipity Oncology Center, Terukuni, Kagoshima (Japan); Woo, Kevin; Cheng, C.-W. [Department of Radiation Oncology, The Carol G. Simon Cancer Center, Morristown Memorial Hospital, Morristown, NJ (United States)

2009-09-01T23:59:59.000Z

317

Copyright 2005 Investor's Business Daily Inc. INVESTOR'S BUSINESS DAILY MONDAY, JUNE 6, 2005 A9  

E-Print Network (OSTI)

for the next 12 months, says a new survey. They see rising oil prices as the leading cause of slipping momentum Oil Prices Slow Multinationals' Growth Among firms citing rising oil prices as: TOP DOWN World economy

Kuzmanovic, Aleksandar

318

Daily PlanetDaily PlanetUniversity of Michigan College of Engineering Spring 2010  

E-Print Network (OSTI)

..................... 14 Pew Fellowship winner .... 16 Climate Change Critique.. 21 Reflections on the Copenhagen Summitby Center. Foreign leaders, diplomats, advocacy groups,companies,andstudents from all over the world were and packets.GoingfartherintotheBellaCenter,therewere several attractions, such as the "Climate Wall", a wall

Eustice, Ryan

319

Pack.PDF  

NLE Websites -- All DOE Office Websites (Extended Search)

February 1999 February 1999 Revised: 05/05/99 CHEVROLET S-10 ELECTRIC (NIMH BATTERIES) PERFORMANCE CHARACTERIZATION SUMMARY ELECTRIC TRANSPORTATION DIVISION Urban Range (On Urban Pomona Loop - see other side for map) Test UR1 UR2 UR3 UR4 Payload (lb.) 180 180 920 920 AC kWh Recharge 54.93 57.09 54.98 51.34 AC kWh/mi. 0.78 0.91 0.87 0.85 Range (mi.) 70.4 63.0 63.0 60.4 Avg. Ambient Temp. 63°F 66°F 63°F 50°F UR1 Urban Range Test, Min Payload, No Auxiliary Loads UR2 Urban Range Test, Min Payload, A/C on High, Headlights on Low, Radio On UR3 Urban Range Test, Max Payload, No Auxiliary Loads UR4 Urban Range Test, Max Payload, A/C on High, Headlights on Low, Radio On State of Charge Meter (UR1) Freeway Range (On Freeway Pomona Loop - see other side for map) Test FW1 FW2 FW3 FW4 Payload (lb.) 180 180 920 920 AC kWh Recharge

320

EV Project Chevrolet Volt Vehicle Summary Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

42 Overall electrical energy consumption (AC Whmi) 231 Number of trips 676,414 Total distance traveled (mi) 5,753,009 Avg trip distance (mi) 8.3 Avg distance traveled per day...

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

EV Project Chevrolet Volt Vehicle Summary Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

fuel economy (mpg) 155 Overall electrical energy consumption (AC Whmi) 242 Number of trips 147,886 Total distance traveled (mi) 1,184,265 Avg trip distance (mi) 8.0 Avg distance...

322

EV Project Nissan Leaf Vehicle Summary Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2011 through March 2011 Vehicle Usage Number of trips 3,364 Total distance traveled (mi) 21,706 Avg trip distance (mi) 5.8 Avg distance traveled per day when the vehicle was...

323

EV Project Nissan Leaf Vehicle Summary Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

through September 2012 Vehicle Usage Number of trips 813,430 Total distance traveled (mi) 5,837,173 Avg trip distance (mi) 7.2 Avg distance traveled per day when the vehicle was...

324

EV Project Nissan Leaf Vehicle Summary Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2012 through June 2012 Vehicle Usage Number of trips 787,895 Total distance traveled (mi) 5,666,469 Avg trip distance (mi) 7.2 Avg distance traveled per day when the vehicle was...

325

EV Project Nissan Leaf Vehicle Summary Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

through December 2012 Vehicle Usage Number of trips 969,853 Total distance traveled (mi) 6,724,952 Avg trip distance (mi) 6.9 Avg distance traveled per day when the vehicle was...

326

EV Project NIssan Leaf Vehicle Summary Report-Reporting period...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

through September 2011 Vehicle Usage Number of trips 536,548 Total distance traveled (mi) 3,718,272 Avg trip distance (mi) 6.9 Avg distance traveled per day when the vehicle was...

327

EV Project NIssan Leaf Vehicle Summary Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2012 through March 2012 Vehicle Usage Number of trips 773,602 Total distance traveled (mi) 5,558,155 Avg trip distance (mi) 7.2 Avg distance traveled per day when the vehicle was...

328

EV Project NIssan Leaf Vehicle Summary Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

through December 2011 Vehicle Usage Number of trips 707,330 Total distance traveled (mi) 4,878,735 Avg trip distance (mi) 6.9 Avg distance traveled per day when the vehicle was...

329

EV Project NIssan Leaf Vehicle Summary Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2011 through June 2011 Vehicle Usage Number of trips 160,588 Total distance traveled (mi) 1,077,931 Avg trip distance (mi) 6.7 Avg distance traveled per day when the vehicle was...

330

CP ROAD MAP Mix Design & Analysis Track  

E-Print Network (OSTI)

& reinforcing steel. . . The "Resistance to severe weathering and sulfate waters is determined largely Beams: 764, 7-d ­ Avg. 601 psi 28-d ­ Avg. 734 psi #12;SAUDI ARABIA - 1970 · $660 million headquarters

331

A B S T R A C T OIIOof iiiosl cli;ill(wgiiig problems in the field of friinie-  

E-Print Network (OSTI)

. - Avg % error = 9.3 % 8 - f 6 - E- b:0 Calc Dy Disp. - Avg % error = 6.0 % m:o Calc 0 5 10 15 Bead No

Miga, Michael I.

332

EV Project Nissan Leaf Vehicle Summary Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

40 Reporting period: January 2013 through March 2013 Vehicle Usage Number of trips 1,075,251 Total distance traveled (mi) 7,563,354 Avg trip distance (mi) 7.0 Avg distance...

333

The curse of dimension in nonparametric regression  

E-Print Network (OSTI)

to three dimensions. Rotating teapot: This consists ofimages of a rotating teapot, each 3050 pixels in size. ThusAvg of max diam square n Teapot dataset ? n : Avg of max

Kpotufe, Samory

2010-01-01T23:59:59.000Z

334

Seagate Crystal Reports - RADCM  

Office of Environmental Management (EM)

Sludges & Treatment Residues - 1 Sludges & Treatment Residues - 1 WASTE STREAM CODE: 01582 STREAM NAME:Sludges & Treatment Residues - 1 MPC NAME:Inorganic Sludges TOTAL CURIES: 26.000 Approved Volume : Future Volume Avg: Future Volume Lower Limit: Future Volume Upper Limit: 100.000 Sludges & Treatment Residues - 1 Isotopes Scandium-46 Avg Concentration: Low Limit Concent: Upper Limit Concent: Tin-113 Avg Concentration: Low Limit Concent: Upper Limit Concent: Strontium-85 Avg Concentration: Low Limit Concent: Upper Limit Concent: Tantalum-182 Avg Concentration: Low Limit Concent: Upper Limit Concent: Californium-250 Avg Concentration: Low Limit Concent: Upper Limit Concent: Lead-212 Avg Concentration: Low Limit Concent: Upper Limit Concent: Americium-244 Avg Concentration: Low Limit Concent: Upper Limit Concent:

335

Tetrahedron: Asymmetry report number 86 a-Vinylic amino acids: occurrence, asymmetric synthesis,  

E-Print Network (OSTI)

-Substituted . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 871 2.3. c-Substituted . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 871 2.3.1. MVG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 871 2.3.2. AVG

Berkowitz, David

336

_MainReport  

NLE Websites -- All DOE Office Websites (Extended Search)

Usage Usage Overall fuel economy (mpg) 139 Overall electrical energy consumption (AC Wh/mi) 293 Number of trips¹ 76,425 Total distance traveled (mi) 609,737 Avg trip distance (mi) 8.0 Avg distance traveled per day when the vehicle was driven (mi) 36.4 Avg number of trips between charging events 3.0 Avg distance traveled between charging events (mi) 24.1 Avg number of charging events per day when the vehicle was driven 1.5

337

Data:650daf17-bfc0-4b67-8a38-44eeb0c29323 | Open Energy Information  

Open Energy Info (EERE)

daf17-bfc0-4b67-8a38-44eeb0c29323 daf17-bfc0-4b67-8a38-44eeb0c29323 No revision has been approved for this page. It is currently under review by our subject matter experts. Jump to: navigation, search Loading... 1. Basic Information 2. Demand 3. Energy << Previous 1 2 3 Next >> Basic Information Utility name: Lincoln Electric System Effective date: End date if known: Rate name: Large Power Contract Off-Peak Daily Dual Primary Sector: Description: Excess kVA Source or reference: http://www.les.com/your_business/rate_schedules_lpc.aspx Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service Voltage Minimum (V): Maximum (V): Character of Service Voltage Category: Phase Wiring: << Previous

338

Data:Afc8896e-daa3-4c62-9903-5e233f616134 | Open Energy Information  

Open Energy Info (EERE)

Afc8896e-daa3-4c62-9903-5e233f616134 Afc8896e-daa3-4c62-9903-5e233f616134 No revision has been approved for this page. It is currently under review by our subject matter experts. Jump to: navigation, search Loading... 1. Basic Information 2. Demand 3. Energy << Previous 1 2 3 Next >> Basic Information Utility name: Lincoln Electric System Effective date: End date if known: Rate name: Large Light and Power Off-Peak Seasonal Daily Secondary Sector: Description: Excess kVA Source or reference: http://www.les.com/your_business/rate_schedules_llp.aspx Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service Voltage Minimum (V): Maximum (V): Character of Service Voltage Category: Phase Wiring: << Previous

339

Data:B0f8cf1f-9675-4c3c-85ba-a97573938074 | Open Energy Information  

Open Energy Info (EERE)

f-9675-4c3c-85ba-a97573938074 f-9675-4c3c-85ba-a97573938074 No revision has been approved for this page. It is currently under review by our subject matter experts. Jump to: navigation, search Loading... 1. Basic Information 2. Demand 3. Energy << Previous 1 2 3 Next >> Basic Information Utility name: Lincoln Electric System Effective date: End date if known: Rate name: Large Power Contract Off-Peak Daily Primary Sector: Description: Excess kVA Source or reference: http://www.les.com/your_business/rate_schedules_lpc.aspx Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service Voltage Minimum (V): Maximum (V): Character of Service Voltage Category: Phase Wiring: << Previous 1 2 3 Next >>

340

Data:Dcc5815a-06d5-4472-b92f-a6f4cf31491f | Open Energy Information  

Open Energy Info (EERE)

a-06d5-4472-b92f-a6f4cf31491f a-06d5-4472-b92f-a6f4cf31491f No revision has been approved for this page. It is currently under review by our subject matter experts. Jump to: navigation, search Loading... 1. Basic Information 2. Demand 3. Energy << Previous 1 2 3 Next >> Basic Information Utility name: Lincoln Electric System Effective date: End date if known: Rate name: Large Power Contract Off-Peak Daily Secondary Sector: Description: Excess kVA Source or reference: http://www.les.com/your_business/rate_schedules_lpc.aspx Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service Voltage Minimum (V): Maximum (V): Character of Service Voltage Category: Phase Wiring: << Previous 1 2 3 Next >>

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
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341

Seagate Crystal Reports - RADCM  

Office of Environmental Management (EM)

Sludge, Salt, Liquid Sludge, Salt, Liquid WASTE STREAM CODE: 02113 STREAM NAME:Sludge, Salt, Liquid MPC NAME:Aqueous Liquids/Slurries TOTAL CURIES: Approved Volume : Future Volume Avg: Future Volume Lower Limit: Future Volume Upper Limit: 100.000 Sludge, Salt, Liquid Isotopes Americium-241 Avg Concentration: 3.4967E-001 Ci/m3 Low Limit Concent: Upper Limit Concent: Cadmium-113m Avg Concentration: 8.4542E-002 Ci/m3 Low Limit Concent: Upper Limit Concent: Niobium-93m Avg Concentration: 1.8159E-002 Ci/m3 Low Limit Concent: Upper Limit Concent: Protactinium-231 Avg Concentration: 7.8039E-004 Ci/m3 Low Limit Concent: Upper Limit Concent: Europium-152 Avg Concentration: 7.4037E-003 Ci/m3 Low Limit Concent: Upper Limit Concent: Plutonium-240 Avg Concentration: 4.4672E-002 Ci/m3 Low Limit Concent: Upper Limit Concent:

342

An Improved Gridded Historical Daily Precipitation Analysis for Brazil  

Science Journals Connector (OSTI)

A gauge-only precipitation data quality control and analysis system has been developed for monitoring precipitation at NOAAs Climate Prediction Center (CPC). Over the past 10 yr the system has been used to develop and deliver many different ...

Viviane B. S. Silva; Vernon E. Kousky; Wei Shi; R. Wayne Higgins

2007-08-01T23:59:59.000Z

343

Reconstructing influenza incidence by deconvolution of daily mortality time series  

Science Journals Connector (OSTI)

...On September 28, a 200,000-person Liberty Loan Drive took place on the streets...September 27, one day before the notorious Liberty Loan parade, and seven days before the...research group meetings at which this project was begun. The authors declare no conflict...

Edward Goldstein; Jonathan Dushoff; Junling Ma; Joshua B. Plotkin; David J. D. Earn; Marc Lipsitch

2009-01-01T23:59:59.000Z

344

Jeff Lab director plans retirement (Daily Press) | Jefferson...  

NLE Websites -- All DOE Office Websites (Extended Search)

and Jefferson Science Associates chairman - praised Leemann's leadership during the transition to a new management contract last year and on the expansion plans. "This...

345

The Preuss School UCSD Daily Bulletin B Day  

E-Print Network (OSTI)

like ASB Ball, college formals, etc. Register online at www.mysignup.com/freedress Dates: April 18th Graders: Tuesday, March 21st will be the first day in the new wheel class: 6th Grade Science (Rupert

Russell, Lynn

346

The Preuss School UCSD Daily Bulletin A Day  

E-Print Network (OSTI)

like ASB Ball, college formals, etc. Register online at www.mysignup.com/freedress Dates: April 18th: Tuesday, March 21st will be the first day in the new wheel class: 6th Grade Science (Rupert) moves

Russell, Lynn

347

Jefferson Lab: Laser gun to eventually shoot down missiles (Daily...  

NLE Websites -- All DOE Office Websites (Extended Search)

articles.dailypress.com2011-02-21newsdp-nws-jefferson-lab-201102211jefferson-lab-researchers-free-electron-l... Submitted: Monday, February 21, 2011...

348

SNORKEL PRO-66 DAILY INSPECTION AND MAINTENANCE CHECKLIST  

E-Print Network (OSTI)

not be operated if not in proper mechanical condition. All defects must be reported to the Electric Shop Foreman is to be returned to the BMC Electric Shop at the end of the day or the end of the job, whichever comes first. Beginning Hours: ______________ Ending Hours: ______________ Fuel (DIESEL): ________gallons List all

Gelfond, Michael

349

The Preuss School UCSD Daily Bulletin B Day  

E-Print Network (OSTI)

/102, Library Recording in Library/Lab (through block 7) ART HISTORY Students: 83 Location: Walton Center History Location: Walton Center #12;Reminders LIBRARY CLOSED: Due to AP testing and inventory the library. Space on our late-activities bus is limited. If you are staying for tutoring, you must sign up before

Russell, Lynn

350

Magnetic Properties of Daily Sampled Total Suspended Particulates in Shanghai  

Science Journals Connector (OSTI)

Acquisition of isothermal remanent magnetization (IRM 10-5 Am2 kg-1) was made in fields of 20 mT, 30 mT, 1 T (SIRM) followed by demagnetiza tion in fields of ?20 mT, ?50 mT, ?100 mT, and ?300 mT using a Molspin pulse magnetizer and spinner magnetometer. ...

Jiong Shu; John A. Dearing; Andrew P. Morse; Lizhong Yu; Chaoyi Li

2000-05-09T23:59:59.000Z

351

Bacteria Total Maximum Daily Load Task Force Final Report  

E-Print Network (OSTI)

Research and Development Needs 51 References 64 Appendix 1: Bacteria TMDL Task Force Members and Expert Advisors 71 Appendix 2: Models Used in Bacteria Projects 73 as Described in EPA Publications... Appendix 3: EPA Bacteria TMDL Guidelines 78 Appendix 4: State Approaches to Bacteria TMDL 88 Development Appendix 5: Comments from Expert Advisory Group 100 1 Executive Summary In September 2006, the Texas...

Jones, C. Allan; Wagner, Kevin; Di Giovanni, George; Hauck, Larry; Mott, Joanna; Rifai, Hanadi; Srinivasan, Raghavan; Ward, George; Wythe, Kathy

352

An examination of daily information needs and sharing opportunities  

Science Journals Connector (OSTI)

A person often has highly context-sensitive information needs that require assistance from individuals in their social network. However, a person's social network is often not broad enough to include the right people in the right situations or circumstances ... Keywords: communal knowledge, design considerations, diary study, information need, information sharing

David Dearman; Melanie Kellar; Khai N. Truong

2008-11-01T23:59:59.000Z

353

INTRODUCTION Daily energetic expenditure and timeenergy budgets are useful for  

E-Print Network (OSTI)

production provided by the DLW method can be used to calculate MR. Many reptiles, however, excrete method requires capturing and dosing a study animal with water that has been enriched with isotopes of hydrogen (2 H, deuterium, or 3 H, tritium) and oxygen (18 O). A blood sample is taken before injection

Schluter, Dolph

354

Daily Texan During warm summer months, UT restores  

E-Print Network (OSTI)

the Renovation and Renewal Program. The program funds construction and renovation projects to sustain and improve, although no classes are housed there currently. The stone facade and stairwells of the building were

Johnston, Daniel

355

Modeling daily flow patterns individuals to characterize disease spread  

SciTech Connect

The effect of an individual's travels throughout a day on the spread of disease is examined using a deterministic SIR model. We determine which spatial and demographic characteristics most contribute to the disease spread and whether the progression of the disease can be slowed by appropriate vaccination of people belonging to a specific location-type.

Smallwood, J. (Jeanine); Hyman, J. M. (James M.); Mirchandani, Pitu B.

2002-11-17T23:59:59.000Z

356

Daily OMP Retro 4-29-12.xls  

NLE Websites -- All DOE Office Websites (Extended Search)

0 0 977 18 265 1585 94 HE19 0 1416 0 0 1291 17 262 1663 117 HE20 0 1393 0 0 1987 17 211 1603 101 HE21 0 1397 0 0 2149 17 245 1640 154 HE22 0 1399 0 0 2206 19 255 1628 130 HE23 0...

357

DAILY FACILITY AND PROGRAMMING SCHEDULE Tuesday, September 10th, 2013  

E-Print Network (OSTI)

:00 AM UGA Swimming & Diving Practice UGA Athletics-Swimming 50M Pool 9:00 AM 1:00 PM Swim Informal Recreation 50M Pool 2:00 PM 5:00 PM UGA Swimming & Diving Practice UGA Athletics-Swimming 50M Pool 5:00 PM 8:00 PM Athens Bulldog Swim Club Practice Community Group - ongoing 50M Pool 5:00 PM 10:00 PM Swim

Hall, Daniel

358

DAILY FACILITY AND PROGRAMMING SCHEDULE Monday, September 9, 2013  

E-Print Network (OSTI)

Meeting Intramural Sports Location Start End Event Customer 50M Pool 5:00 AM 8:00 AM UGA Swimming & Diving Practice UGA Athletics-Swimming 50M Pool 9:00 AM 1:00 PM Swim Informal Rec 50M Pool 9:05 AM 9:55 AM PEDB 1940 FFL Swimming Physical Education 50M Pool 10:10 AM 11:00 AM PEDB 1310 Intermediate Swimming

Scott, Robert A.

359

DAILY FACILITIES AND PROGRAMMING SCHEDULE Wednesday, September 10, 2014  

E-Print Network (OSTI)

Hall Swimming: 6-9am & 1-10pm Rec Pool and 9am-1pm & 5:30-10pm 50M Pool Table Tennis: 6am-10:45pm Table Meter Pool 8:00 AM 9:00 AM Triathlon Club 50 Meter Pool 9:00 AM 1:00 PM Swim 50 Meter Pool 9:05 AM 9:55 AM PEDB 1940, FFL Swimming 50 Meter Pool 10:10 AM 11:00 AM PEDB 1310, Inter Swimming 50 Meter Pool 11

Hall, Daniel

360

French Ambassador Pierre Vimont tours JLab (Daily Press) | Jefferson...  

NLE Websites -- All DOE Office Websites (Extended Search)

the United States, Pierre Vimont, spoke to about 250 people Thursday night about the political relationship between the two countries. "We want to be a true friend, a loyal and...

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

The Preuss School UCSD Daily Bulletin B Day  

E-Print Network (OSTI)

STAR Information Meeting, C101, 12:15pm-12:45pm - CURE Meeting for Seniors, E101, 1:00pm-2:00pm - Geared Up Project, Manchester Field, 2:30pm-3:30pm - Running Club, 4:00pm - ABC's of Opera Talk, Media a time he galloped over deep green moats On bridges princes had let down in friendship And sat at board

Russell, Lynn

362

Daily Air Temperature and Electricity Load in Spain  

Science Journals Connector (OSTI)

Weather has a significant impact on different sectors of the economy. One of the most sensitive is the electricity market, because power demand is linked to several weather variables, mainly the air temperature. This work analyzes the ...

Enric Valor; Vicente Meneu; Vicente Caselles

2001-08-01T23:59:59.000Z

363

The Preuss School UCSD Daily Bulletin A Day  

E-Print Network (OSTI)

in the United State replaced one regular light bulb with one of those new compact fluorescent bulbs E103 and return it to Ms. Garcia by Fri, May 5. Journalism is a student-led class with lots

Russell, Lynn

364

JLab's economic footprint expands (Daily Press) | Jefferson Lab  

NLE Websites -- All DOE Office Websites (Extended Search)

articles.dailypress.com2011-01-20newsdp-nws-jlab-economy-201101201jefferson-lab-national-labs-jlab Submitted: Thursday, January 20, 2011...

365

Daily HMS Extremes in Met Data - Hanford Site  

NLE Websites -- All DOE Office Websites (Extended Search)

Sun Feb 01 00:04:15 PST 2015 For the day: Sat Jan 31 MAX MAX MIN Total Station Spd Time Temp Time Temp Time Precip 1 PROS 15.6 0:15 39.7 15:00 35.4 7:00 0.00 2 EOC 17.1 6:00 36.3...

366

Daily OMP Retro 7-16-12.xls  

NLE Websites -- All DOE Office Websites (Extended Search)

0 126 333 581 2000 34 HE03 9 1120 1469 0 14 330 925 2000 38 HE04 9 1122 1224 0 3 355 871 2000 29 HE05 9 1143 1014 0 7 320 786 2000 62 HE06 9 1198 120 0 227 135 551 2000 198...

367

Performance of Quality Assurance Procedures on Daily Precipitation  

Science Journals Connector (OSTI)

The search for precipitation quality control (QC) methods has proven difficult. The high spatial and temporal variability associated with precipitation data causes high uncertainty and edge creep when regression-based approaches are applied. ...

Jinsheng You; Kenneth G. Hubbard; Saralees Nadarajah; Kenneth E. Kunkel

2007-05-01T23:59:59.000Z

368

Daily Reporting Rainfall Station GILBERT & NORMAN RIVERS Manual River Station  

E-Print Network (OSTI)

Rockfields TM Inorunie Strathmore LangdonR Esmeralda Malacura Green Hills Dismal Ck EtheridgeR Prestwood Wallam Spear Ck Saxby R Norman R Forest Ck East Ck Bunda Bunda Boorabin Ck Woodstock Saxby R Gilberton

Greenslade, Diana

369

Daily Rainfall Bulletin for Avon -Swan Bureau of Meteorology, Perth  

E-Print Network (OSTI)

.0 Ballidu 13 0.8 Kokardine 9.4 1.4 5.0 Kondut 13 0.8 5.2 Cadoux 9.2 3.4 0.4 Wongan Hills Research Stn Wongan Hills North AL* 0.0 0.0 9.0 2.4 0.2 0.2 4.6 0.2 Wongan Hills (DAFWA)* 0.0 13 5.6 1.0 0.0 Ejanding 10.0 2 0.2 3.8 0.2 Goomalling SYN 0.0 0.0 17 1.0 13 Long Forest AL* 0.0 0.0 22 1.0 11 0.0 5.6 0.2 Bolgart

Greenslade, Diana

370

From Nepal to JLab " One Scientist's Journey (Daily Press...  

NLE Websites -- All DOE Office Websites (Extended Search)

articles.dailypress.com2011-12-24newsdp-nws-evg-jlab-nepal-201112241tribhuvan-university-jefferson-lab-nepal... Submitted: Sunday, December 4, 2011...

371

Daily HMS Extremes in Met Data - Hanford Site  

NLE Websites -- All DOE Office Websites (Extended Search)

Mon Jan 12 00:04:15 PST 2015 For the day: Sun Jan 11 MAX MAX MIN Total Station Spd Time Temp Time Temp Time Precip 1 PROS 11.9 22:30 40.2 15:15 32.2 5:00 0.00 2 EOC 14.6 20:00 37.2...

372

Daily HMS Extremes in Met Data - Hanford Site  

NLE Websites -- All DOE Office Websites (Extended Search)

Thu Jan 08 00:04:15 PST 2015 For the day: Wed Jan 07 MAX MAX MIN Total Station Spd Time Temp Time Temp Time Precip 1 PROS 11.4 14:15 41.3 14:00 25.0 7:15 0.00 2 EOC 15.0 1:15 42.3...

373

Daily HMS Extremes in Met Data - Hanford Site  

NLE Websites -- All DOE Office Websites (Extended Search)

Wed Jan 14 00:04:15 PST 2015 For the day: Tue Jan 13 MAX MAX MIN Total Station Spd Time Temp Time Temp Time Precip 1 PROS 10.8 16:45 37.5 14:15 34.1 7:30 0.00 2 EOC 9.3 23:30 38.8...

374

Daily HMS Extremes in Met Data - Hanford Site  

NLE Websites -- All DOE Office Websites (Extended Search)

Fri Jan 09 00:04:21 PST 2015 For the day: Thu Jan 08 MAX MAX MIN Total Station Spd Time Temp Time Temp Time Precip 1 PROS 16.3 21:00 35.4 0:00 31.7 0:15 0.00 2 EOC 22.0 22:30 34.8...

375

Daily HMS Extremes in Met Data - Hanford Site  

NLE Websites -- All DOE Office Websites (Extended Search)

Tue Jan 13 00:04:15 PST 2015 For the day: Mon Jan 12 MAX MAX MIN Total Station Spd Time Temp Time Temp Time Precip 1 PROS 10.2 19:15 42.7 13:45 33.0 3:00 0.00 2 EOC 10.0 17:30 39.1...

376

honda.PDF  

NLE Websites -- All DOE Office Websites (Extended Search)

HONDA EV PLUS HONDA EV PLUS NIMH BATTERIES SEPTEMBER 1997 Urban Range (On Urban Pomona Loop - see other side for map) Range (mi.) Without Aux. Loads With Aux. Loads 81.7 97.7 105.3 Payload (lb.) Maximum 860 Minimum 140 UR1 UR2 UR 3 UR4 86.9 Test UR1 UR2 UR3 UR4 Payload (lb.) 140 140 860 860 AC kWh Recharge 40 43 40 45 AC kWh/mi. 0.38 0.49 0.41 0.55 Range (mi.) 105.3 86.9 97.7 81.7 Avg. Ambient Temp. 79° F 83° F 84° F 89° F State of Charge Meter (Urban Range Test) 0 20 40 60 80 100 120 0 1 2 3 4 5 6 7 8 9 State of Charge Miles Driven 0 20 40 60 80 100 120 140 Miles Remaining Miles Driven Miles Remaining Start End * * Initial " Miles Remaining" depend on driving economy before recharge Freeway Range (On Freeway Pomona Loop - see other side for map) Range (mi.) Without Aux. Loads With Aux. Loads 90.6 89.1 Maximum 860 Minimum

377

CHEVROLET S-10 ELECTRIC  

NLE Websites -- All DOE Office Websites (Extended Search)

January - February 2000 January - February 2000 Date Prepared: 3/24/2000 1997 GM EV1 (PANASONIC PB-A BATTERIES) PERFORMANCE CHARACTERIZATION SUMMARY ELECTRIC TRANSPORTATION DIVISION Urban Range (On Urban Pomona Loop - see other side for map) Payload (lb) 90.3 88.9 (mi.) Range Without Aux. loads With Aux. loads Maximum 447 Minimum 185 72.6 79.7 UR1 UR2 UR3 UR4 Test UR1 UR2 UR3 UR4 Payload (lb.) 185 185 447 447 AC kWh Recharge 26.91 26.61 27.69 22.80 AC kWh/mi. 0.296 0.331 0.311 0.312 Range (mi.) 90.3 79.7 88.9 72.6 Avg. Ambient Temp. 65°F 72°F 70°F 71°F UR1 Urban Range Test, Min Payload, No Auxiliary Loads UR2 Urban Range Test, Min Payload, A/C on High, Headlights on Low, Radio On UR3 Urban Range Test, Max Payload, No Auxiliary Loads UR4 Urban Range Test, Max Payload, A/C on High, Headlights on Low, Radio On State of Charge Meter (UR1)

378

Sheet.PDF  

NLE Websites -- All DOE Office Websites (Extended Search)

CHRYSLER EPIC (NIMH BATTERIES) PERFORMANCE CHARACTERIZATION SUMMARY CHRYSLER EPIC (NIMH BATTERIES) PERFORMANCE CHARACTERIZATION SUMMARY ELECTRIC TRANSPORTATION DIVISION Urban Range (On Urban Pomona Loop - see other side for map) Range (mi.) Weight (lb.) 160 930 Max. Payload Min. Payload 63.6 82.0 without aux. loads with aux. loads 77.6 67.8 Test UR1 UR2 UR3 UR4 Payload (lb.) 160 160 930 930 AC kWh Recharge 53.91 50.03 53.02 52.61 AC kWh/mi. 0.663 0.734 06.75 0.823 Range (mi.) 82.0 67.8 77.6 63.6 Avg. Ambient Temp. 75º F 80º F 79º F 85º F UR1 Urban Range Test, Min Payload, No Auxiliary Loads UR2 Urban Range Test, Min Payload, A/C on High, Headlights on Low, Radio On UR3 Urban Range Test, Max Payload, No Auxiliary Loads UR4 Urban Range Test, Max Payload, A/C on High, Headlights on Low, Radio On State of Charge Meter (UR1) SOC Meter Reading vs Miles Driven 0 10

379

Can Solar PV Rebates Be Funded with Utility Cost Savings?  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Jan Aceti Jan Aceti Concord Light February 19, 2013 Concord Municipal Light Plant Photo Credit: K.M. Peterson  7,600 Customers ◦ 6,000 Residential ◦ 1,600 Commercial/Institutional/Governmental  Retail Sales: 180,000,000 kWh per Year  Peak Electrical Demand: 40 MW  Power Purchased from Facilities in Northeast Year # of Installations kW DC kW AC 1999 1 5 5 2008 3 4.2 4.0 2009 5 75.0 74.6 2010 3 158 151 2011 7 36 35 2012 19 143 137 2013 2 8.2 7.7 Total 40 429 414 Residential 35 178 170  $1,000 per kW AC, up to $5,000  Retail Net Metering  Replaced Retail Net Metering with Wholesale Net Metering ◦ Credit at Avg. Monthly Spot Market Energy Price  Rebate: 10 Years Worth of Estimated Cost Savings, Up to 5 kW AC of Installed Capacity  Transmission Cost Savings  Forward Capacity Market Cost Savings

380

ford.PDF  

NLE Websites -- All DOE Office Websites (Extended Search)

FORD RANGER EV FORD RANGER EV LEAD ACID BATTERIES MARCH 1998 Urban Range (On Urban Pomona Loop - see other side for map) Range (mi.) Without Aux. Loads With Aux . Lo a ds Pay load ( lb.) Maximum 640 Minimum 140 UR1 UR2 UR3 UR4 58.3 58.7 60.1 72.1 Test UR1 UR2 UR3 UR4 Payload (lb.) 140 140 640 640 AC kWh Recharge 29.11 28.16 28.20 28.23 AC kWh/mi. 0.40 0.47 0.48 0.48 Range (mi.) 72.1 60.1 58.7 58.3 Avg. Ambient Temp. 79° F 61° F 69° F 64° F State of Charge Meter (Urban Range Test) 0 10 20 30 40 50 60 70 80 0 0.5 1 1.5 2 2.5 3 3.5 4 State of Charge (4=F, 0=E) Miles Driven Miles Driven Miles Remaining * * Initial "Miles Remaining" depend on driving economy before recharge Freeway Range (On Freeway Pomona Loop - see other side for map) Range (mi.) Without Aux. Loads With Au x . L o a ds 51.6 57.2 60 66.4

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Toyota_RAV4.PDF  

NLE Websites -- All DOE Office Websites (Extended Search)

1999 Inductive version tested. 1999 Inductive version tested. Test Date: June 1999 / Revised: 10/07/99 1999 TOYOTA RAV4-EV* (NIMH BATTERIES) PERFORMANCE CHARACTERIZATION SUMMARY ELECTRIC TRANSPORTATION DIVISION Urban Range (On Urban Pomona Loop - see other side for map) Payload (lb) 92.8 89.5 84.8 Range Without Aux. loads With Aux. loads Maximum 760 Minimum 160 UR1 UR2 UR3 UR4 68.9 Test UR1 UR2 UR3 UR4 Payload (lb.) 160 160 766 766 AC kWh Recharge 31.80 33.96 32.72 32.22 AC kWh/mi. 0.329 0.394 0.360 0.434 Range (mi.) 92.8 84.8 89.5 68.9 Avg. Ambient Temp. 68.5°F 75.3°F 80.0°F 87.0°F Note: A/C fluctuating and may have impacted A/C tests. UR1 Urban Range Test, Min Payload, No Auxiliary Loads UR2 Urban Range Test, Min Payload, A/C on High, Headlights on Low, Radio On UR3 Urban Range Test, Max Payload, No Auxiliary Loads UR4

382

T ti E St S tTetiaroa Energy Storage System Estimated ZBB Zinc Bromide Battery Performance and Costs  

E-Print Network (OSTI)

://rael.berkeley.edu 6Modeled 455kW gen set output power #12;Alte nati e Diesel Si ingAlternative Diesel Sizing://rael.berkeley.edu 1 #12;Island Load and DieselIsland Load and Diesel Generation Assumptions #12;Estimated Elect ical: Average daily energy use: 5,698 kWh d d 23 k Average power demand: 237 kW Peak power demand: 427 kW Load

Kammen, Daniel M.

383

Seagate Crystal Reports - RADCM  

Office of Environmental Management (EM)

Mexico Mexico SITE: LosAlamos PROGRAM: DP WASTE TYPE: Low Level Waste OPERATIONS OFFICE: Albuquerque Operations Office % of Stream LosAlamos - Low Level Waste - LLW-PCB WASTE STREAM CODE: 02015 STREAM NAME:LLW-PCB MPC NAME:Soil/Debris TOTAL CURIES: Approved Volume : Future Volume Avg: Future Volume Lower Limit: Future Volume Upper Limit: 100.000 LLW -PCB Isotopes Plutonium-239 Avg Concentration: Low Limit Concent: Upper Limit Concent:1.0000E+002 nCi/g Americium-241 Avg Concentration: Low Limit Concent: Upper Limit Concent:1.0000E+002 nCi/g Cesium-137 Avg Concentration: Low Limit Concent: Upper Limit Concent:8.6400E+002 nCi/g Uranium-238 Avg Concentration: Low Limit Concent: Upper Limit Concent:4.8900E+002 nCi/g Plutonium-238 Avg Concentration: Low Limit Concent: Upper Limit Concent:1.0000E+002 nCi/g

384

Seagate Crystal Reports - RADCM  

Office of Environmental Management (EM)

South Carolina South Carolina SITE: Savannah PROGRAM: DP WASTE TYPE: Low Level Waste OPERATIONS OFFICE: Savannah River Operations Office % of Stream Savannah - Low Level Waste - Intermediate Level Waste WASTE STREAM CODE: 00539 STREAM NAME:Intermediate Level Waste MPC NAME:Solids TOTAL CURIES: Approved Volume : Future Volume Avg: Future Volume Lower Limit: Future Volume Upper Limit: 100.000 Intermediate Level W aste Isotopes Nickel-59 Avg Concentration: Low Limit Concent: Upper Limit Concent:8.3000E-002 Ci/ft3 Uranium-234 Avg Concentration: Low Limit Concent: Upper Limit Concent:4.7000E-004 Ci/ft3 Carbon-14 Avg Concentration: Low Limit Concent: Upper Limit Concent:4.7000E-004 Ci/ft3 Hydrogen-3 Avg Concentration: Low Limit Concent: Upper Limit Concent:3.0000E+001 Ci/ft3 Technetium-99 Avg Concentration: Low Limit Concent:

385

Seagate Crystal Reports - RADCM  

Office of Environmental Management (EM)

Colorado Colorado SITE: GrJuncOff PROGRAM: EM WASTE TYPE: 11e(2) Byproduct Waste OPERATIONS OFFICE: Idaho Operations Office % of Stream GrJuncOff - 11e(2) Byproduct Waste - RRM Contaminated Soil WASTE STREAM CODE: 01091 STREAM NAME:RRM Contaminated Soil MPC NAME:Soil TOTAL CURIES: Approved Volume : 30.000 Future Volume Avg: 0.000 Future Volume Lower Limit: Future Volume Upper Limit: 100.000 RRM Contaminated Soil Isotopes Radium-226 Avg Concentration: Low Limit Concent: Upper Limit Concent: Uranium-234 Avg Concentration: Low Limit Concent: Upper Limit Concent: Uranium-238 Avg Concentration: Low Limit Concent: Upper Limit Concent: Thorium-230 Avg Concentration: Low Limit Concent: Upper Limit Concent: Uranium-235 Avg Concentration: Low Limit Concent: Upper Limit Concent: % of Stream GrJuncOff - 11e(2) Byproduct Waste - RRM Contaminated Rubble/Debris

386

Seagate Crystal Reports - RADCM  

Office of Environmental Management (EM)

Cs/Sr Capsules Cs/Sr Capsules WASTE STREAM CODE: 02115 STREAM NAME:Cs/Sr Capsules MPC NAME:Salt Waste TOTAL CURIES: Approved Volume : Future Volume Avg: Future Volume Lower Limit: Future Volume Upper Limit: 100.000 Cs/Sr Capsules Isotopes Barium-137m Avg Concentration: 2.5941E+007 Ci/m3 Low Limit Concent: Upper Limit Concent: Cesium-137 Avg Concentration: 2.7391E+007 Ci/m3 Low Limit Concent: Upper Limit Concent: Yttrium-90 Avg Concentration: 1.1840E+007 Ci/m3 Low Limit Concent: Upper Limit Concent: Strontium-90 Avg Concentration: 1.1840E+007 Ci/m3 Low Limit Concent: Upper Limit Concent: % of Stream Hanford - High Level Waste - HLW to Treatment WASTE STREAM CODE: 03857 STREAM NAME:HLW to Treatment MPC NAME:Aqueous Liquids/Slurries TOTAL CURIES: Approved Volume : Future Volume Avg: Future Volume Lower Limit:

387

Algorithms for processing ultrasonic echo data for height control systems  

E-Print Network (OSTI)

estimation was affected by the value of the weighting factor (M) in equation (1). The accuracy of this stubble height estimation was evaluated by using the Student's t test technique. ESTH(n) = AVS(n) ? AVG(n) (3) Computer program: A FORTRAN program... YES IS HTs'P READ AVS & AVG, STALK AND GROUND AVERAGES r---- RAISE BLADES t, READ THD OR THH & THL, SINGLE THRESHOLD OR GET NEW SAMPLE ECHO ECHO DISCRIMINATION GROUND STALK OR GROUND ? STALK AVS ~AVS + Y(I)-AVS n n-I AVG =AVG Y...

Lin, Reng Rong

2012-06-07T23:59:59.000Z

388

1  

NLE Websites -- All DOE Office Websites (Extended Search)

Instrument Measurement Manufacturer Sampling Rate (interval) Accuracy HeightRange Thermometer Temperature Vaisala 1 min. avgs. (1 sec) 0.41C 2 m RH Sensor Relative humidity...

389

Conservation screening curves to compare efficiency investments to power plants: Applications to commercial sector conservation programs  

E-Print Network (OSTI)

7/kWh Gas Turbine 5/kWh Combined-Cycle Oil Baseload Coal7/kWh Gas Turbine 5/kWh Combined-Cycle Oi Baseload Coalof Supply Technologies CT Combined- Cycle Oil Baseload Coal

Koomey, Jonathan; Rosenfeld, Arthur H.; Gadgil, Ashok J.

2008-01-01T23:59:59.000Z

390

January 2011 Strategic Planning Session  

E-Print Network (OSTI)

Maintenance work requests .1.2 All FM Units Achieve Customer Satisfaction of 85% 85% 85.0% Annual 4.1.3 Reduce: Maintenance & Ops.1.5 Maint Cost/GSF +/ 5% of APPA Avg for Peer Inst +/5% 6.1.6 Landscape Cost/GSF +/5% of APPA Avg for Peer

Howitt, Ivan

391

January 2013 Strategic Planning Session  

E-Print Network (OSTI)

Process 1.3.1 Reactive Maintenance work requests rating 85% 4.1.2 All FM Units Achieve Customer Satisfaction of 85% 85% 4.1.3 Reduce: Maintenance & Ops% of APPA Avg for Peer Inst "+/-5%" 6.1.6 Landscape Cost/GSF +/-5% of APPA Avg for Peer Inst "+/-5%" 6

Howitt, Ivan

392

April 2010 Strategic Planning Session  

E-Print Network (OSTI)

satisfaction 4.1.3 Reduce: Maintenance & Ops # hot/cold calls 15% or /GSF +/ 5% of APPA Avg for Peer Inst +/5% ? Annual Annual 6.1.6 Landscape Cost/GSF +/5% of APPA Avg for Peer Request Process 1.3.1 Reactive Maintenance work requests

Howitt, Ivan

393

PERIODIC HEAT REPORT  

NLE Websites -- All DOE Office Websites (Extended Search)

186.00 TripHigh tc Date MO:DAY 1.00: 16.00 TripHigh tc Time HR:MIN 10.00: 9.00 Ports Temp: Avg, High, Low 19.00, 21.00, 17.00 Coils Temp: Avg, High, Low 19.00, 21.00,...

394

Gradient-Based Distance Estimation for Spatial Computers  

Science Journals Connector (OSTI)

......the reduced width area, the average gradient value Gout avg and the SMG value Gout si are shown using Equation (12) and (13). If...Gin si as shown using Equation (14) and (15). Gout avg = nl (a - 1) + nl a + nl (a + 1) nl = a......

Qingzhi Liu; Andrei Pruteanu; Stefan Dulman

2013-12-01T23:59:59.000Z

395

Seagate Crystal Reports - Radcm  

Office of Environmental Management (EM)

Dry Active Waste Dry Active Waste WASTE STREAM CODE: 01585 STREAM NAME:Dry Active Waste MPC NAME:Solids TOTAL CURIES: 87,675.000 Approved Volume : Future Volume Avg: Future Volume Lower Limit: Future Volume Upper Limit: 100.000 Dry Active W aste Isotopes Hafnium-181 Avg Concentration: 1.4222E-007 Ci/m3 Low Limit Concent: Upper Limit Concent: Iridium-192 Avg Concentration: 1.2220E-003 Ci/m3 Low Limit Concent: Upper Limit Concent: Molybdenum-99 Avg Concentration: 3.6706E-008 Ci/m3 Low Limit Concent: Upper Limit Concent: Protactinium-234m Avg Concentration: 5.1907E-009 Ci/m3 Low Limit Concent: Upper Limit Concent: Lead-212 Avg Concentration: 1.6569E-009 Ci/m3 Low Limit Concent: Upper Limit Concent: Silver-111 Avg Concentration: 3.2355E-007 Ci/m3 Low Limit Concent: Upper Limit Concent: Arsenic-73 Avg Concentration: 1.4091E-010 Ci/m3

396

Category:Properties | Open Energy Information  

Open Energy Info (EERE)

Category Category Edit History Facebook icon Twitter icon » Category:Properties Jump to: navigation, search This category uses the form Property. Subcategories This category has only the following subcategory. T [×] Tech Potential Properties‎ 30 pages Pages in category "Properties" The following 200 pages are in this category, out of 1,075 total. (previous 200) (next 200) A Property:Abbreviation Property:Achievement Date Property:AdditionalRef Property:Affiliated Companies Property:Applicant Property:Area Property:AreaGeology Property:Author Property:Available Personnel Types Property:Available Sensors Property:AvgAnnlGrossOpCpcty Property:AvgGeoFluidTemp Property:AvgReservoirDepth Property:AvgTempGeoFluidIntoPlant Property:AvgWellDepth B Property:Bandwidth(kHz)

397

Using ''waste'' heat to conserve energy  

SciTech Connect

The organic Rankine cycle diesel bottoming system (DRCDBS) is being tested at the Naval Air Station in Bermuda for viability in operational use. The system uses heat recovered from the exhaust gases of diesel/generator sets to power a turbine/generator unit. The system will be demonstrated for three years before operational use. A schematic for the system is given. Its daily KWh hours performance is calculated. Logistic support--maintainence and training--are also treated. Potential sites are being studied.

Cooper, E.

1983-04-01T23:59:59.000Z

398

Data:25cd644a-4e90-44a7-8ca4-8181c316483d | Open Energy Information  

Open Energy Info (EERE)

44a-4e90-44a7-8ca4-8181c316483d 44a-4e90-44a7-8ca4-8181c316483d No revision has been approved for this page. It is currently under review by our subject matter experts. Jump to: navigation, search Loading... 1. Basic Information 2. Demand 3. Energy << Previous 1 2 3 Next >> Basic Information Utility name: North Central Public Pwr Dist Effective date: 2012/01/01 End date if known: Rate name: 32- Irrigation- 5 Hours Daily Control & Sunday control Sector: Commercial Description: demand= 50/.786=67.02 Source or reference: http://www.ncppd.com/rates.pdf Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service Voltage Minimum (V): Maximum (V): Character of Service Voltage Category: Phase Wiring:

399

Data:646b1bed-b381-4ca8-b0a0-0f1f75feb89f | Open Energy Information  

Open Energy Info (EERE)

b1bed-b381-4ca8-b0a0-0f1f75feb89f b1bed-b381-4ca8-b0a0-0f1f75feb89f No revision has been approved for this page. It is currently under review by our subject matter experts. Jump to: navigation, search Loading... 1. Basic Information 2. Demand 3. Energy << Previous 1 2 3 Next >> Basic Information Utility name: Lincoln Electric System Effective date: End date if known: Rate name: Large Light and Power Off-Peak Seasonal Dual Daily Primary Sector: Description: Excess kVA Source or reference: http://www.les.com/your_business/rate_schedules_llp.aspx Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service Voltage Minimum (V): Maximum (V): Character of Service Voltage Category: Phase Wiring: << Previous

400

Data:15fb8a46-8c86-4227-99f4-8f4ac7c61c7f | Open Energy Information  

Open Energy Info (EERE)

fb8a46-8c86-4227-99f4-8f4ac7c61c7f fb8a46-8c86-4227-99f4-8f4ac7c61c7f No revision has been approved for this page. It is currently under review by our subject matter experts. Jump to: navigation, search Loading... 1. Basic Information 2. Demand 3. Energy << Previous 1 2 3 Next >> Basic Information Utility name: Lincoln Electric System Effective date: End date if known: Rate name: Large Light and Power Off-Peak Seasonal Daily Primary Sector: Description: Excess kVA Source or reference: http://www.les.com/your_business/rate_schedules_llp.aspx Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service Voltage Minimum (V): Maximum (V): Character of Service Voltage Category: Phase Wiring: << Previous

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Data:Cc6ca81f-16a5-4da4-b4c8-89ae1682b0f2 | Open Energy Information  

Open Energy Info (EERE)

f-16a5-4da4-b4c8-89ae1682b0f2 f-16a5-4da4-b4c8-89ae1682b0f2 No revision has been approved for this page. It is currently under review by our subject matter experts. Jump to: navigation, search Loading... 1. Basic Information 2. Demand 3. Energy << Previous 1 2 3 Next >> Basic Information Utility name: Butler Public Power District Effective date: 2013/01/01 End date if known: Rate name: Irrigation Services Rate 45 daily control Sector: Industrial Description: Source or reference: http://www.butlerppd.com/common/New%20Customer%20Packet%20_1.2013.pdf Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service Voltage Minimum (V): Maximum (V): Character of Service Voltage Category: Phase Wiring:

402

Seagate Crystal Reports - RADCM  

Office of Environmental Management (EM)

Packaged Low-level Waste from SNF Activities Packaged Low-level Waste from SNF Activities WASTE STREAM CODE: 00265 STREAM NAME:Packaged Low-level Waste from SNF Activities MPC NAME:Solids TOTAL CURIES: 2.900 Approved Volume : 0.000 Future Volume Avg: 18.500 Future Volume Lower Limit: Future Volume Upper Limit: 100.000 Hot Cell W aste Isotopes Strontium-90 Avg Concentration: 1.5800E+000 Ci/m3 Low Limit Concent: Upper Limit Concent: Curium-244 Avg Concentration: 9.1700E-002 Ci/m3 Low Limit Concent: Upper Limit Concent: Europium-152 Avg Concentration: 4.6400E-001 Ci/m3 Low Limit Concent: Upper Limit Concent: Plutonium-238 Avg Concentration: 2.4100E-002 Ci/m3 Low Limit Concent: Upper Limit Concent: Europium-154 Avg Concentration: 4.0100E-001 Ci/m3 Low Limit Concent: Upper Limit Concent: Plutonium-240 Avg Concentration: 8.4500E-003 Ci/m3

403

Optimizing and Diversifying the Electric Range of Plug-in Hybrid Electric Vehicles for U.S. Drivers  

SciTech Connect

To provide useful information for automakers to design successful plug-in hybrid electric vehicle (PHEV) products and for energy and environmental analysts to understand the social impact of PHEVs, this paper addresses the question of how many of the U.S. consumers, if buying a PHEV, would prefer what electric ranges. The Market-oriented Optimal Range for PHEV (MOR-PHEV) model is developed to optimize the PHEV electric range for each of 36,664 sampled individuals representing U.S. new vehicle drivers. The optimization objective is the minimization of the sum of costs on battery, gasoline, electricity and refueling hassle. Assuming no battery subsidy, the empirical results suggest that: 1) the optimal PHEV electric range approximates two thirds of one s typical daily driving distance in the near term, defined as $450/kWh battery delivered price and $4/gallon gasoline price. 2) PHEVs are not ready to directly compete with HEVs at today s situation, defined by the $600/kWh battery delivered price and the $3-$4/gallon gasoline price, but can do so in the near term. 3) PHEV10s will be favored by the market over longer-range PHEVs in the near term, but longer-range PHEVs can dominate the PHEV market if gasoline prices reach as high as $5-$6 per gallon and/or battery delivered prices reach as low as $150-$300/kWh. 4) PHEVs can become much more attractive against HEVs in the near term if the electric range can be extended by only 10% with multiple charges per day, possible with improved charging infrastructure or adapted charging behavior. 5) the impact of a $100/kWh decrease in battery delivered prices on the competiveness of PHEVs against HEVs can be offset by about $1.25/gallon decrease in gasoline prices, or about 7/kWh increase in electricity prices. This also means that the impact of a $1/gallon decrease in gasoline prices can be offset by about 5/kWh decrease in electricity prices.

Lin, Zhenhong [ORNL

2012-01-01T23:59:59.000Z

404

Phase I clinical and pharmacokinetic study of carzelesin (U-80244) given daily for five consecutive days.  

Science Journals Connector (OSTI)

...Carzelesin (U-80244), one of the synthetic DNA minor groove binding cyclopropylpyrroloindole...Carzelesin (U-80244), one of the synthetic DNA minor groove binding cyclopropylpyrroloindole...Carzelesin (U-80244), one of the synthetic DNA minor groove binding cyclopropylpyrroboindole...

I Wolff; K Bench; J H Beijnen; U Bruntsch; F Cavalli; J de Jong; Y Groot; O van Tellingen; J Wanders; C Sessa

1996-10-01T23:59:59.000Z

405

A Comparison of Nicotine Biomarkers and Smoking Patterns in Daily and Nondaily Smokers  

Science Journals Connector (OSTI)

...Control and Prevention [Internet].Behavioral Risk Factor...1221-6. 5. Substance Abuse and Mental Health Services Administration [Internet]. Rockville (MD...on Alcoholism and Drug Abuse DHHS Publications; 1985...multiethnic national sample of young adults.Am J Epidemiol...

Saul Shiffman; Michael S. Dunbar; and Neal L. Benowitz

2014-07-01T23:59:59.000Z

406

A Comparison of Nicotine Biomarkers and Smoking Patterns in Daily and Nondaily Smokers  

Science Journals Connector (OSTI)

...Control and Prevention [Internet].Behavioral Risk Factor...1221-6. 5. Substance Abuse and Mental Health Services Administration [Internet]. Rockville (MD): Results...Institute on Alcoholism and Drug Abuse DHHS Publications; 1985...

Saul Shiffman; Michael S. Dunbar; and Neal L. Benowitz

2014-07-01T23:59:59.000Z

407

Noisy clocks and silent sunrises: measurement methods of daily activity pattern  

E-Print Network (OSTI)

intensity or ambient temperature and thus of the sun's position in the sky: time of sunrise, zenith; distribution of activity. Correspondence Pierre Nouvellet. Current address: Biology and Environmental Science with the actual position of the sun. To demonstrate the important difference between these methods of analysis, we

Courchamp, Franck

408

Association of weather and air pollution interactions on daily mortality in 12 Canadian cities  

Science Journals Connector (OSTI)

It has been well established that both meteorological attributes and air pollution concentrations affect human health outcomes. We examined ... 28years (19812008) in relation to air pollution and synoptic weath...

J. K. Vanos; S. Cakmak; L. S. Kalkstein

2014-05-01T23:59:59.000Z

409

JLab Nanotube Research Leads To Newport News Start-Up (Daily...  

NLE Websites -- All DOE Office Websites (Extended Search)

articles.dailypress.com2012-08-03newsdp-nws-cp-jefferson-lab-spinoff-201208031nanotubes-jefferson-lab-free-e... Submitted: Thursday, August 2...

410

EIA - Daily Report 10/24/05 - Hurricane Impacts on U.S. Oil ...  

U.S. Energy Information Administration (EIA) Indexed Site

bbld as of October 21, 2005. Please consult the Office of Electricity Delivery and Energy Reliability's Situation Report for specific information on the refineries. Natural Gas...

411

EIA - Daily Report 9/14/05 - Hurricane Katrina's Impact on U...  

U.S. Energy Information Administration (EIA) Indexed Site

(which had been 10 billion cubic feet per day). EIA released its monthly Short-Term Energy Outlook on Wednesday, September 7, taking into consideration three Hurricane Katrina...

412

EIA - Daily Report 9/30/05 - Hurricane Impacts on U.S. Oil &...  

U.S. Energy Information Administration (EIA) Indexed Site

refineries remain shutdown. Please consult the Office of Electricity Delivery and Energy Reliability's Situation Report for specific information on the refineries. Natural Gas...

413

EIA - Daily Report 9/29/05 - Hurricane Impacts on U.S. Oil &...  

U.S. Energy Information Administration (EIA) Indexed Site

refineries remain shutdown. Please consult the Office of Electricity Delivery and Energy Reliability's Situation Report for specific information on the refineries. Natural Gas...

414

Statistical Modeling of Daily Energy Consumption in Commercial Buildings Using Multiple Regression and Principal Component Analysis  

E-Print Network (OSTI)

, for example Jolliffer, 1986; Van Rijckevorsel and de Leeuw, 1988; FlUry, 1988; Jackson, 1991; Daultrey, 1976) is a statistical technique useful for describing and summarizing data. It takes a group of "n" variables and re-expresses them as another set... if T and RH are known (Zaikong et al., 1985); (5) solar radiation SOL; and, (6) wind speed WIND. Weather independent variables include: (l) time schedules: regular (weekdays, weekends, holidays) and stochastic; (2) lighting loads; (3) occupant loads...

Reddy, T. A.; Claridge, D.; Wu, J.

415

Question of the Week: What Is Your Daily Commute Like? | Department...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Most made it to work in 25 minutes or less. Whether you drive, walk, take the bus or train, or roll out of bed and stumble into your home office, how you get to work and the...

416

Assessing Maturity in Sweet Sorghum Hybrids and its Role in Daily Biomass Supply  

E-Print Network (OSTI)

in ___________ This thesis follows the style of Crop Science. 2 feed and food grain markets. Finally, perceived concerns over fuel versus food will continue to affect policy and production practices (Hoekman, 2009). Because our biofuel needs cannot be met... by starch-derived ethanol alone, ligno- cellulosic biomass sources will also be required (Heaton et al., 2008). There are many potential ligno-cellulosic biomass sources ranging from crop and wood residue to dedicated bioenergy crops grown specifically...

Burks, Payne

2012-07-16T23:59:59.000Z

417

E-Print Network 3.0 - adolescent daily smoking Sample Search...  

NLE Websites -- All DOE Office Websites (Extended Search)

used to test predictions from life history... of adolescent and young adult life history strategies, and (3) adolescent life history traits would ... Source: Gorman, Michael -...

418

The level crossing analysis of German stock market index (DAX) and daily oil price time series  

E-Print Network (OSTI)

The level crossing analysis of DAX and oil price time series are given. We determine the average frequency of positive-slope crossings, $\

Shayeganfar, F; Peinke, J; Tabar, M Reza Rahimi

2010-01-01T23:59:59.000Z

419

GSOD Based Daily Global Mean Surface Temperature and Mean Sea Level Air Pressure (1982-2011)  

DOE Data Explorer (OSTI)

This data product contains all the gridded data set at 1/4 degree resolution in ASCII format. Both mean temperature and mean sea level air pressure data are available. It also contains the GSOD data (1982-2011) from NOAA site, contains station number, location, temperature and pressures (sea level and station level). The data package also contains information related to the data processing methods

Xuan Shi, Dali Wang

420

From daily movements to population distributions: weather affects competitive ability in a guild of soaring birds  

Science Journals Connector (OSTI)

...1250, 8400 Bariloche, Argentina The ability of many animals...cost of transport|energy landscape|competition...and RG White. 1987 Energy expenditures for locomotion...and RP Wilson. 2011 Energy beyond food: foraging...bird from the Miocene of Argentina. Proc. Natl Acad...

2013-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Daily forecasts of Columbia River plume circulation: a tale of spring/summer cruises  

E-Print Network (OSTI)

Science Foundation (OCE-0424602; OCE-0622278), Bonneville Power Administration, and National Oceanic and Atmospheric Administration (AB133F04CN0033) Submitted to JGR on July 11, 2008 1 Corresponding author; e

Jay, David

422

Source Apportionment of Daily Fine Particulate Matter at Jefferson Street, Atlanta, GA, during Summer and Winter  

E-Print Network (OSTI)

, especially wood burning, as well as vehicular exhaust, and suggest that secondary aerosol for- mation dominates in summer in Atlanta. TECHNICAL PAPER ISSN 1047-3289 J. Air & Waste Manage. Assoc. 57:228­242 Copyright 2007 Air & Waste Management Association 228 Journal of the Air & Waste Management Association

Zheng, Mei

423

Optimization of an artificial neural network dedicated to the multivariate forecasting of daily global radiation  

E-Print Network (OSTI)

wall power (MJ) kk Estimation of partial autocorrelations for time lag k PV Plant efficiency (%) R Networks, PV Plant, Energy Prediction, Stationarity *Corresponding author: Marc,MUSELLI, tél: +33 4 95 52 S Surface of PV wall [m²] x Parameter to optimize PR Performance ratio of the PV plant J Jacobian matrix hal

Paris-Sud XI, Université de

424

Thememory: Experiencing Thematic Photos in Daily Practice Kai-Yin Cheng  

E-Print Network (OSTI)

keynes@cmlab.csie.ntu.edu.tw Ko-Yuan Chou National Taiwan University koyuan@cmlab.csie.ntu.edu.tw Bing-Yu Chen National Taiwan University robin@ntu.edu.tw Figure 1. Interaction with the Thememory. (a Effect (template dependent) Photos X Theme Templates Progressive Reminder Preprocessing Theme

Ouhyoung, Ming

425

ANALYZING THE WIDTH OF DAILY OTOLITH INCREMENTS TO AGE THE HAWAIIAN SNAPPER, PRISTIPOMOIDES FlLAMENTOSUS  

E-Print Network (OSTI)

and extended his findings to a wide variety of temperate and tropical species in both marine and freshwater.1983 tleman 1967; Degens et a1. 1969), yet their temporal significance was unappreciated at the time. Weare

426

Modelling the convenience yield in carbon prices using daily and realized measures  

E-Print Network (OSTI)

for carbon spot and futures prices, which are exchanged since 2005 on the European Union Emissions Trading Scheme (EU ETS). The EU emissions trading system has been created by the Directive 2003/87/CE. Across 27

Paris-Sud XI, Université de

427

GSOD Based Daily Global Mean Surface Temperature and Mean Sea Level Air Pressure (1982-2011)  

SciTech Connect

This data product contains all the gridded data set at 1/4 degree resolution in ASCII format. Both mean temperature and mean sea level air pressure data are available. It also contains the GSOD data (1982-2011) from NOAA site, contains station number, location, temperature and pressures (sea level and station level). The data package also contains information related to the data processing methods

Xuan Shi, Dali Wang

2014-05-05T23:59:59.000Z

428

Daily life of the ancient Maya recorded on murals at Calakmul, Mexico  

Science Journals Connector (OSTI)

...paints formed a durable bond with the plaster surface similar in its effect to mezzo fresco. To consolidate the pictorial surface, calcium hydroxide...calcium hydroxide Ca(OH) 2 ] into plaster (calcium carbonate CaCO 3 ) (9...

Ramn Carrasco Vargas; Vernica A. Vzquez Lpez; Simon Martin

2009-01-01T23:59:59.000Z

429

Space Physics In our daily environment, we encounter matter in three  

E-Print Network (OSTI)

, liquid, and gas. In space, a fourth state of matter exists: the plasma state. Plasma is like a gas. Plasmas make up 99% of the material in the Universe. It is important to understand the natural physical transport and conversion in space plasmas Space Weather Prediction In today's technologically driven world

Mojzsis, Stephen J.

430

Daily/Hourly Hydrosystem Operation : How the Columbia River System Responds to Short-Term Needs.  

SciTech Connect

The System Operation Review, being conducted by the Bonneville Power Administration, the US Army Corps of Engineers, and the US Bureau of Reclamation, is analyzing current and potential future operations of the Columbia River System. One goal of the System Operations Review is to develop a new System Operation Strategy. The strategy will be designed to balance the many regionally and nationally important uses of the Columbia River system. Short-term operations address the dynamics that affect the Northwest hydro system and its multiple uses. Demands for electrical power and natural streamflows change constantly and thus are not precisely predictable. Other uses of the hydro system have constantly changing needs, too, many of which can interfere with other uses. Project operators must address various river needs, physical limitations, weather, and streamflow conditions while maintaining the stability of the electric system and keeping your lights on. It takes staffing around the clock to manage the hour-to-hour changes that occur and the challenges that face project operators all the time.

Columbia River System Operation Review (U.S.)

1994-02-01T23:59:59.000Z

431

Hypocholesterolemic effect of daily fisetin supplementation in high fat fed SpragueDawley rats  

Science Journals Connector (OSTI)

Abstract We aimed to test whether fisetin could modulate cholesterol homeostasis in rats with diet-induced hypercholesterolemia, and further investigated the underlying mechanisms by which fisetin exerts its cholesterol lowering effect. Blood lipid profile, hepatic cholesterol content, as well as gene expressions in cholesterol metabolism were examined. Elevated levels of total cholesterol and LDL-cholesterol, along with hepatic cholesterol content in a high fat group were found to be significantly reduced by fisetin. The high fat diet significantly decreased hepatic mRNA levels of LDLR, SREBP2, HMGCR and PCSK9 in comparison to the control diet, however, fisetin did not further elicit any changes in mRNA levels of the same genes. The high fat diet dramatically increased the transcript levels of CYP7A1, which was subsequently reversed by the fisetin. In HepG2 cells, fisetin was found to increase the levels of a nuclear form of SREBP2 and LDLR. In conclusion, fisetin supplementation displayed hypocholesterolemic effects by modulating the expression of genes associated with cholesterol and bile acid metabolism.

Min-Jeong Shin; Yoonsu Cho; Jiyoung Moon; Hyun Ju Jeon; Seung-Min Lee; Ji Hyung Chung

2013-01-01T23:59:59.000Z

432

INTRODUCTION More than 28 million children receive meals daily in almost all of the  

E-Print Network (OSTI)

. 1. FDA Food Code. 2009. U. S. Department of Health and Human Services. Available online: http://www Food Service Management Institute (NFSMI). 2005. Beef or Pork Taco. USDA Recipes for Child Nutrition to foodborne illnesses include food from unsafe sources, inadequate cooking, improper food storage and holding

Heller, Barbara

433

Feasibility of compressed air energy storage to store wind on monthly and daily basis.  

E-Print Network (OSTI)

??The storage volumes are often limited in terms of availability. Since volume is expensive, optimizing its use is very important to make reasonable net earnings. (more)

Riaz, Muhammad Ali

2010-01-01T23:59:59.000Z

434

Manual on Conditional Reliability, Daily Time Step, Flood Control, and Salinity Features of WRAP (Draft)  

E-Print Network (OSTI)

SALT Input Files root2.SIN required salinity input file with concentrations or loads of entering flows root2.DAT required main SIM/SIMD input file from which CP records are read root2.OUT required main SIM/SIMD output file with simulation results...

Wurbs, Ralph

435

Phase I Clinical and Pharmacokinetic Study of Trimetrexate Using a Daily 5 Schedule  

Science Journals Connector (OSTI)

...peaks were integrated using a Spectra-Physics 4200 computing system. Samples were prepared...TRIMETREXATE ing that prior TMTX treatment does not result in alteration of the drug's...Biopharm. 4:443-467, 1976. 18. WHO Handbook for Reporting Results of Cancer Treatment...

James A. Stewart; John J. McCormack; William Tong; Jane B. Low; John D. Roberts; Alton Blow; Lloyd R. Whitfield; Larry D. Haugh; William R. Grove; Antonio J. Grillo Lopez; and Robert J. DeLap

1988-09-01T23:59:59.000Z

436

School of Health and Related Research Daily Shut-down Checklist  

E-Print Network (OSTI)

: Lights in public areas such as stair wells and the lift lobby mustNOT be switched off. 5. Christmas) · Turn off all office lights (including ceiling and desk lights) · Turn off any other electrical the day in shared areas (e.g. coffee machine, microwave) · Turn off lights in all shared areas (including

Oakley, Jeremy

437

Decomposing CAD Models of Objects of Daily Use and Reasoning about their Functional Parts  

E-Print Network (OSTI)

manipulation tasks to identify abstract concepts like a "handle" or the "blade of a spatula" and to ground them into the robot's knowledge base as procedural attachments to the semantic representation. Bottom- up segmentation, at the end of a handle" and a bottle2 as "a rigid container with a neck that is narrower than the body

438

Using Utility Bills and Average Daily Energy Consumption to Target Commissioning Efforts and Track Building Performance  

E-Print Network (OSTI)

energy. This sort of analysis can be done using relatively simple techniques such as a hand calculation or a spreadsheet and is the type of thing that any facility engineer or operator could handle and would be interested in. Techniques are also discussed...

Sellers, D.

2001-01-01T23:59:59.000Z

439

The Daily Camera: Environment Home | News | Sports | Buffzone | Business | Opinion | Entertainment | Lifestyles | Recreation | Community  

E-Print Network (OSTI)

plants and global wildfires caused by the giant collision -- and not because of ancient volcanic eruptions or climate change, according to a new study by scientists in Colorado, Pennsylvania and Washington

Wilf, Peter

440

Trends in Daily Temperature and Precipitation Extremes for the Southeastern United States: 1948-2012  

Science Journals Connector (OSTI)

Spatial and temporal trends in temperature and precipitation extremes were investigated for the period 1948 to 2012 across the southeastern United States using 27 previously defined indices. Results show that region-wide warming in extreme minimum ...

Emily J. Powell; Barry D. Keim

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Daily uranium excretion in German peacekeeping personnel serving on the Balkans compared to ICRP model prediction  

Science Journals Connector (OSTI)

......assess a possible health risk of depleted uranium (DU) for residents...119-122. 10 WHO. Depleted uranium: Sources, exposure and health effects. (2001...assess a possible health risk of depleted uranium (DU) for residents......

U. Oeh; W. B. Li; V. Hllriegl; A. Giussani; P. Schramel; P. Roth; H. G. Paretzke

2007-11-01T23:59:59.000Z

442

Subscribe to the Tech Law Journal Daily E-Mail Alert  

E-Print Network (OSTI)

, and Utility Consumers' Action Network. James M. Carr, Office of General Counsel, Washington, D.C., for amicus. Portland, 6/22/00. 9/14/2007mhtml:file://C:\\CMU\\LawCourse2007\\readings\\Interpretation\\Document Appeals. Opinion by Judge Thomas COUNSEL David W. Carpenter (argued), Sidley & Austin, Chicago, Illinois

Shamos, Michael I.

443

From daily movements to population distributions: weather affects competitive ability in a guild of soaring birds  

Science Journals Connector (OSTI)

...model-observation hybrid data [33]. Values...was predicted by wind velocity, w...contrast to terrestrial systems, fluid media are...an increase in wind strength will reduce...as the increased solar radiation, cooler...Furthermore, when wind strength increases...

2013-01-01T23:59:59.000Z

444

Heavy Daily Precipitation Frequency over the Contiguous United States: Sources of Climatic Variability and Seasonal Predictability  

Science Journals Connector (OSTI)

By matching large-scale patterns in climate fields with patterns in observed station precipitation, this work explores seasonal predictability of precipitation in the contiguous United States for all seasons. Although it is shown that total ...

Alexander Gershunov; Daniel R. Cayan

2003-08-01T23:59:59.000Z

445

Reconstruction of a Daily Large-Pan Evaporation Dataset over China  

Science Journals Connector (OSTI)

Land surface evaporation is an important component of the earths surface hydrological cycle, as well as in the atmospheric energy and water balances. In China, different instruments have been used over time to measure evaporation. A small pan ...

An-Yuan Xiong; Jie Liao; Bin Xu

2012-07-01T23:59:59.000Z

446

Forecasting of Remotely Sensed Daily Evapotranspiration Data Over Nile Delta Region, Egypt  

Science Journals Connector (OSTI)

The impacts of higher temperatures and higher evapotranspiration values, lead to increased demands of agricultural water uses in Egypt and is an additional factor for the ... crop water use and increases in other...

Aris Psilovikos; Mohamed Elhag

2013-09-01T23:59:59.000Z

447

Daily pollution forecast using optimal meteorological data at synoptic and local scales  

E-Print Network (OSTI)

We present a simple framework to easily pre-select the most essential data for accurately forecasting the concentration of the pollutant PM$_{10}$, based on pollutants observations for the years 2002 until 2006 in the metropolitan region of Lisbon, Portugal. Starting from a broad panoply of different data sets collected at several meteorological stations, we apply a forward stepwise regression procedure that enables us not only to identify the most important variables for forecasting the pollutant but also to rank them in order of importance. We argue the importance of this variable ranking, showing that the ranking is very sensitive to the urban spot where measurements are taken. Having this pre-selection, we then present the potential of linear and non-linear neural network models when applied to the concentration of pollutant PM$_{10}$. Similarly to previous studies for other pollutants, our validation results show that non-linear models in average perform as well or worse as linear models for PM$_{10}$. F...

Russo, Ana; Raischel, Frank; Trigo, Ricardo; Mendes, Manuel

2014-01-01T23:59:59.000Z

448

Daily Reporting Rainfall Station MULGRAVE-RUSSELL RIVERS Manual Heavy Rainfall Station  

E-Print Network (OSTI)

Station Telemetry Rainfall Station Telemetry River Station Revised: Nov 2011 MAP 111.1 FLOOD WARNING ulgraveR The Boulders TM RussellR Clyde Rd AL Babinda Bucklands TM Daradgee McAvoy Br AL 0 5 10 kilometres

Greenslade, Diana

449

Tyrosine Transaminase: Development of Daily Rhythm in Liver of Neonatal Rat  

Science Journals Connector (OSTI)

...Present address: U.S. Geological Survey, Water Resources Division, Tallahassee, Flor-ida 32304. 18 September 1968 Female CFE rats (Carworth) were obtained during the second week of pregnancy. During gestation and at all times thereafter, the animals...

Eva Honova; Sanford A. Miller; Richard A. Ehrenkranz; Anna Woo

1968-11-29T23:59:59.000Z

450

Recruitment of the intertidal barnacle Semibalanus balanoides : metamorphosis and survival from daily to seasonable timescales  

E-Print Network (OSTI)

The benthic habitat is the terminal destination for marine animals in terms of their reproductive lifecycle. Recruitment dynamics relating to seasonal changes in the benthic habitat may be the best source of information ...

Blythe, Jonathan N

2008-01-01T23:59:59.000Z

451

ELPIS-JP: a dataset of local-scale daily climate change scenarios for Japan  

Science Journals Connector (OSTI)

...Centre for Climate Modelling and Analysis Canada A1B, B1, A2 Flato et al. [37] mean...minimum temperatures, precipitation, solar radiation, relative humidity and wind...temperatures, (f) maximum temperatures, (g) solar radiation, (h)-relative humidity and...

2012-01-01T23:59:59.000Z

452

Atmospheric Environment 38 (2004) 44274436 Statistical comparison of observed and CMAQ modeled daily  

E-Print Network (OSTI)

2004 Abstract New statistical procedures to evaluate the Models-3/Community Multiscale Air Quality reserved. Keywords: Air quality model; Model evaluation; Space­time process; Separable covariance function 1. Introduction The Models-3/Community Multiscale Air Quality (CMAQ) modeling system has been

Jun, Mikyoung

453

E-Print Network 3.0 - average daily global Sample Search Results  

NLE Websites -- All DOE Office Websites (Extended Search)

Dunlop E.D., Albuisson M., Wald L, 2006. Online data and tools for estimation of solar electricity in Africa: the PVGIS approach. Proceedings from 21st Summary: . Long-term...

454

Age determined from the daily deposition of concentric rings on common octopus  

E-Print Network (OSTI)

Las Palmas de Gran Canaria Apdo. 550, Las Palmas de Gran Canaria Canary Islands, Spain E and May 1999, from catches of the small-scale fishery off the island of Gran Canaria (The Canary Islands

455

Future changes in daily summer temperature variability: driving processes and role for temperature extremes  

E-Print Network (OSTI)

extremes Erich M. Fischer ? Christoph Scha¨r Received: 20 May 2008 / Accepted: 19 September 2008 ? Springer summer temperature extremes, not only due to the mean warming itself, but also due to changes extremes particularly over the Mediterranean and the transitional climate zone (TCZ, between

Fischlin, Andreas

456

Long-Term Outcome Of Once Daily Saline Irrigation For The Treatment Of Pediatric Chronic Rhinosinusitis  

E-Print Network (OSTI)

Objectives:Chronic rhinosinusitis (CRS) results in significant morbidity and healthcare expenditure. The safety and effectiveness of nasal irrigation for the treatment of pediatric CRS has been demonstrated, but its long-term ...

Pham, Vinh

2013-05-31T23:59:59.000Z

457

Student Stress Exposure: A Daily Path Perspective on the Connections among Cognition, Place, and the Socioenvironment  

E-Print Network (OSTI)

with synched heart rate monitors and digital audio recorders. Stress as operationalized in this study is a negative cognitive appraisal and related physiological reaction to internal dialogues and the surrounding socio-environment assessed through heart rate...

Williams, Nikki

2012-10-19T23:59:59.000Z

458

An automatic cutting height control system for a sugarcane harvester  

E-Print Network (OSTI)

). . . . . 53 22. 23. Effect of the soil-stalk weight factor on the ground average, and the stalk average A comparison of Avg and Avs calculated from laboratory data with both real numbers, and integer numbers. . . . . . . 57 24 . A graph of a portion... factor, W. By calculating the difference between Avg and Avs, as equation (5) shows, the height of the sugarcane stubble remaining after cutting, 0, was to be determined. D = Avg - Avs (5) where: D - the height of the sugarcane stubble remaining...

Hale, Scott Andrew

2012-06-07T23:59:59.000Z

459

Data:79b8b601-9d3a-423f-bb6c-1afd2e27f810 | Open Energy Information  

Open Energy Info (EERE)

and the net energy charge for the billing period Applicability Demand (kW) Minimum (kW): 26 Maximum (kW): History (months): 1 Energy (kWh) Minimum (kWh): 2501 Maximum (kWh):...

460

Data:05d6c74a-9073-4ad2-8045-cd52082ca0a4 | Open Energy Information  

Open Energy Info (EERE)

http:www.xcelenergy.com Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

ENERGY & ENVIRONMENT DIVISION. ANNUAL REPORT FY 1980  

E-Print Network (OSTI)

kWh) (kWh) b b Refrigerator and Freezer (kWh) Source: Unionseveral months for refrigerators and freezers to a maximumPart 2, June, 1980. Refrigerator/freezers Freezers Clothes

Authors, Various

2010-01-01T23:59:59.000Z

462

Data:C4c60389-130a-4ffb-bef6-0fd9390d8ce8 | Open Energy Information  

Open Energy Info (EERE)

Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service Voltage Minimum (V):...

463

Data:5ae79a59-909b-4d8e-b6b2-de767fb70902 | Open Energy Information  

Open Energy Info (EERE)

Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

464

Data:E90b1d67-8320-4c1e-9538-066872d2d8bf | Open Energy Information  

Open Energy Info (EERE)

Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

465

Data:89a183f1-9364-4688-a526-7f3695abc274 | Open Energy Information  

Open Energy Info (EERE)

Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

466

Data:F1f7c112-b6f5-41ea-9174-8129be58f96f | Open Energy Information  

Open Energy Info (EERE)

Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

467

Data:8edef349-5aad-49ea-8005-247868695cea | Open Energy Information  

Open Energy Info (EERE)

Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

468

Data:9aaf2445-9bcb-47ad-ba23-674fdf0cca53 | Open Energy Information  

Open Energy Info (EERE)

Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

469

Data:6312d6f0-b4f9-4e0a-b53b-1ce45eb56c46 | Open Energy Information  

Open Energy Info (EERE)

your-home-rates-charges Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

470

Data:Cb37b28a-94c2-4591-bc52-b95e50ec7a45 | Open Energy Information  

Open Energy Info (EERE)

Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

471

Data:640c04cf-afd0-40a3-a28d-5198194b8b72 | Open Energy Information  

Open Energy Info (EERE)

Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

472

Data:52eabb28-cd1d-43dd-80d2-219739044111 | Open Energy Information  

Open Energy Info (EERE)

Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

473

Data:7d9701f3-cceb-418d-a3e1-655931024f05 | Open Energy Information  

Open Energy Info (EERE)

Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

474

Data:A498cc77-5706-412c-8478-af69daeb86da | Open Energy Information  

Open Energy Info (EERE)

10 Ted Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

475

Data:3f62f785-9067-4bec-8d26-1acc36863a1d | Open Energy Information  

Open Energy Info (EERE)

Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

476

Data:47d0fa79-672d-47e9-9da0-9e93850eba89 | Open Energy Information  

Open Energy Info (EERE)

2014%20Rate%20Sheet.pdf Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

477

Data:F1682cd3-50fb-4b21-b81c-4e5f9d77fb95 | Open Energy Information  

Open Energy Info (EERE)

Source Parent: Comments Applicability Demand (kW) Minimum (kW): Maximum (kW): History (months): Energy (kWh) Minimum (kWh): Maximum (kWh): History (months): Service...

478

Energy Cost Calculator for Electric and Gas Water Heaters | Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Electric and Gas Water Heaters Electric and Gas Water Heaters Energy Cost Calculator for Electric and Gas Water Heaters October 8, 2013 - 2:26pm Addthis Vary equipment size, energy cost, hours of operation, and /or efficiency level. INPUT SECTION Input the following data (if any parameter is missing, calculator will set to default value). Defaults Type of Water Heater Electric Gas Electric Average Daily Usage (gallons per day)* gallons 64* Energy Factor† 0.92 (electric) 0.61 (gas) Energy Cost $ / kWh $0.06 per kWh $.60 per therm Quantity of Water Heaters to be Purchased unit(s) 1 unit * See assumptions for various daily water use totals. † The comparison assumes a storage tank water heater as the input type. To allow demand water heaters as the comparison type, users can specify an input EF of up to 0.85; however, 0.66 is currently the best available EF for storage water heaters.

479

18 Characteristics of Texas Public Doctoral Programs Updated 7/16/12  

E-Print Network (OSTI)

'd; $133,241 avg; $1,598,90 3 total 13 Faculty Teaching Load Total number of semester credit hours Employment Profile (in field within one year of graduation) For each of the three most recent years

Johnston, Daniel

480

EV Project Chevrolet Volt Vehicle Summary Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2012 Vehicle Usage Overall fuel economy (mpg) 136 Overall electrical energy consumption (AC Whmi) 222 Number of trips 286,682 Total distance traveled (mi) 2,392,509 Avg...

Note: This page contains sample records for the topic "kwh daily avg" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

EV Project Chevrolet Volt Vehicle Summary Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

December 2011 Vehicle Usage Overall fuel economy (mpg) 131 Overall electrical energy consumption (AC Whmi) 271 Number of trips 13,819 Total distance traveled (mi) 108,115 Avg trip...

482

EV Project Chevrolet Volt Vehicle Summary Report  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

March 2012 Vehicle Usage Overall fuel economy (mpg) 139 Overall electrical energy consumption (AC Whmi) 293 Number of trips 76,425 Total distance traveled (mi) 609,737 Avg...

483

Gaussian interaction profile kernels for predicting drugtarget interaction  

Science Journals Connector (OSTI)

......2009). For the GPCR and nuclear receptor datasets, the method with the highest...Ion Channel, GPCR and nuclear receptor datasets, respectively. These results...predictions. Finally, on the Nuclear Receptor dataset, BY09 and RLS-Kron-avg......

Twan van Laarhoven; Sander B. Nabuurs; Elena Marchiori

2011-11-01T23:59:59.000Z

484

L3:MPO.CRUD.P8.02 Two-Phase Fluid Flow  

NLE Websites -- All DOE Office Websites (Extended Search)

or equivalent) m Mobility of a particle in a fluid Pa m s Density kg m 3 Surface tension N m avg Average tortuosity for flowpaths and diffusion - c Contact...

485

ARM - Datastreams - 30twr21x  

NLE Websites -- All DOE Office Websites (Extended Search)

Send us a note below or call us at 1-888-ARM-DATA. Send Datastream : 30TWR21X Sixty Meter Tower: temperature, humidity, & vapor pressure, 30-min avg Active Dates 1993.07.01 -...

486

ARM - Datastreams - 30twr10x  

NLE Websites -- All DOE Office Websites (Extended Search)

Archive Data Plot Example 30twr10x Archive Data Plot Datastream : 30TWR10X Sixty Meter Tower: temperature, humidity, & vapor pressure, 30-min avg Active Dates 1997.09.12 -...

487

ARM - Datastreams - 1twr10x  

NLE Websites -- All DOE Office Websites (Extended Search)

1twr10x Archive Data Plot Example 1twr10x Archive Data Plot Datastream : 1TWR10X Sixty Meter Tower: temp, humidity & vapor pressure, 1-min avg Active Dates 1997.09.12 - 2015.01.28...

488

ARM - Datastreams - 30twr60m  

NLE Websites -- All DOE Office Websites (Extended Search)

Archive Data Plot Example 30twr60m Archive Data Plot Datastream : 30TWR60M Sixty Meter Tower: temperature, humidity, & vapor pressure at 60-m, 30-min avg Active Dates...

489

ARM - VAP Product - 30twrmr  

NLE Websites -- All DOE Office Websites (Extended Search)

Send Example 30twrmr Data Plot Example 30twrmr data plot VAP Output : 30TWRMR Sixty meter tower: mixing ratio at surface, 25-m, and 60-m, 30-min avg Active Dates 1998.04.01 -...

490

Tracking the Sun III; The Installed Cost of Photovoltaics in the United States from 1998-2009  

E-Print Network (OSTI)

Incentive Programs (AEP, Entergy, Oncor, SWEPCO, TNMP) RERCIncentive TX Programs (AEP, Entergy, 10-100 kW Avg. CostIncentive Programs (AEP, Entergy, Oncor, SWEPCO, TNMP) VT

Barbose, Galen

2011-01-01T23:59:59.000Z

491

Heat-Loss Testing of Solel's UVAC3 Parabolic Trough Receiver  

SciTech Connect

For heat-loss testing on two Solel UVAC3 parabolic trough receivers, a correlation developed predicts receiver heat loss as a function of the difference between avg absorber and ambient temperatures.

Burkholder, F.; Kutscher, C.

2008-01-01T23:59:59.000Z

492

Distributed Energy Systems in California's Future: A Preliminary Report Volume 2  

E-Print Network (OSTI)

avg. energy/blade area) HEA}'/COOL Solar Thermal F1atplateSolar Thermal Cogeneration, waste heat recovery, and total energyof the energy to be produced by solar thermal plants.

Balderston, F.

2010-01-01T23:59:59.000Z

493

Computationally Efficient Modeling of High-Efficiency Clean Combustion...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

CFD simulation CFD Temp. Distribution at TDC overall tot i i i q m m C q Zone heat loss multipliers avg ad i ad i T T T T C - - Heat Loss from zone 'i' From Modified...

494

Seagate Crystal Reports - RADCM  

Office of Environmental Management (EM)

Missouri Missouri SITE: KansasCity PROGRAM: DP WASTE TYPE: Low Level Waste OPERATIONS OFFICE: Albuquerque Operations Office % of Stream KansasCity - Low Level Waste - Low Level Waste WASTE STREAM CODE: 04442 STREAM NAME:Low Level Waste MPC NAME:Solids TOTAL CURIES: 50.000 Approved Volume : Future Volume Avg: Future Volume Lower Limit: Future Volume Upper Limit: 100.000 Low Level W aste Isotopes Uranium-238 Avg Concentration: 1.0000E-003 Ci/m3 Low Limit Concent: Upper Limit Concent: Hydrogen-3 Avg Concentration: 5.0000E-003 Ci/m3 Low Limit Concent: Upper Limit Concent: Nickel-63 Avg Concentration: 2.5000E-001 Ci/m3 Low Limit Concent: Upper Limit Concent: STATE: Missouri SITE: W eldon PROGRAM: EM WASTE TYPE: 11e(2) Byproduct Waste OPERATIONS OFFICE: Oak Ridge Operations Office % of Stream

495

Seagate Crystal Reports - Snf10  

Office of Environmental Management (EM)

Stream Characteristic Detail (SNF-10) Stream Characteristic Detail (SNF-10) STATE: California SITE: GenAtomics PROGRAM: Office of Environmental Management OPERATIONS OFFICE: Oakland Operations Office GenAtomics - Spent Nuclear Fuel - TRIG A Reactor SNF STREAM CODE: 01725 Stream Fuel Types DOE Test SNF SST clad Storage Facility % of Stream Quantity GA TRIGA Reactor Facility 100 % of Stream Quantity Source Reactor GA-TRIGA MARK F 100.00 % of Stream TOTAL CURIES: ISOTOPE AND CONTAMINANT PROFILES 100 TRIGA Reactor SNF Isotopes Avg Concentration: 1.7706E-006 Ci Low Limit Concent: Upper Limit Concent: Actinium-227 Avg Concentration: 2.6087E+001 Ci Low Limit Concent: Upper Limit Concent: Americium-241 Avg Concentration: 1.1960E-001 Ci Low Limit Concent: Upper Limit Concent: Americium-242m Avg Concentration: 5.0739E-002 Ci

496

Seagate Crystal Reports - RADCM  

Office of Environmental Management (EM)

Iowa Iowa SITE: Ames Lab PROGRAM: SC WASTE TYPE: Low Level Waste OPERATIONS OFFICE: Chicago Operations Office % of Stream Ames Lab - Low Level Waste - Low Level Waste WASTE STREAM CODE: 00275 STREAM NAME:Low Level Waste MPC NAME:Heterogeneous Debris TOTAL CURIES: Approved Volume : Future Volume Avg: Future Volume Lower Limit: Future Volume Upper Limit: 100.000 Isotopes Thorium-232 Avg Concentration: Low Limit Concent: Upper Limit Concent: Uranium-238 Avg Concentration: Low Limit Concent: Upper Limit Concent: % of Stream Ames Lab - Low Level Waste - TRU Waste WASTE STREAM CODE: 03941 STREAM NAME:TRU Waste MPC NAME:Solids TOTAL CURIES: Approved Volume : Future Volume Avg: Future Volume Lower Limit: Future Volume Upper Limit: % of Stream Ames Lab - Low Level Waste - Low Level Waste FY 2046-2070

497

Seagate Crystal Reports - RADCM  

Office of Environmental Management (EM)

Jersey Jersey SITE: Princeton PROGRAM: SC WASTE TYPE: Low Level Waste OPERATIONS OFFICE: Chicago Operations Office % of Stream Princeton - Low Level Waste - Compactable LLW WASTE STREAM CODE: 00492 STREAM NAME:Com pactable LLW MPC NAME:Solids TOTAL CURIES: Approved Volume : Future Volume Avg: Future Volume Lower Limit: Future Volume Upper Limit: 100.000 Compactable LLW Isotopes Cobalt-60 Avg Concentration: Low Limit Concent:5.0000E-003 Ci/m3 Upper Limit Concent:5.0000E-003 Ci/m3 Hydrogen-3 Avg Concentration: Low Limit Concent:5.0040E-003 Ci/m3 Upper Limit Concent:1.0000E+001 Ci/m3 % of Stream Princeton - Low Level Waste - Non-Compactable LLW WASTE STREAM CODE: 00493 STREAM NAME:Non-Compactable LLW MPC NAME:Solids TOTAL CURIES: Approved Volume : Future Volume Avg: Future Volume Lower Limit:

498

E-Print Network 3.0 - area guizhou province Sample Search Results  

NLE Websites -- All DOE Office Websites (Extended Search)

and John Gibson Summary: exporting Provinces in 2006 included Shanxi, 43 billion KWh (coal based); Guizhou 36 billion KWh (coal based... driving demand and supply. The final...

499

EIA - Daily Report 10/12/05 - Hurricane Impacts on U.S. Oil & Natural Gas  

U.S. Energy Information Administration (EIA) Indexed Site

2, 4:00 pm 2, 4:00 pm Shut-in Status Date Shut-in Oil (bbl/d) % of Total Federal GOM Shut-in Gas (mmcf/d) % of Total Federal GOM 10/12/2005 1,046,462 66.4% 5,919 58.6% 10/11/2005 1,062,530 67.4% 6,042 59.8% 10/7/2005 1,162,913 73.8% 6,441 63.8% 10/6/2005 1,202,364 76.3% 6,628 65.6% 10/5/2005 1,299,928 82.5% 6,895 68.3% 10/4/2005 1,349,617 85.6% 7,170 71.0% 10/3/2005 1,391,926 88.3% 7,495 74.2% 9/30/2005 1,467,577 93.1% 7,941 78.6% 9/29/2005 1,478,780 93.8% 7,980 79.0% 9/28/2005 1,511,715 96.8% 8,072 77.2% source: Minerals Management Service graph of shut-in oil & natural gas production comparison of hurricanes Katrina & Ivan figure data Prices graph of oil and gas prices figure data graph of nymex futures for gasoline & deisel figure data NYMEX Futures Prices 10/12/2005 10/11/2005 change Week Ago 10/5/2005 Year Ago

500

EIA - Daily Report 10/19/05 - Hurricane Impacts on U.S. Oil & Natural Gas  

U.S. Energy Information Administration (EIA) Indexed Site

9, 4:00 pm 9, 4:00 pm Shut-in Status Date Shut-in Oil (bbl/d) % of Total Federal GOM Shut-in Gas (mmcf/d) % of Total Federal GOM 10/19/2005 973,084 61.7% 5,242 51.9% 10/18/2005 982,011 62.3% 5,346 52.9% 10/17/2005 996,291 63.2% 5,498 54.4% 10/14/2005 1,008,909 64.0% 5,647 55.9% 10/13/2005 1,031,261 65.4% 5,700 56.4% 10/12/2005 1,046,462 66.4% 5,919 58.6% 10/11/2005 1,062,530 67.4% 6,042 59.8% 10/7/2005 1,162,913 73.8% 6,441 63.8% 10/6/2005 1,202,364 76.3% 6,628 65.6% 10/5/2005 1,299,928 82.5% 6,895 68.3% 10/4/2005 1,349,617 85.6% 7,170 71.0% source: Minerals Management Service graph of shut-in oil & natural gas production comparison of hurricanes Katrina & Ivan figure data Prices graph of oil and gas prices figure data graph of nymex futures for gasoline & deisel figure data NYMEX Futures Prices 10/19/2005 10/18/2005