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Note: This page contains sample records for the topic "forecast thousand barrels" 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

California Natural Gas Total Liquids Extracted (Thousand Barrels...  

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

Liquids Extracted (Thousand Barrels) California Natural Gas Total Liquids Extracted (Thousand Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

2

Barrel cortex function  

Science Journals Connector (OSTI)

Neocortex, the neuronal structure at the base of the remarkable cognitive skills of mammals, is a layered sheet of neuronal tissue composed of juxtaposed and interconnected columns. A cortical column is considered the basic module of cortical processing present in all cortical areas. It is believed to contain a characteristic microcircuit composed of a few thousand neurons. The high degree of cortical segmentation into vertical columns and horizontal layers is a boon for scientific investigation because it eases the systematic dissection and functional analysis of intrinsic as well as extrinsic connections of the column. In this review we will argue that in order to understand neocortical function one needs to combine a microscopic view, elucidating the workings of the local columnar microcircuits, with a macroscopic view, which keeps track of the linkage of distant cortical modules in different behavioral contexts. We will exemplify this strategy using the model system of vibrissal touch in mice and rats. On the macroscopic level vibrissal touch is an important sense for the subterranean rodents and has been honed by evolution to serve an array of distinct behaviors. Importantly, the vibrissae are moved actively to touch – requiring intricate sensorimotor interactions. Vibrissal touch, therefore, offers ample opportunities to relate different behavioral contexts to specific interactions of distant columns. On the microscopic level, the cortical modules in primary somatosensory cortex process touch inputs at highest magnification and discreteness – each whisker is represented by its own so-called barrel column. The cellular composition, intrinsic connectivity and functional aspects of the barrel column have been studied in great detail. Building on the versatility of genetic tools available in rodents, new, highly selective and flexible cellular and molecular tools to monitor and manipulate neuronal activity have been devised. Researchers have started to combine these with advanced and highly precise behavioral methods, on par with the precision known from monkey preparations. Therefore, the vibrissal touch model system is exquisitely positioned to combine the microscopic with the macroscopic view and promises to be instrumental in our understanding of neocortical function.

Dirk Feldmeyer; Michael Brecht; Fritjof Helmchen; Carl C.H. Petersen; James F.A. Poulet; Jochen F. Staiger; Heiko J. Luhmann; Cornelius Schwarz

2013-01-01T23:59:59.000Z

3

U.S. crude oil production expected to top 9 million barrels per...  

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

half of this year, drilling is expected to increase and U.S. production is forecast to rise to an average of 9.5 million barrels per day in 2016. That would be the...

4

Forecast Prices  

Gasoline and Diesel Fuel Update (EIA)

Notes: Notes: Prices have already recovered from the spike, but are expected to remain elevated over year-ago levels because of the higher crude oil prices. There is a lot of uncertainty in the market as to where crude oil prices will be next winter, but our current forecast has them declining about $2.50 per barrel (6 cents per gallon) from today's levels by next October. U.S. average residential heating oil prices peaked at almost $1.50 as a result of the problems in the Northeast this past winter. The current forecast has them peaking at $1.08 next winter, but we will be revisiting the outlook in more detail next fall and presenting our findings at the annual Winter Fuels Conference. Similarly, diesel prices are also expected to fall. The current outlook projects retail diesel prices dropping about 14 cents per gallon

5

Vibration of Gun-Barrels1  

Science Journals Connector (OSTI)

... THIS research on the vibration of gun-barrels is a continuation of former investigations on the nature of ... of gun-barrels is a continuation of former investigations on the nature of vibrations set up in a gun-barrel when fixed, with a view to discover how ...

F. J.-S

1901-01-17T23:59:59.000Z

6

RACORO Forecasting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Daniel Hartsock CIMMS, University of Oklahoma ARM AAF Wiki page Weather Briefings Observed Weather Cloud forecasting models BUFKIT forecast soundings + guidance...

7

U.S. monthly oil production tops 8 million barrels per day for the first time since 1988  

Gasoline and Diesel Fuel Update (EIA)

U.S. crude oil production expected to hit four-decade high during 2015 U.S. crude oil production expected to hit four-decade high during 2015 U.S. crude oil production over the next two years is expected to grow to its highest level since the early 1970s. Oil output increased by 1 million barrels per day in 2013...and is expected to repeat that growth rate during 2014....according to the new forecast from the U.S. Energy Information Administration. U.S. crude oil production is forecast to average 8.5 million barrels per day this year and then rise to 9.3 million barrels per day in 2015. That would be the highest yearly oil output since 1972, and just 300,000 barrels per day below the all-time production high of 9.6 million barrels per day set in 1970. Most of the oil production growth will come from increased drilling in the shale formations in

8

Price of Maine Natural Gas Exports (Dollars per Thousand Cubic...  

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

Natural Gas Exports (Dollars per Thousand Cubic Feet) (Dollars per Thousand Cubic Feet) Price of Maine Natural Gas Exports (Dollars per Thousand Cubic Feet) (Dollars per Thousand...

9

Florida Natural Gas Plant Liquids, Proved Reserves (Million Barrels...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Proved Reserves (Million Barrels) Florida Natural Gas Plant Liquids, Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

10

Alaska Natural Gas Plant Liquids, Proved Reserves (Million Barrels...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Liquids, Proved Reserves (Million Barrels) Alaska Natural Gas Plant Liquids, Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

11

Kansas Natural Gas Plant Liquids, Proved Reserves (Million Barrels...  

Gasoline and Diesel Fuel Update (EIA)

Proved Reserves (Million Barrels) Kansas Natural Gas Plant Liquids, Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

12

Wyoming Natural Gas Liquids Proved Reserves (Million Barrels...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Proved Reserves (Million Barrels) Wyoming Natural Gas Liquids Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's...

13

Alabama Natural Gas Plant Liquids, Proved Reserves (Million Barrels...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Liquids, Proved Reserves (Million Barrels) Alabama Natural Gas Plant Liquids, Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7...

14

Pennsylvania Natural Gas Liquids Proved Reserves (Million Barrels...  

Gasoline and Diesel Fuel Update (EIA)

Proved Reserves (Million Barrels) Pennsylvania Natural Gas Liquids Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

15

Utah Natural Gas Liquids Proved Reserves (Million Barrels)  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Proved Reserves (Million Barrels) Utah Natural Gas Liquids Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 59...

16

Secretary Bodman Announces Sale of 11 Million Barrels of Crude...  

Energy Savers [EERE]

Sale of 11 Million Barrels of Crude Oil from the Nation's Strategic Petroleum Reserve Secretary Bodman Announces Sale of 11 Million Barrels of Crude Oil from the Nation's Strategic...

17

UNCORRECTED Reliability analysis of hybrid ceramic/steel gun barrels  

E-Print Network [OSTI]

UNCORRECTED PROOF Reliability analysis of hybrid ceramic/steel gun barrels M. GRUJICIC1 , J. R-5069, USA Received in final form 25 February 2002 AB ST R AC T Failure of the ceramic gun-barrel lining probability for the lining is also discussed. Keywords failure; gun-barrel lining; reliability; thermo

Grujicic, Mica

18

NETL: News Release - Ultra-low Cost Well Monitoring Could Save Thousands of  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

January 19, 2005 January 19, 2005 Ultra-low Cost Well Monitoring Could Save Thousands of Marginal Oil Wells DOE-funded Project in California Tested Successfully TULSA, OKLA. - A new, ultra-low cost method for monitoring marginal oil wells promises to help rescue thousands of U.S. wells from an early demise. Developed with funding from the Department of Energy (DOE) and project-managed by DOE's National Energy Technology Laboratory, this novel, inexpensive, monitoring-system prototype helps improve the efficiency of rod-pumped oil wells. The ultimate payoff for such an approach could be the recovery of millions of barrels of oil otherwise permanently lost while the United States watches its oil production continue to slide. MORE INFO Marginal Expense Oil Well Wireless Surveillance MEOWS -Phase II final technical report [PDF-294KB]

19

Recent results from the Crystal Barrel experiment  

SciTech Connect (OSTI)

The Crystal Barrel experiment has been constructed and installed at the Low Energy Antiproton Ring (LEAR) at CERN. It has been fully operational since late 1989. In this talk, recent results of meson spectroscopy in p[bar p]-annihilations are presented. The main emphasis is on all-neutral annihilations, the study of the strange quark content of the proton, and the investigation of the decay mode of il particles. A 2[sup ++] resonance decaying into [pi][degrees][pi][degrees]at a mass of 1515 [plus minus] 10 MeV with a width of 120 [plus minus] 10 MeV has been seen in a 3[pi][degrees] final state.

Not Available

1991-10-09T23:59:59.000Z

20

Recent results from the Crystal Barrel experiment  

SciTech Connect (OSTI)

The Crystal Barrel experiment has been constructed and installed at the Low Energy Antiproton Ring (LEAR) at CERN. It has been fully operational since late 1989. In this talk, recent results of meson spectroscopy in p{bar p}-annihilations are presented. The main emphasis is on all-neutral annihilations, the study of the strange quark content of the proton, and the investigation of the decay mode of il particles. A 2{sup ++} resonance decaying into {pi}{degrees}{pi}{degrees}at a mass of 1515 {plus_minus} 10 MeV with a width of 120 {plus_minus} 10 MeV has been seen in a 3{pi}{degrees} final state.

The Crystal Barrel Collaboration

1991-10-09T23:59:59.000Z

Note: This page contains sample records for the topic "forecast thousand barrels" 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

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Oil Markets Oil Markets IEO2005 projects that world crude oil prices in real 2003 dollars will decline from their current level by 2010, then rise gradually through 2025. In the International Energy Outlook 2005 (IEO2005) reference case, world demand for crude oil grows from 78 million barrels per day in 2002 to 103 million barrels per day in 2015 and to just over 119 million barrels per day in 2025. Much of the growth in oil consumption is projected for the emerging Asian nations, where strong economic growth results in a robust increase in oil demand. Emerging Asia (including China and India) accounts for 45 percent of the total world increase in oil use over the forecast period in the IEO2005 reference case. The projected increase in world oil demand would require an increment to world production capability of more than 42 million barrels per day relative to the 2002 crude oil production capacity of 80.0 million barrels per day. Producers in the Organization of Petroleum Exporting Countries (OPEC) are expected to be the major source of production increases. In addition, non-OPEC supply is expected to remain highly competitive, with major increments to supply coming from offshore resources, especially in the Caspian Basin, Latin America, and deepwater West Africa. The estimates of incremental production are based on current proved reserves and a country-by-country assessment of ultimately recoverable petroleum. In the IEO2005 oil price cases, the substantial investment capital required to produce the incremental volumes is assumed to exist, and the investors are expected to receive at least a 10-percent return on investment.

22

Short-Term World Oil Price Forecast  

Gasoline and Diesel Fuel Update (EIA)

4 4 Notes: This graph shows monthly average spot West Texas Intermediate crude oil prices. Spot WTI crude oil prices peaked last fall as anticipated boosts to world supply from OPEC and other sources did not show up in actual stocks data. So where do we see crude oil prices going from here? Crude oil prices are expected to be about $28-$30 per barrel for the rest of this year, but note the uncertainty bands on this projection. They give an indication of how difficult it is to know what these prices are going to do. Also, EIA does not forecast volatility. This relatively flat forecast could be correct on average, with wide swings around the base line. Let's explore why we think prices will likely remain high, by looking at an important market barometer - inventories - which measures the

23

E-Print Network 3.0 - alice central barrel Sample Search Results  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

barrel robots. This centralized sensing and control can reduce the cost of each barrel robot. In one... - dition for the upper bound on the number of barrel robots that can be...

24

DOE Sponsored College Night Draws Thousands | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

Sponsored College Night Draws Thousands Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands September 6, 2013 - 12:00pm Addthis DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands College recruiters from the Golden State to the Peach State gathered in a packed arena for the twentieth annual CSRA College Night in Augusta, Georgia. The event is a cooperative effort among Department of Energy

25

DOE Sponsored College Night Draws Thousands | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands September 6, 2013 - 12:00pm Addthis DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands DOE Sponsored College Night Draws Thousands College recruiters from the Golden State to the Peach State gathered in a packed arena for the twentieth annual CSRA College Night in Augusta, Georgia. The event is a cooperative effort among Department of Energy

26

Forecasting World Crude Oil Production Using Multicyclic Hubbert Model  

Science Journals Connector (OSTI)

OPEC’s actual production was mainly unrestricted until the 1973 Arab oil embargo. ... On the basis of the analysis of all 47 investigated oil producing countries, the results of our study estimated that the world ultimate reserve of crude oil is around 2140 BSTB and that 1161 BSTB are remaining to be produced as of 2005 year end. ... MSTB/D = thousand stock tank barrels per day ...

Ibrahim Sami Nashawi; Adel Malallah; Mohammed Al-Bisharah

2010-02-04T23:59:59.000Z

27

Ohio Natural Gas Liquids Proved Reserves (Million Barrels)  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Natural Gas Liquids Proved Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 0 1980's 0 0 - No Data Reported; -- ...

28

Thousand Springs Wind Park | Open Energy Information  

Open Energy Info (EERE)

Park Park Jump to: navigation, search Name Thousand Springs Wind Park Facility Thousand Springs Wind Park Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner Exergy Developer Exergy Energy Purchaser Idaho Power Location Twin Falls County ID Coordinates 42.7452°, -114.828° 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":42.7452,"lon":-114.828,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

29

Baseballs and Barrels: World Statistics Day | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

Baseballs and Barrels: World Statistics Day Baseballs and Barrels: World Statistics Day Baseballs and Barrels: World Statistics Day October 20, 2010 - 1:06pm Addthis Dr. Richard Newell Dr. Richard Newell Does the American League hold more baseball World Series titles than the National League? Yes. Does Saudi Arabia produce more crude oil than Russia? No. How do I know? Statistics. The month of October not only marks the beginning of Major League Baseball's World Series and Energy Awareness Month, but also the celebration of the first ever World Statistics Day on October 20th. Statistics don't just help us answer trivia questions - they also help us make intelligent decisions. If I heat my home with natural gas, I'm probably interested in what natural gas prices are likely to be this winter. If my business manufactures solar panels, I would want to know how

30

Gulf LNG, Mississippi LNG Imports (Price) (Dollars per Thousand...  

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

Gulf LNG, Mississippi LNG Imports (Price) (Dollars per Thousand Cubic Feet) Gulf LNG, Mississippi LNG Imports (Price) (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2...

31

Price of New Hampshire Natural Gas Exports (Dollars per Thousand...  

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

New Hampshire Natural Gas Exports (Dollars per Thousand Cubic Feet) Price of New Hampshire Natural Gas Exports (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3...

32

Price of Michigan Natural Gas Exports (Dollars per Thousand Cubic...  

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

Michigan Natural Gas Exports (Dollars per Thousand Cubic Feet) Price of Michigan Natural Gas Exports (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

33

Price of Texas Natural Gas Exports (Dollars per Thousand Cubic...  

Gasoline and Diesel Fuel Update (EIA)

Texas Natural Gas Exports (Dollars per Thousand Cubic Feet) Price of Texas Natural Gas Exports (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

34

Price of Washington Natural Gas Exports (Dollars per Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Washington Natural Gas Exports (Dollars per Thousand Cubic Feet) Price of Washington Natural Gas Exports (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

35

Price of Alaska Natural Gas Exports (Dollars per Thousand Cubic...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Alaska Natural Gas Exports (Dollars per Thousand Cubic Feet) Price of Alaska Natural Gas Exports (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

36

Price of California Natural Gas Exports (Dollars per Thousand...  

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

California Natural Gas Exports (Dollars per Thousand Cubic Feet) Price of California Natural Gas Exports (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

37

Price of Montana Natural Gas Exports (Dollars per Thousand Cubic...  

Gasoline and Diesel Fuel Update (EIA)

Montana Natural Gas Exports (Dollars per Thousand Cubic Feet) Price of Montana Natural Gas Exports (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

38

Price of Arizona Natural Gas Exports (Dollars per Thousand Cubic...  

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

Arizona Natural Gas Exports (Dollars per Thousand Cubic Feet) Price of Arizona Natural Gas Exports (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

39

Oklahoma Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Oklahoma Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

40

New Jersey Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) New Jersey Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

Note: This page contains sample records for the topic "forecast thousand barrels" 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

Texas Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Texas Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

42

Florida Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Florida Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

43

Ohio Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Ohio Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

44

Washington Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Washington Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

45

Louisiana Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Louisiana Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

46

West Virginia Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) West Virginia Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

47

Colorado Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Colorado Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

48

Nebraska Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Nebraska Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

49

Illinois Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Illinois Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

50

New York Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) New York Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

51

Virginia Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Virginia Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

52

New Hampshire Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) New Hampshire Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

53

Alabama Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Alabama Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

54

Pennsylvania Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Pennsylvania Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

55

Nevada Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Nevada Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

56

Idaho Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Idaho Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

57

Rhode Island Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Rhode Island Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

58

Connecticut Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Connecticut Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

59

Oregon Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Oregon Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

60

Michigan Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Michigan Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

Note: This page contains sample records for the topic "forecast thousand barrels" 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

Kansas Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Kansas Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

62

Indiana Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Indiana Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

63

Mississippi Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Mississippi Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

64

Iowa Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Iowa Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

65

South Carolina Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) South Carolina Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

66

Tennessee Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Tennessee Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

67

Delaware Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Delaware Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

68

North Carolina Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) North Carolina Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

69

Georgia Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Georgia Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

70

South Dakota Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) South Dakota Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

71

Arkansas Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Arkansas Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

72

Arizona Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Arizona Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

73

Wyoming Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Wyoming Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

74

Utah Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Utah Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

75

Massachusetts Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Massachusetts Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

76

Minnesota Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Minnesota Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

77

North Dakota Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) North Dakota Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

78

Maryland Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Maryland Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

79

Missouri Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Missouri Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

80

California Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) California Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

Note: This page contains sample records for the topic "forecast thousand barrels" 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

Montana Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Montana Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

82

Forecasting wireless communication technologies  

Science Journals Connector (OSTI)

The purpose of the paper is to present a formal comparison of a variety of multiple regression models in technology forecasting for wireless communication. We compare results obtained from multiple regression models to determine whether they provide a superior fitting and forecasting performance. Both techniques predict the year of wireless communication technology introduction from the first (1G) to fourth (4G) generations. This paper intends to identify the key parameters impacting the growth of wireless communications. The comparison of technology forecasting approaches benefits future researchers and practitioners when developing a prediction of future wireless communication technologies. The items of focus will be to understand the relationship between variable selection and model fit. Because the forecasting error was successfully reduced from previous approaches, the quadratic regression methodology is applied to the forecasting of future technology commercialisation. In this study, the data will show that the quadratic regression forecasting technique provides a better fit to the curve.

Sabrina Patino; Jisun Kim; Tugrul U. Daim

2010-01-01T23:59:59.000Z

83

U.S. diesel fuel price forecast to be 1 penny lower this summer at $3.94 a gallon  

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

diesel fuel price forecast to be 1 penny lower this summer diesel fuel price forecast to be 1 penny lower this summer at $3.94 a gallon The retail price of diesel fuel is expected to average $3.94 a gallon during the summer driving season that which runs from April through September. That's close to last summer's pump price of $3.95, according to the latest monthly energy outlook from the U.S. Energy Information Administration. Demand for distillate fuel, which includes diesel fuel, is expected to be up less than 1 percent from last summer. Daily production of distillate fuel at U.S. refineries is forecast to be 70,000 barrels higher this summer. With domestic distillate output exceeding demand, U.S. net exports of distillate fuel are expected to average 830,000 barrels per day this summer. That's down 12 percent from last summer's

84

Wind Power Forecasting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Retrospective Reports 2011 Smart Grid Wind Integration Wind Integration Initiatives Wind Power Forecasting Wind Projects Email List Self Supplied Balancing Reserves Dynamic...

85

Solar forecasting review  

E-Print Network [OSTI]

2.1.2 European Solar Radiation Atlas (ESRA)2.4 Evaluation of Solar Forecasting . . . . . . . . .2.4.1 Solar Variability . . . . . . . . . . . . .

Inman, Richard Headen

2012-01-01T23:59:59.000Z

86

Wind Power Forecasting  

Science Journals Connector (OSTI)

The National Center for Atmospheric Research (NCAR) has configured a Wind Power Forecasting System for Xcel Energy that integrates high resolution and ensemble...

Sue Ellen Haupt; William P. Mahoney; Keith Parks

2014-01-01T23:59:59.000Z

87

Energy Demand Forecasting  

Science Journals Connector (OSTI)

This chapter presents alternative approaches used in forecasting energy demand and discusses their pros and cons. It... Chaps. 3 and 4 ...

S. C. Bhattacharyya

2011-01-01T23:59:59.000Z

88

Improving Inventory Control Using Forecasting  

E-Print Network [OSTI]

This project studied and analyzed Electronic Controls, Inc.’s forecasting process for three high-demand products. In addition, alternative forecasting methods were developed to compare to the current forecast method. The ...

Balandran, Juan

2005-12-16T23:59:59.000Z

89

Basic Installation Guidelines & Instructions for your SkyJuice Rain Barrel 1. Your rain barrel must be placed on a surface that is flat and level. Use a spade to flatten the area for placement of the barrel.  

E-Print Network [OSTI]

the laundry, or rinsing your hair like some of our grandmothers may have done. 3. To maintain the tight the barrel by the spigot. To maintain the tight connection, open the barrel and tighten the nut on the inside will not harm plants and will actually help the soil soak up the water. B. Adding a few drops of Olive Oil

90

Technology Forecasting Scenario Development  

E-Print Network [OSTI]

Technology Forecasting and Scenario Development Newsletter No. 2 October 1998 Systems Analysis was initiated on the establishment of a new research programme entitled Technology Forecasting and Scenario and commercial applica- tion of new technology. An international Scientific Advisory Panel has been set up

91

CAPP 2010 Forecast.indd  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Forecast, Markets & Pipelines 1 Crude Oil Forecast, Markets & Pipelines June 2010 2 CANADIAN ASSOCIATION OF PETROLEUM PRODUCERS Disclaimer: This publication was prepared by the...

92

,"New York Natural Gas Industrial Price (Dollars per Thousand...  

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

,,"(202) 586-8800",,,"182015 12:47:18 PM" "Back to Contents","Data 1: New York Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"...

93

,"New York Natural Gas Industrial Price (Dollars per Thousand...  

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

,,"(202) 586-8800",,,"182015 12:47:17 PM" "Back to Contents","Data 1: New York Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"...

94

,"Connecticut Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Connecticut Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2013...

95

,"Connecticut Natural Gas Industrial Price (Dollars per Thousand...  

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

,,"(202) 586-8800",,,"1162014 3:02:15 PM" "Back to Contents","Data 1: Connecticut Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"...

96

,"New York Natural Gas Imports Price (Dollars per Thousand Cubic...  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New York Natural Gas Imports Price (Dollars per Thousand Cubic Feet)",1,"Annual",2013 ,"Release...

97

,"New York Natural Gas Vehicle Fuel Price (Dollars per Thousand...  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New York Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2013...

98

Data Acquisition-Manipulation At Valley Of Ten Thousand Smokes...  

Open Energy Info (EERE)

Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Data Acquisition-Manipulation At Valley Of Ten Thousand Smokes Region Area (Kodosky & Keith,...

99

Extreme wave events during hurricanes can seriously jeopardize the integrity and safety of offshore oil and gas operations in the Gulf of Mexico. Validation of wave forecast for  

E-Print Network [OSTI]

oil and gas operations in the Gulf of Mexico. Validation of wave forecast for significant wave heights of Mexico. Before the storm, it produced 148,000 barrels of oil equivalent per day and 160 million cubic over the warm Gulf of Mexico water between 26 and 28 August, and became a category 5 hurricane by 1200

100

Valuing Climate Forecast Information  

Science Journals Connector (OSTI)

The article describes research opportunities associated with evaluating the characteristics of climate forecasts in settings where sequential decisions are made. Illustrative results are provided for corn production in east central Illinois. ...

Steven T. Sonka; James W. Mjelde; Peter J. Lamb; Steven E. Hollinger; Bruce L. Dixon

1987-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast thousand barrels" 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

Comparing Forecast Skill  

Science Journals Connector (OSTI)

A basic question in forecasting is whether one prediction system is more skillful than another. Some commonly used statistical significance tests cannot answer this question correctly if the skills are computed on a common period or using a common ...

Timothy DelSole; Michael K. Tippett

2014-12-01T23:59:59.000Z

102

Secretary Bodman Announces Sale of 11 Million Barrels of Crude Oil from the  

Broader source: Energy.gov (indexed) [DOE]

Sale of 11 Million Barrels of Crude Oil Sale of 11 Million Barrels of Crude Oil from the Nation's Strategic Petroleum Reserve Secretary Bodman Announces Sale of 11 Million Barrels of Crude Oil from the Nation's Strategic Petroleum Reserve September 14, 2005 - 10:21am Addthis WASHINGTON, DC - Secretary Samuel W. Bodman announced that the Department of Energy has approved bids for the sale of 11 million barrels of crude oil from the Strategic Petroleum Reserve (SPR). Combined with the 12.6 million barrels of crude previously approved for loans these SPR releases, in response to the disruptions caused by Hurricane Katrina, will provide 23.6 million barrels of crude for the U.S. market. "The United States is committed to using all of the tools at our disposal to help keep our oil and gasoline markets well supplied," Secretary Bodman

103

The How's and Why's of Replacing the Whole Barrel | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

The How's and Why's of Replacing the Whole Barrel The How's and Why's of Replacing the Whole Barrel The How's and Why's of Replacing the Whole Barrel October 19, 2011 - 4:09pm Addthis A 42-U.S. gallon barrel of crude oil yields about 45 gallons of petroleum products. Source: Energy Information Administration, “Oil: Crude Oil and Petroleum Products Explained” and Annual Energy Outlook 2009 (Updated February 2010). A 42-U.S. gallon barrel of crude oil yields about 45 gallons of petroleum products. Source: Energy Information Administration, "Oil: Crude Oil and Petroleum Products Explained" and Annual Energy Outlook 2009 (Updated February 2010). Paul Bryan Biomass Program Manager, Office of Energy Efficiency & Renewable Energy For many, a barrel of oil is almost synonymous with its most prominent

104

Valley Of Ten Thousand Smokes Region Geothermal Area | Open Energy  

Open Energy Info (EERE)

Valley Of Ten Thousand Smokes Region Geothermal Area Valley Of Ten Thousand Smokes Region Geothermal Area (Redirected from Valley Of Ten Thousand Smokes Region Area) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermal Resource Area: Valley Of Ten Thousand Smokes Region Geothermal Area Contents 1 Area Overview 2 History and Infrastructure 3 Regulatory and Environmental Issues 4 Exploration History 5 Well Field Description 6 Geology of the Area 7 Geofluid Geochemistry 8 NEPA-Related Analyses (0) 9 Exploration Activities (8) 10 References Area Overview Geothermal Area Profile Location: Alaska Exploration Region: Alaska Geothermal Region GEA Development Phase: 2008 USGS Resource Estimate Mean Reservoir Temp: Estimated Reservoir Volume: Mean Capacity: Click "Edit With Form" above to add content

105

Compound and Elemental Analysis At Valley Of Ten Thousand Smokes...  

Open Energy Info (EERE)

DOE-funding Unknown References T. E. C. Keith, J. M. Thompson, R. A. Hutchinson, L. D. White (1992) Geochemistry Of Waters In The Valley Of Ten Thousand Smokes Region, Alaska...

106

Sligar's Thousand Springs Resort Pool & Spa Low Temperature Geothermal  

Open Energy Info (EERE)

Sligar's Thousand Springs Resort Pool & Spa Low Temperature Geothermal Sligar's Thousand Springs Resort Pool & Spa Low Temperature Geothermal Facility Jump to: navigation, search Name Sligar's Thousand Springs Resort Pool & Spa Low Temperature Geothermal Facility Facility Sligar's Thousand Springs Resort Sector Geothermal energy Type Pool and Spa Location Hagerman, Idaho Coordinates 42.8121244°, -114.898669° 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":[]}

107

Sandia National Laboratories: solar forecasting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Energy, Modeling & Analysis, News, News & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource...

108

Consensus Coal Production Forecast for  

E-Print Network [OSTI]

Rate Forecasts 19 5. EIA Forecast: Regional Coal Production 22 6. Wood Mackenzie Forecast: W.V. Steam to data currently published by the Energy Information Administration (EIA), coal production in the state in this report calls for state production to decline by 11.3 percent in 2009 to 140.2 million tons. During

Mohaghegh, Shahab

109

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Table 2. Total Energy Consumption, Actual vs. Forecasts Table 3. Total Petroleum Consumption, Actual vs. Forecasts Table 4. Total Natural Gas Consumption, Actual vs. Forecasts Table 5. Total Coal Consumption, Actual vs. Forecasts Table 6. Total Electricity Sales, Actual vs. Forecasts Table 7. Crude Oil Production, Actual vs. Forecasts Table 8. Natural Gas Production, Actual vs. Forecasts Table 9. Coal Production, Actual vs. Forecasts Table 10. Net Petroleum Imports, Actual vs. Forecasts Table 11. Net Natural Gas Imports, Actual vs. Forecasts Table 12. Net Coal Exports, Actual vs. Forecasts Table 13. World Oil Prices, Actual vs. Forecasts Table 14. Natural Gas Wellhead Prices, Actual vs. Forecasts Table 15. Coal Prices to Electric Utilities, Actual vs. Forecasts

110

On Sequential Probability Forecasting  

E-Print Network [OSTI]

at the same time. [Probability, Statistics and Truth, MacMillan 1957. page 11] ... the collective "denotes a collective wherein the attribute of the single event is the number of points thrown. [Probability, StatisticsOn Sequential Probability Forecasting David A. Bessler 1 David A. Bessler Texas A&M University

McCarl, Bruce A.

111

Property:Ind rev (thousand $) | Open Energy Information  

Open Energy Info (EERE)

rev (thousand $) rev (thousand $) Jump to: navigation, search This is a property of type Number. Revenue from sales to industrial consumers Pages using the property "Ind rev (thousand $)" Showing 25 pages using this property. (previous 25) (next 25) 4 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - April 2008 + 1,350 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - August 2008 + 1,445 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - December 2008 + 1,337 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - February 2008 + 1,345 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - February 2009 + 1,219 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - January 2008 + 1,337 +

112

Valley Of Ten Thousand Smokes Region Geothermal Area | Open Energy  

Open Energy Info (EERE)

Valley Of Ten Thousand Smokes Region Geothermal Area Valley Of Ten Thousand Smokes Region Geothermal Area Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermal Resource Area: Valley Of Ten Thousand Smokes Region Geothermal Area Contents 1 Area Overview 2 History and Infrastructure 3 Regulatory and Environmental Issues 4 Exploration History 5 Well Field Description 6 Geology of the Area 7 Geofluid Geochemistry 8 NEPA-Related Analyses (0) 9 Exploration Activities (8) 10 References Area Overview Geothermal Area Profile Location: Alaska Exploration Region: Alaska Geothermal Region GEA Development Phase: 2008 USGS Resource Estimate Mean Reservoir Temp: Estimated Reservoir Volume: Mean Capacity: Click "Edit With Form" above to add content History and Infrastructure Operating Power Plants: 0 No geothermal plants listed.

113

Property:Com rev (thousand $) | Open Energy Information  

Open Energy Info (EERE)

Com rev (thousand $) Com rev (thousand $) Jump to: navigation, search This is a property of type Number. Revenue from sales to commercial consumers Pages using the property "Com rev (thousand $)" Showing 25 pages using this property. (previous 25) (next 25) 4 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - April 2008 + 1,765 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - August 2008 + 2,643 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - December 2008 + 2,031 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - February 2008 + 1,765 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - February 2009 + 2,044 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - January 2008 + 1,764 +

114

Forecasting future oil production in Norway and the UK: a general improved methodology  

E-Print Network [OSTI]

We present a new Monte-Carlo methodology to forecast the crude oil production of Norway and the U.K. based on a two-step process, (i) the nonlinear extrapolation of the current/past performances of individual oil fields and (ii) a stochastic model of the frequency of future oil field discoveries. Compared with the standard methodology that tends to underestimate remaining oil reserves, our method gives a better description of future oil production, as validated by our back-tests starting in 2008. Specifically, we predict remaining reserves extractable until 2030 to be 188 +/- 10 million barrels for Norway and 98 +/- 10 million barrels for the UK, which are respectively 45% and 66% above the predictions using the standard methodology.

Fievet, Lucas; Cauwels, Peter; Sornette, Didier

2014-01-01T23:59:59.000Z

115

Metabolic Engineering and Synthetic Biology in Strain Development Every year, we consume about 27 billion barrels of fossil oil.  

E-Print Network [OSTI]

billion barrels of fossil oil. This enormous amount of oil is used for fueling our cars and airplanes

116

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sánchez The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors,

117

Simulation and testing of pyramid and barrel vault skylights  

SciTech Connect (OSTI)

The thermal performance of fenestration in commercial buildings can have a significant effect on building loads--yet there is little information on the performance of these products. With this in mind, ASHRAE TC 4.5, Fenestration, commissioned a research project involving test and simulation of commercial fenestration systems. The objectives of ASHRAE Research Project 877 were: to evaluate the thermal performance (U-factors) of commonly used commercial glazed roof and wall assemblies; to obtain a better fundamental understanding of the heat transfer processes that occur in these specialty fenestration products; to develop correlations for natural-convection heat transfer in complex glazing cavities; to develop a methodology for evaluating complex fenestration products, suitable for inclusion in ASHRAE Standard 142P (ASHRAE 1996); and to generate U-factors for common commercial fenestration products, suitable for inclusion in the ASHRAE Handbook--Fundamentals. This paper describes testing and simulation of pyramid and barrel vault skylight specimens and provides guidelines for modeling these systems based on the validated results.

McGowan, A.G. [Enermodal Engineering, Ltd., Kitchener, Ontario (Canada); Desjarlais, A.O. [Oak Ridge National Lab. TN (United States); Wright, J.L. [Univ. of Waterloo, Ontario (Canada)

1998-10-01T23:59:59.000Z

118

THOUSANDS OF PROTEINS LIKELY TO HAVE LONG DISORDERED REGIONS  

E-Print Network [OSTI]

THOUSANDS OF PROTEINS LIKELY TO HAVE LONG DISORDERED REGIONS PEDRO ROMERO, ZORAN OBRADOVIC School of protein disorder using primary sequence information were developed and applied to the Swiss Protein Database. More than 15,000 proteins were predicted to contain disordered regions of at least 40 consecutive

Obradovic, Zoran

119

Approximate Bayesian Computations Done Exactly: Towards a Thousand Human Genomes  

E-Print Network [OSTI]

Approximate Bayesian Computations Done Exactly: Towards a Thousand Human Genomes Principal of California, Irvine, USA January 28, 2011 Abstract Currently, 1000 whole human genomes are being sequenced. It is becoming exceedingly difficult to extract critical information from such extensive population-level genomic

Sainudiin, Raazesh

120

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sanchez by Esmeralda Sanchez Errata -(7/14/04) The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors, expressed as the percentage difference between the Reference Case projection and actual historic value, shown for every AEO and for each year in the forecast horizon (for a given variable). The historical data are typically taken from the Annual Energy Review (AER). The last column of Table 1 provides a summary of the most recent average absolute forecast errors. The calculation of the forecast error is shown in more detail in Tables 2 through 18. Because data for coal prices to electric generating plants were not available from the AER, data from the Monthly Energy Review (MER), July 2003 were used.

Note: This page contains sample records for the topic "forecast thousand barrels" 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

DOE to Sell 35,000 Barrels of Oil from the Northeast Home Heating Oil  

Broader source: Energy.gov (indexed) [DOE]

to Sell 35,000 Barrels of Oil from the Northeast Home Heating to Sell 35,000 Barrels of Oil from the Northeast Home Heating Oil Reserve DOE to Sell 35,000 Barrels of Oil from the Northeast Home Heating Oil Reserve May 24, 2007 - 4:16pm Addthis WASHINGTON, DC - The U.S. Department of Energy announced today that it will sell approximately 35,000 barrels of home heating oil from the Northeast Home Heating Oil Reserve (NEHHOR). The Reserve's current 5-year storage contracts expire on September 30, 2007 and market conditions have caused new storage costs to rise to a level that exceeds available funds. Revenue from the sale will be used to supplement funds for the award of new long-term storage contracts that will begin on October 1, 2007. The Department will work with Congress to resolve these funding issues in order

122

DOE to Sell 35,000 Barrels of Oil from the Northeast Home Heating Oil  

Broader source: Energy.gov (indexed) [DOE]

Sell 35,000 Barrels of Oil from the Northeast Home Heating Sell 35,000 Barrels of Oil from the Northeast Home Heating Oil Reserve DOE to Sell 35,000 Barrels of Oil from the Northeast Home Heating Oil Reserve May 24, 2007 - 4:16pm Addthis WASHINGTON, DC - The U.S. Department of Energy announced today that it will sell approximately 35,000 barrels of home heating oil from the Northeast Home Heating Oil Reserve (NEHHOR). The Reserve's current 5-year storage contracts expire on September 30, 2007 and market conditions have caused new storage costs to rise to a level that exceeds available funds. Revenue from the sale will be used to supplement funds for the award of new long-term storage contracts that will begin on October 1, 2007. The Department will work with Congress to resolve these funding issues in order to restore the inventory of the Reserve to its full authorized size.

123

U.S. monthly oil production tops 8 million barrels per day for...  

Gasoline and Diesel Fuel Update (EIA)

the U.S. Energy Information Administration said it expects world oil production to rise by 1.3 million barrels per day next year....with U.S. daily oil output alone...

124

A 12-barrel deuterium pellet injector for the C-2 field-reversed configuration device  

Science Journals Connector (OSTI)

A compact 12-barrel deuterium pellet injector for plasma studies in the C-2 field-reversed configuration device (USA) is described. As in other multibarrel injectors, pellets are simultaneously formed inside s...

I. V. Vinyar; A. Ya. Lukin; S. V. Skoblikov…

2014-07-01T23:59:59.000Z

125

Price forecasting for notebook computers.  

E-Print Network [OSTI]

??This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a… (more)

Rutherford, Derek Paul

2012-01-01T23:59:59.000Z

126

Ensemble Forecasts and their Verification  

E-Print Network [OSTI]

· Ensemble forecast verification ­ Performance metrics: Brier Score, CRPSS · New concepts and developments of weather Sources: Insufficient spatial resolution, truncation errors in the dynamical equations

Maryland at College Park, University of

127

"2012 Total Electric Industry- Revenue (Thousands Dollars)"  

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

Revenue (Thousands Dollars)" Revenue (Thousands Dollars)" "(Data from forms EIA-861- schedules 4A-D, EIA-861S and EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",7418025.1,6137400,3292222.3,37797.4,16885444.6 "Connecticut",2212594.3,1901294.3,451909.7,18679.5,4584477.8 "Maine",656822,467228,241624.4,0,1365674.3 "Massachusetts",3029291.6,2453106,2127180,17162,7626739.5 "New Hampshire",713388.2,598371.1,231041,0,1542800.3 "Rhode Island",449603.6,431951.9,98597.2,1955.9,982108.6 "Vermont",356325.4,285448.7,141870,0,783644.1 "Middle Atlantic",20195109.9,20394744.7,5206283.9,488944,46285082.4

128

"2012 Total Electric Industry- Sales (Thousand Megawatthours)"  

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

Sales (Thousand Megawatthours)" Sales (Thousand Megawatthours)" "(Data from forms EIA-861- schedules 4A, 4B, 4D, EIA-861S and EIA-861U)" "State","Residential","Commercial","Industrial","Transportation","Total" "New England",47207.696,44864.227,27817.984,566.173,120456.08 "Connecticut",12757.633,12976.05,3565.944,192.711,29492.338 "Maine",4480.736,4053.188,3027.135,0,11561.059 "Massachusetts",20313.469,17722.811,16927.205,349.839,55313.324 "New Hampshire",4439.208,4478.42,1952.633,0,10870.261 "Rhode Island",3121.367,3639.866,923.478,23.623,7708.334 "Vermont",2095.283,1993.892,1421.589,0,5510.764 "Middle Atlantic",132230.522,157278.208,69506.519,3910.06,362925.309

129

Thousand Oaks, California: Energy Resources | Open Energy Information  

Open Energy Info (EERE)

Thousand Oaks, California: Energy Resources Thousand Oaks, California: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.1705609°, -118.8375937° 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":34.1705609,"lon":-118.8375937,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

130

Probabilistic manpower forecasting  

E-Print Network [OSTI]

- ing E. Results- Probabilistic Forecasting . 26 27 Z8 29 31 35 36 38 39 IV. CONCLUSIONS. V. GLOSSARY 42 44 APPENDICES REFERENCES 50 70 LIST OF TABLES Table Page Outline of Job-Probability Matrix Job-Probability Matrix. Possible... Outcomes of Job A Possible Outcomes of Jobs A and B 10 Possible Outcomes of Jobs A, B and C II LIST GF FIGURES Figure Page Binary Representation of Numbers 0 Through 7 12 First Cumulative Probability Table 14 3. Graph of Cumulative Probability vs...

Koonce, James Fitzhugh

1966-01-01T23:59:59.000Z

131

Diagnosing Forecast Errors in Tropical Cyclone Motion  

Science Journals Connector (OSTI)

This paper reports on the development of a diagnostic approach that can be used to examine the sources of numerical model forecast error that contribute to degraded tropical cyclone (TC) motion forecasts. Tropical cyclone motion forecasts depend ...

Thomas J. Galarneau Jr.; Christopher A. Davis

2013-02-01T23:59:59.000Z

132

Louisiana Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Louisiana Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.19 0.19 0.19 1970's 0.19 0.20 0.20 0.22 0.31 0.42 0.46 0.70 0.84 1.11 1980's 1.61 2.07 2.60 2.67 2.73 2.66 2.21 1.78 1.81 1.82 1990's 1.83 1.73 1.73 2.14 2.08 1.58 2.33 2.36 2.02 2.22 2000's 3.68 3.99 3.20 5.64 5.96 8.72 6.93 7.02 8.73 3.82 2010's 4.23 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Louisiana Natural Gas Prices

133

Colorado Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Colorado Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.13 0.13 0.14 1970's 0.15 0.16 0.16 0.18 0.20 0.26 0.48 0.81 0.84 1.41 1980's 1.47 1.97 3.17 3.38 3.43 2.90 2.05 1.76 1.59 1.52 1990's 1.55 1.41 1.37 1.61 1.39 0.95 1.37 2.23 1.90 2.18 2000's 3.67 3.84 2.41 4.54 5.21 7.43 6.12 4.57 6.94 3.21 2010's 3.96 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Colorado Natural Gas Prices

134

Kansas Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Kansas Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.13 0.14 0.14 1970's 0.14 0.14 0.14 0.16 0.17 0.17 0.42 0.48 0.57 0.76 1980's 0.77 0.92 1.51 1.57 1.49 1.27 1.21 1.15 1.36 1.44 1990's 1.56 1.37 1.54 1.80 1.60 1.36 1.92 2.05 1.70 1.80 2000's 3.21 3.66 2.61 4.33 4.94 6.51 5.61 5.69 6.85 3.16 2010's 4.23 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Kansas Natural Gas Prices

135

Michigan Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Michigan Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.25 0.25 0.26 1970's 0.27 0.26 0.31 0.39 0.50 0.63 0.89 1.01 1.20 1.74 1980's 2.35 2.86 3.19 3.58 3.76 3.60 3.60 3.24 3.18 3.16 1990's 3.00 2.79 2.71 2.38 1.96 1.67 2.21 2.19 1.77 1.77 2000's 2.44 3.47 2.16 4.01 3.85 5.30 NA NA 5.63 3.92 2010's 3.79 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Michigan Natural Gas Prices

136

Kentucky Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Kentucky Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.24 0.25 0.25 1970's 0.25 0.25 0.25 0.35 0.50 0.54 0.55 0.55 0.58 0.95 1980's 0.89 1.01 1.52 1.51 1.70 2.39 1.88 1.82 2.56 2.13 1990's 2.24 2.03 1.92 2.28 2.24 1.64 2.55 2.66 2.39 2.07 2000's 3.16 4.78 3.01 4.54 5.26 6.84 8.83 7.35 8.42 NA 2010's 4.47 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Kentucky Natural Gas Prices

137

Alabama Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Alabama Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.13 0.13 0.13 1970's 0.14 0.15 0.35 0.38 0.74 0.87 0.99 1.47 1.50 2.04 1980's 3.19 4.77 3.44 4.28 3.73 3.71 2.89 2.97 2.65 2.72 1990's 2.75 2.33 2.29 2.46 2.17 1.82 2.62 2.67 2.21 2.32 2000's 3.99 4.23 3.48 5.93 6.66 9.28 7.57 7.44 9.65 4.32 2010's 4.46 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Alabama Natural Gas Prices

138

Wyoming Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Wyoming Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.15 0.15 0.15 1970's 0.15 0.15 0.16 0.18 0.25 0.34 0.41 0.64 0.79 1.13 1980's 1.92 2.77 3.22 3.18 3.32 3.01 2.52 1.76 1.53 1.24 1990's 1.16 1.06 1.13 1.99 2.05 1.78 2.57 2.42 1.78 1.97 2000's 3.34 3.49 2.70 4.13 4.96 6.86 5.85 4.65 6.86 3.40 2010's 4.30 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Wyoming Natural Gas Prices

139

Oklahoma Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Oklahoma Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.14 0.14 0.15 1970's 0.16 0.16 0.16 0.19 0.28 0.32 0.50 0.79 0.90 1.12 1980's 1.51 1.88 2.74 2.83 2.72 2.47 1.71 1.47 1.55 1.59 1990's 1.57 1.47 1.70 1.88 1.70 1.44 2.21 2.32 1.77 2.05 2000's 3.63 4.03 2.94 4.97 5.52 7.21 6.32 6.24 7.56 3.53 2010's 4.71 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Oklahoma Natural Gas Prices

140

Montana Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Montana Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.08 0.09 0.10 1970's 0.10 0.12 0.12 0.24 0.25 0.43 0.45 0.72 0.85 1.21 1980's 1.45 1.91 2.15 2.41 2.46 2.39 2.05 1.80 1.70 1.55 1990's 1.79 1.66 1.62 1.55 1.46 1.36 1.41 1.59 1.53 1.68 2000's 2.84 3.12 2.39 3.73 4.51 6.57 5.53 5.72 7.50 3.16 2010's 3.64 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Montana Natural Gas Prices

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141

Ohio Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Ohio Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.24 0.25 0.26 1970's 0.27 0.34 0.39 0.43 0.48 0.71 1.02 1.40 1.57 1.81 1980's 1.98 2.17 2.71 3.24 3.19 3.08 2.84 2.58 2.55 2.55 1990's 2.54 2.38 2.35 2.46 2.43 2.33 2.63 2.70 2.95 2.43 2000's 4.06 4.54 4.52 5.90 6.65 9.03 7.75 7.59 7.88 4.36 2010's 4.63 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Ohio Natural Gas Prices Natural Gas Wellhead

142

Alaska Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Alaska Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.25 0.25 0.25 1970's 0.25 0.24 0.15 0.15 0.17 0.30 0.39 0.40 0.52 0.52 1980's 0.73 0.62 0.63 0.73 0.73 0.74 0.50 0.94 1.27 1.36 1990's 1.38 1.48 1.41 1.42 1.27 1.64 1.61 1.82 1.32 1.37 2000's 1.76 1.99 2.13 2.41 3.42 4.75 5.79 5.63 7.39 2.93 2010's 3.17 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Alaska Natural Gas Prices

143

Utah Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Utah Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.13 0.16 0.15 1970's 0.15 0.17 0.17 0.19 0.41 0.48 0.50 0.61 0.64 0.72 1980's 1.12 1.10 3.06 3.40 4.08 3.52 2.90 1.88 2.39 1.58 1990's 1.70 1.54 1.63 1.77 1.54 1.15 1.39 1.86 1.73 1.93 2000's 3.28 3.52 1.99 4.11 5.24 7.16 5.49 NA 6.15 3.38 2010's 4.23 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Utah Natural Gas Prices Natural Gas Wellhead

144

Indiana Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Indiana Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.23 0.24 0.23 1970's 0.24 0.25 0.15 0.14 0.14 0.39 0.52 0.69 0.71 1.05 1980's 1.35 2.08 1.55 2.09 3.38 2.51 1.23 1.71 1.57 1.71 1990's 2.01 1.72 2.01 2.09 1.97 1.90 2.30 2.18 2.09 2.19 2000's 3.51 3.28 3.11 5.41 6.30 9.11 6.01 5.78 7.58 4.05 2010's 4.13 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Indiana Natural Gas Prices

145

Arkansas Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Arkansas Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.15 0.16 0.16 1970's 0.16 0.17 0.17 0.18 0.26 0.35 0.53 0.58 0.75 0.96 1980's 0.70 1.81 2.13 2.29 2.54 2.55 2.51 2.29 1.94 2.41 1990's 2.06 1.92 2.15 2.81 2.65 3.02 3.82 4.03 3.92 4.10 2000's 5.23 4.99 4.43 5.17 5.68 7.26 6.43 6.61 8.72 3.43 2010's 3.84 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Arkansas Natural Gas Prices

146

Texas Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Texas Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.13 0.14 0.14 1970's 0.14 0.16 0.16 0.20 0.31 0.52 0.72 0.90 0.99 1.23 1980's 1.56 1.87 2.17 2.36 2.45 2.33 1.65 1.47 1.51 1.53 1990's 1.57 1.59 1.77 2.09 1.89 1.61 2.29 2.48 2.06 2.31 2000's 3.93 4.12 3.16 5.18 5.83 7.55 6.60 6.98 8.51 3.81 2010's 4.70 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Texas Natural Gas Prices Natural Gas Wellhead

147

Mississippi Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Mississippi Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.17 0.17 0.18 1970's 0.18 0.21 0.27 0.23 0.29 0.50 0.71 0.73 1.15 1.60 1980's 2.32 3.21 3.91 3.78 3.47 3.17 2.13 1.94 1.86 1.97 1990's 1.76 1.66 1.64 1.73 1.49 1.24 1.66 1.73 1.42 1.63 2000's 3.30 3.93 3.06 5.13 5.83 8.54 6.84 6.70 8.80 3.73 2010's 4.17 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Mississippi Natural Gas Prices

148

Maryland Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) Maryland Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.26 0.26 0.25 1970's 0.25 0.24 0.21 0.23 0.24 0.27 0.32 0.39 0.61 1.04 1980's 0.46 0.48 0.78 0.55 0.55 0.59 0.65 0.55 0.93 0.85 1990's 1.14 1.55 1.91 2.44 1.37 1.42 2.23 2.60 2.73 2000's 3.75 4.15 5.98 4.50 6.25 7.43 NA NA NA NA 2010's NA - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price Maryland Natural Gas Prices Natural Gas Wellhead

149

Project Profile: Forecasting and Influencing Technological Progress...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Forecasting and Influencing Technological Progress in Solar Energy Project Profile: Forecasting and Influencing Technological Progress in Solar Energy Logos of the University of...

150

Forecasting with adaptive extended exponential smoothing  

Science Journals Connector (OSTI)

Much of product level forecasting is based upon time series techniques. However, traditional time series forecasting techniques have offered either smoothing constant adaptability or consideration of various t...

John T. Mentzer Ph.D.

151

Electricity price forecasting in a grid environment.  

E-Print Network [OSTI]

??Accurate electricity price forecasting is critical to market participants in wholesale electricity markets. Market participants rely on price forecasts to decide their bidding strategies, allocate… (more)

Li, Guang, 1974-

2007-01-01T23:59:59.000Z

152

Energy Department Forecasts Geothermal Achievements in 2015 ...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Forecasts Geothermal Achievements in 2015 Energy Department Forecasts Geothermal Achievements in 2015 The 40th annual Stanford Geothermal Workshop in January featured speakers in...

153

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation by Susan H. Holte In this paper, the Office of Integrated Analysis and Forecasting (OIAF) of the Energy Information Administration (EIA) evaluates the projections published in the Annual Energy Outlook (AEO), (1) by comparing the projections from the Annual Energy Outlook 1982 through the Annual Energy Outlook 2001 with actual historical values. A set of major consumption, production, net import, price, economic, and carbon dioxide emissions variables are included in the evaluation, updating similar papers from previous years. These evaluations also present the reasons and rationales for significant differences. The Office of Integrated Analysis and Forecasting has been providing an

154

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Title of Paper Annual Energy Outlook Forecast Evaluation Title of Paper Annual Energy Outlook Forecast Evaluation by Susan H. Holte OIAF has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Natural gas has generally been the fuel with the least accurate forecasts of consumption, production, and prices. Natural gas was the last fossil fuel to be deregulated following the strong regulation of energy markets in the 1970s and early 1980s. Even after deregulation, the behavior

155

Correcting and combining time series forecasters  

Science Journals Connector (OSTI)

Combined forecasters have been in the vanguard of stochastic time series modeling. In this way it has been usual to suppose that each single model generates a residual or prediction error like a white noise. However, mostly because of disturbances not ... Keywords: Artificial neural networks hybrid systems, Linear combination of forecasts, Maximum likelihood estimation, Time series forecasters, Unbiased forecasters

Paulo Renato A. Firmino; Paulo S. G. De Mattos Neto; Tiago A. E. Ferreira

2014-02-01T23:59:59.000Z

156

NOAA Harmful Algal Bloom Operational Forecast System Southwest Florida Forecast Region Maps  

E-Print Network [OSTI]

Bloom Operational Forecast System Southwest Florida Forecast Region Maps 0 5 102.5 Miles #12;Bay Harmful Algal Bloom Operational Forecast System Southwest Florida Forecast Region Maps 0 5 102.5 Miles #12 N Collier N Charlotte S Charlotte NOAA Harmful Algal Bloom Operational Forecast System Southwest

157

DOE - Office of Legacy Management -- Queen City Barrel Co - OH 41  

Office of Legacy Management (LM)

Queen City Barrel Co - OH 41 Queen City Barrel Co - OH 41 FUSRAP Considered Sites Site: QUEEN CITY BARREL CO. (OH.41) Eliminated from further consideration under FUSRAP Designated Name: Not Designated Alternate Name: None Location: Cincinnati , Ohio OH.41-1 Evaluation Year: 1987 OH.41-1 Site Operations: Cleaned and reconditioned 30- and 55-gallon drums. OH.41-2 OH.41-3 Site Disposition: Eliminated - Based upon limited scope of operations, potential for residual radioactive contamination from MED or AEC operations considered remote OH.41-1 Radioactive Materials Handled: Yes OH.41-2 Primary Radioactive Materials Handled: Radium Bearing Material OH.41-2 OH.41-3 Radiological Survey(s): None Indicated Site Status: Eliminated from further consideration under FUSRAP Also see

158

Forecast Energy | Open Energy Information  

Open Energy Info (EERE)

Forecast Energy Forecast Energy Jump to: navigation, search Name Forecast Energy Address 2320 Marinship Way, Suite 300 Place Sausalito, California Zip 94965 Sector Services Product Intelligent Monitoring and Forecasting Services Year founded 2010 Number of employees 11-50 Company Type For profit Website http://www.forecastenergy.net Coordinates 37.865647°, -122.496315° 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":37.865647,"lon":-122.496315,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

159

Price forecasting for notebook computers  

E-Print Network [OSTI]

This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a series of time periods, and the rates of change in the influence...

Rutherford, Derek Paul

2012-06-07T23:59:59.000Z

160

Forecasting phenology under global warming  

Science Journals Connector (OSTI)

...Forrest Forecasting phenology under global warming Ines Ibanez 1 * Richard B. Primack...and site-specific responses to global warming. We found that for most species...climate change|East Asia, global warming|growing season, hierarchical...

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast thousand barrels" 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

Demand Forecasting of New Products  

E-Print Network [OSTI]

Keeping Unit or SKU) employing attribute analysis techniques. The objective of this thesis is to improve Abstract This thesis is a study into the demand forecasting of new products (also referred to as Stock

Sun, Yu

162

U.S. Nominal Cost per Dry Well Drilled (Thousand Dollars per...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Dry Well Drilled (Thousand Dollars per Well) U.S. Nominal Cost per Dry Well Drilled (Thousand Dollars per Well) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7...

163

U.S. Nominal Cost per Natural Gas Well Drilled (Thousand Dollars...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Natural Gas Well Drilled (Thousand Dollars per Well) U.S. Nominal Cost per Natural Gas Well Drilled (Thousand Dollars per Well) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

164

U.S. Nominal Cost per Crude Oil Well Drilled (Thousand Dollars...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Oil Well Drilled (Thousand Dollars per Well) U.S. Nominal Cost per Crude Oil Well Drilled (Thousand Dollars per Well) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7...

165

U.S. Footage Drilled for Natural Gas Exploratory Wells (Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Wells (Thousand Feet) U.S. Footage Drilled for Natural Gas Exploratory Wells (Thousand Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1940's...

166

U.S. Footage Drilled for Natural Gas Developmental Wells (Thousand...  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Developmental Wells (Thousand Feet) U.S. Footage Drilled for Natural Gas Developmental Wells (Thousand Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

167

Fact #841: October 6, 2014 Vehicles per Thousand People: U.S...  

Broader source: Energy.gov (indexed) [DOE]

41: October 6, 2014 Vehicles per Thousand People: U.S. vs. Other World Regions - Dataset Fact 841: October 6, 2014 Vehicles per Thousand People: U.S. vs. Other World Regions -...

168

U.S. Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic...  

Gasoline and Diesel Fuel Update (EIA)

Vehicle Fuel Price (Dollars per Thousand Cubic Feet) U.S. Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

169

Weather forecasting : the next generation : the potential use and implementation of ensemble forecasting  

E-Print Network [OSTI]

This thesis discusses ensemble forecasting, a promising new weather forecasting technique, from various viewpoints relating not only to its meteorological aspects but also to its user and policy aspects. Ensemble forecasting ...

Goto, Susumu

2007-01-01T23:59:59.000Z

170

Property:Res rev (thousand $) | Open Energy Information  

Open Energy Info (EERE)

residential customers. residential customers. Pages using the property "Res rev (thousand $)" Showing 25 pages using this property. (previous 25) (next 25) 4 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - April 2008 + 3,675 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - August 2008 + 5,720 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - December 2008 + 5,629 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - February 2008 + 5,156 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - February 2009 + 6,100 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - January 2008 + 4,728 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - January 2009 + 6,009 +

171

Property:Oth rev (thousand $) | Open Energy Information  

Open Energy Info (EERE)

other consumers other consumers Pages using the property "Oth rev (thousand $)" Showing 25 pages using this property. (previous 25) (next 25) C Central Illinois Pub Serv Co (Illinois) EIA Revenue and Sales - April 2008 + 92 + Central Illinois Pub Serv Co (Illinois) EIA Revenue and Sales - December 2008 + 78 + Central Illinois Pub Serv Co (Illinois) EIA Revenue and Sales - February 2008 + 49 + Central Illinois Pub Serv Co (Illinois) EIA Revenue and Sales - February 2009 + 128 + Central Illinois Pub Serv Co (Illinois) EIA Revenue and Sales - January 2008 + 52 + Central Illinois Pub Serv Co (Illinois) EIA Revenue and Sales - January 2009 + 100 + Central Illinois Pub Serv Co (Illinois) EIA Revenue and Sales - June 2008 + 54 + Central Illinois Pub Serv Co (Illinois) EIA Revenue and Sales - March 2008 + 106 +

172

Property:Tot rev (thousand $) | Open Energy Information  

Open Energy Info (EERE)

all consumers all consumers Pages using the property "Tot rev (thousand $)" Showing 25 pages using this property. (previous 25) (next 25) 4 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - April 2008 + 6,790 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - August 2008 + 9,808 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - December 2008 + 8,997 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - February 2008 + 8,266 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - February 2009 + 9,363 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - January 2008 + 7,829 + 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales - January 2009 + 9,432 +

173

Wind Forecast Improvement Project Southern Study Area Final Report...  

Office of Environmental Management (EM)

Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern...

174

Applying Bayesian Forecasting to Predict New Customers' Heating Oil Demand.  

E-Print Network [OSTI]

??This thesis presents a new forecasting technique that estimates energy demand by applying a Bayesian approach to forecasting. We introduce our Bayesian Heating Oil Forecaster… (more)

Sakauchi, Tsuginosuke

2011-01-01T23:59:59.000Z

175

Determination of barreling curve in upsetting process by artificial neural networks  

Science Journals Connector (OSTI)

In this paper, an approach for prediction deformation of upsetting processes is developed. The approach combines the finite element method and Neural Network to view the resultant deformation changes in upsetting. Because real time deformation simulation ... Keywords: FEM, barreling, neural network(NN), prediction, train, upsetting

H. Mohammadi Majd; M. Poursina; K. H. Shirazi

2009-09-01T23:59:59.000Z

176

Solar Energy Market Forecast | Open Energy Information  

Open Energy Info (EERE)

Solar Energy Market Forecast Solar Energy Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast Agency/Company /Organization: United States Department of Energy Sector: Energy Focus Area: Solar Topics: Market analysis, Technology characterizations Resource Type: Publications Website: giffords.house.gov/DOE%20Perspective%20on%20Solar%20Market%20Evolution References: Solar Energy Market Forecast[1] Summary " Energy markets / forecasts DOE Solar America Initiative overview Capital market investments in solar Solar photovoltaic (PV) sector overview PV prices and costs PV market evolution Market evolution considerations Balance of system costs Silicon 'normalization' Solar system value drivers Solar market forecast Additional resources"

177

Summary Verification Measures and Their Interpretation for Ensemble Forecasts  

Science Journals Connector (OSTI)

Ensemble prediction systems produce forecasts that represent the probability distribution of a continuous forecast variable. Most often, the verification problem is simplified by transforming the ensemble forecast into probability forecasts for ...

A. Allen Bradley; Stuart S. Schwartz

2011-09-01T23:59:59.000Z

178

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: * Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the

179

Aggregate vehicle travel forecasting model  

SciTech Connect (OSTI)

This report describes a model for forecasting total US highway travel by all vehicle types, and its implementation in the form of a personal computer program. The model comprises a short-run, econometrically-based module for forecasting through the year 2000, as well as a structural, scenario-based longer term module for forecasting through 2030. The short-term module is driven primarily by economic variables. It includes a detailed vehicle stock model and permits the estimation of fuel use as well as vehicle travel. The longer-tenn module depends on demographic factors to a greater extent, but also on trends in key parameters such as vehicle load factors, and the dematerialization of GNP. Both passenger and freight vehicle movements are accounted for in both modules. The model has been implemented as a compiled program in the Fox-Pro database management system operating in the Windows environment.

Greene, D.L.; Chin, Shih-Miao; Gibson, R. [Tennessee Univ., Knoxville, TN (United States)

1995-05-01T23:59:59.000Z

180

Communication of uncertainty in temperature forecasts  

Science Journals Connector (OSTI)

We used experimental economics to test whether undergraduate students presented with a temperature forecast with uncertainty information in a table and bar graph format were able to use the extra information to interpret a given forecast. ...

Pricilla Marimo; Todd R. Kaplan; Ken Mylne; Martin Sharpe

Note: This page contains sample records for the topic "forecast thousand barrels" 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

FORECASTING THE ROLE OF RENEWABLES IN HAWAII  

E-Print Network [OSTI]

FORECASTING THE ROLE OF RENEWABLES IN HAWAII Jayant SathayeFORECASTING THE ROLF OF RENEWABLES IN HAWAII J Sa and Henrythe Conservation Role of Renewables November 18, 1980 Page 2

Sathaye, Jayant

2013-01-01T23:59:59.000Z

182

Massachusetts state airport system plan forecasts.  

E-Print Network [OSTI]

This report is a first step toward updating the forecasts contained in the 1973 Massachusetts State System Plan. It begins with a presentation of the forecasting techniques currently available; it surveys and appraises the ...

Mathaisel, Dennis F. X.

183

Antarctic Satellite Meteorology: Applications for Weather Forecasting  

Science Journals Connector (OSTI)

For over 30 years, weather forecasting for the Antarctic continent and adjacent Southern Ocean has relied on weather satellites. Significant advancements in forecasting skill have come via the weather satellite. The advent of the high-resolution ...

Matthew A. Lazzara; Linda M. Keller; Charles R. Stearns; Jonathan E. Thom; George A. Weidner

2003-02-01T23:59:59.000Z

184

Forecasting Water Use in Texas Cities  

E-Print Network [OSTI]

In this research project, a methodology for automating the forecasting of municipal daily water use is developed and implemented in a microcomputer program called WATCAL. An automated forecast system is devised by modifying the previously...

Shaw, Douglas T.; Maidment, David R.

185

Energy demand forecasting: industry practices and challenges  

Science Journals Connector (OSTI)

Accurate forecasting of energy demand plays a key role for utility companies, network operators, producers and suppliers of energy. Demand forecasts are utilized for unit commitment, market bidding, network operation and maintenance, integration of renewable ... Keywords: analytics, energy demand forecasting, machine learning, renewable energy sources, smart grids, smart meters

Mathieu Sinn

2014-06-01T23:59:59.000Z

186

Consensus Coal Production And Price Forecast For  

E-Print Network [OSTI]

Consensus Coal Production And Price Forecast For West Virginia: 2011 Update Prepared for the West December 2011 © Copyright 2011 WVU Research Corporation #12;#12;W.Va. Consensus Coal Forecast Update 2011 i Table of Contents Executive Summary 1 Recent Developments 3 Consensus Coal Production And Price Forecast

Mohaghegh, Shahab

187

Data Acquisition-Manipulation At Valley Of Ten Thousand Smokes Region Area  

Open Energy Info (EERE)

Ten Thousand Smokes Region Area Ten Thousand Smokes Region Area (Kodosky & Keith, 1993) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Data Acquisition-Manipulation At Valley Of Ten Thousand Smokes Region Area (Kodosky & Keith, 1993) Exploration Activity Details Location Valley Of Ten Thousand Smokes Region Area Exploration Technique Data Acquisition-Manipulation Activity Date Usefulness not indicated DOE-funding Unknown Notes Statistical analyses of geochemical data. References Lawrence G. Kodosky, Terry E. C. Keith (1993) Factors Controlling The Geochemical Evolution Of Fumarolic Encrustations, Valley Of Ten Thousand Smokes, Alaska Retrieved from "http://en.openei.org/w/index.php?title=Data_Acquisition-Manipulation_At_Valley_Of_Ten_Thousand_Smokes_Region_Area_(Kodosky_%26_Keith,_1993)&oldid=389784"

188

Vehicle Technologies Office: Fact #778: May 6, 2013 Vehicles per Thousand  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

8: May 6, 2013 8: May 6, 2013 Vehicles per Thousand Persons Rising Quickly in China and India to someone by E-mail Share Vehicle Technologies Office: Fact #778: May 6, 2013 Vehicles per Thousand Persons Rising Quickly in China and India on Facebook Tweet about Vehicle Technologies Office: Fact #778: May 6, 2013 Vehicles per Thousand Persons Rising Quickly in China and India on Twitter Bookmark Vehicle Technologies Office: Fact #778: May 6, 2013 Vehicles per Thousand Persons Rising Quickly in China and India on Google Bookmark Vehicle Technologies Office: Fact #778: May 6, 2013 Vehicles per Thousand Persons Rising Quickly in China and India on Delicious Rank Vehicle Technologies Office: Fact #778: May 6, 2013 Vehicles per Thousand Persons Rising Quickly in China and India on Digg

189

Water Sampling At Valley Of Ten Thousand Smokes Region Area (Keith, Et Al.,  

Open Energy Info (EERE)

Of Ten Thousand Smokes Region Area (Keith, Et Al., Of Ten Thousand Smokes Region Area (Keith, Et Al., 1992) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Water Sampling At Valley Of Ten Thousand Smokes Region Area (Keith, Et Al., 1992) Exploration Activity Details Location Valley Of Ten Thousand Smokes Region Area Exploration Technique Water Sampling Activity Date Usefulness not indicated DOE-funding Unknown References T. E. C. Keith, J. M. Thompson, R. A. Hutchinson, L. D. White (1992) Geochemistry Of Waters In The Valley Of Ten Thousand Smokes Region, Alaska Retrieved from "http://en.openei.org/w/index.php?title=Water_Sampling_At_Valley_Of_Ten_Thousand_Smokes_Region_Area_(Keith,_Et_Al.,_1992)&oldid=386869" Categories: Exploration Activities DOE Funded Activities

190

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Evaluation Evaluation Annual Energy Outlook Forecast Evaluation by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the impacts were not incorporated in the AEO projections until their enactment or effective dates in accordance with EIA's requirement to remain policy neutral and include only current laws and regulations in the AEO reference case projections.

191

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Analysis Papers > Annual Energy Outlook Forecast Evaluation Analysis Papers > Annual Energy Outlook Forecast Evaluation Release Date: February 2005 Next Release Date: February 2006 Printer-friendly version Annual Energy Outlook Forecast Evaluation* Table 1.Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Printer Friendly Version Average Absolute Percent Error Variable AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 AEO82 to AEO2003 AEO82 to AEO2004 Consumption Total Energy Consumption 1.9 2.0 2.1 2.1 2.1 2.1 Total Petroleum Consumption 2.9 3.0 3.1 3.1 3.0 2.9 Total Natural Gas Consumption 7.3 7.1 7.1 6.7 6.4 6.5 Total Coal Consumption 3.1 3.3 3.5 3.6 3.7 3.8 Total Electricity Sales 1.9 2.0 2.3 2.3 2.3 2.4 Production Crude Oil Production 4.5 4.5 4.5 4.5 4.6 4.7

192

Load Forecasting of Supermarket Refrigeration  

E-Print Network [OSTI]

energy system. Observed refrigeration load and local ambient temperature from a Danish su- permarket renewable energy, is increasing, therefore a flexible energy system is needed. In the present ThesisLoad Forecasting of Supermarket Refrigeration Lisa Buth Rasmussen Kongens Lyngby 2013 M.Sc.-2013

193

Essays on macroeconomics and forecasting  

E-Print Network [OSTI]

explanatory variables. Compared to Stock and Watson (2002)�s models, the models proposed in this chapter can further allow me to select the factors structurally for each variable to be forecasted. I find advantages to using the structural dynamic factor...

Liu, Dandan

2006-10-30T23:59:59.000Z

194

U.S. monthly oil production tops 8 million barrels per day for...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Several companies plan to build U.S. terminals to export liquefied natural gas, or LNG, to Europe and Asia. EIA's revised forecast reflects one of those LNG export terminals...

195

Forecasting-based SKU classification  

Science Journals Connector (OSTI)

Different spare parts are associated with different underlying demand patterns, which in turn require different forecasting methods. Consequently, there is a need to categorise stock keeping units (SKUs) and apply the most appropriate methods in each category. For intermittent demands, Croston's method (CRO) is currently regarded as the standard method used in industry to forecast the relevant inventory requirements; this is despite the bias associated with Croston's estimates. A bias adjusted modification to CRO (Syntetos–Boylan Approximation, SBA) has been shown in a number of empirical studies to perform very well and be associated with a very ‘robust’ behaviour. In a 2005 article, entitled ‘On the categorisation of demand patterns’ published by the Journal of the Operational Research Society, Syntetos et al. (2005) suggested a categorisation scheme, which establishes regions of superior forecasting performance between CRO and SBA. The results led to the development of an approximate rule that is expressed in terms of fixed cut-off values for the following two classification criteria: the squared coefficient of variation of the demand sizes and the average inter-demand interval. Kostenko and Hyndman (2006) revisited this issue and suggested an alternative scheme to distinguish between CRO and SBA in order to improve overall forecasting accuracy. Claims were made in terms of the superiority of the proposed approach to the original solution but this issue has never been assessed empirically. This constitutes the main objective of our work. In this paper the above discussed classification solutions are compared by means of experimentation on more than 10,000 \\{SKUs\\} from three different industries. The results enable insights to be gained into the comparative benefits of these approaches. The trade-offs between forecast accuracy and other implementation related considerations are also addressed.

G. Heinecke; A.A. Syntetos; W. Wang

2013-01-01T23:59:59.000Z

196

Fact #676: May 23, 2011 U.S. Refiners Produce about 19 Gallons of Gasoline from a Barrel of Oil  

Broader source: Energy.gov [DOE]

A standard U.S. barrel contains 42 gallons of crude oil which yields about 44 gallons of petroleum products. The additional 2 gallons of petroleum products come from refiner gains which result in...

197

Forecasting wind speed financial return  

E-Print Network [OSTI]

The prediction of wind speed is very important when dealing with the production of energy through wind turbines. In this paper, we show a new nonparametric model, based on semi-Markov chains, to predict wind speed. Particularly we use an indexed semi-Markov model that has been shown to be able to reproduce accurately the statistical behavior of wind speed. The model is used to forecast, one step ahead, wind speed. In order to check the validity of the model we show, as indicator of goodness, the root mean square error and mean absolute error between real data and predicted ones. We also compare our forecasting results with those of a persistence model. At last, we show an application of the model to predict financial indicators like the Internal Rate of Return, Duration and Convexity.

D'Amico, Guglielmo; Prattico, Flavio

2013-01-01T23:59:59.000Z

198

Weather Forecast Data an Important Input into Building Management Systems  

E-Print Network [OSTI]

Lewis Poulin Implementation and Operational Services Section Canadian Meteorological Centre, Dorval, Qc National Prediction Operations Division ICEBO 2013, Montreal, Qc October 10 2013 Version 2013-09-27 Weather Forecast Data An Important... and weather information ? Numerical weather forecast production 101 ? From deterministic to probabilistic forecasts ? Some MSC weather forecast (NWP) datasets ? Finding the appropriate data for the appropriate forecast ? Preparing for probabilistic...

Poulin, L.

2013-01-01T23:59:59.000Z

199

The design and performance of a twenty barrel hydrogen pellet injector for Alcator C-Mod  

SciTech Connect (OSTI)

A twenty barrel hydrogen pellet injector has been designed, built and tested both in the laboratory and on the Alcator C-Mod Tokamak at MIT. The injector functions by firing pellets of frozen hydrogen or deuterium deep into the plasma discharge for the purpose of fueling the plasma, modifying the density profile and increasing the global energy confinement time. The design goals of the injector are: (1) Operational flexibility, (2) High reliability, (3) Remote operation with minimal maintenance. These requirements have lead to a single stage, pipe gun design with twenty barrels. Pellets are formed by in- situ condensation of the fuel gas, thus avoiding moving parts at cryogenic temperatures. The injector is the first to dispense with the need for cryogenic fluids and instead uses a closed cycle refrigerator to cool the thermal system components. The twenty barrels of the injector produce pellets of four different size groups and allow for a high degree of flexibility in fueling experiments. Operation of the injector is under PLC control allowing for remote operation, interlocked safety features and automated pellet manufacturing. The injector has been extrusively tested and shown to produce pellets reliably with velocities up to 1400 m/sec. During the period from September to November of 1993, the injector was successfully used to fire pellets into over fifty plasma discharges. Experimental results include data on the pellet penetration into the plasma using an advanced pellet tracking diagnostic with improved time and spatial response. Data from the tracker indicates pellet penetrations were between 30 and 86 percent of the plasma minor radius.

Urbahn, J.A.

1994-05-01T23:59:59.000Z

200

BMA Probabilistic Quantitative Precipitation Forecasting over the Huaihe Basin Using TIGGE Multimodel Ensemble Forecasts  

Science Journals Connector (OSTI)

Bayesian model averaging (BMA) probability quantitative precipitation forecast (PQPF) models were established by calibrating their parameters using 1–7-day ensemble forecasts of 24-h accumulated precipitation, and observations from 43 ...

Jianguo Liu; Zhenghui Xie

2014-04-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast thousand barrels" 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

Calibrated Precipitation Forecasts for a Limited-Area Ensemble Forecast System Using Reforecasts  

Science Journals Connector (OSTI)

The calibration of numerical weather forecasts using reforecasts has been shown to increase the skill of weather predictions. Here, the precipitation forecasts from the Consortium for Small Scale Modeling Limited Area Ensemble Prediction System (...

Felix Fundel; Andre Walser; Mark A. Liniger; Christoph Frei; Christof Appenzeller

2010-01-01T23:59:59.000Z

202

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

H Tables H Tables Appendix H Comparisons With Other Forecasts, and Performance of Past IEO Forecasts for 1990, 1995, and 2000 Forecast Comparisons Three organizations provide forecasts comparable with those in the International Energy Outlook 2005 (IEO2005). The International Energy Agency (IEA) provides “business as usual” projections to the year 2030 in its World Energy Outlook 2004; Petroleum Economics, Ltd. (PEL) publishes world energy forecasts to 2025; and Petroleum Industry Research Associates (PIRA) provides projections to 2015. For this comparison, 2002 is used as the base year for all the forecasts, and the comparisons extend to 2025. Although IEA’s forecast extends to 2030, it does not publish a projection for 2025. In addition to forecasts from other organizations, the IEO2005 projections are also compared with those in last year’s report (IEO2004). Because 2002 data were not available when IEO2004 forecasts were prepared, the growth rates from IEO2004 are computed from 2001.

203

Funding Opportunity Announcement for Wind Forecasting Improvement...  

Office of Environmental Management (EM)

to improved forecasts, system operators and industry professionals can ensure that wind turbines will operate at their maximum potential. Data collected during this field...

204

Upcoming Funding Opportunity for Wind Forecasting Improvement...  

Office of Environmental Management (EM)

to improved forecasts, system operators and industry professionals can ensure that wind turbines will operate at their maximum potential. Data collected during this field...

205

Huge market forecast for linear LDPE  

Science Journals Connector (OSTI)

Huge market forecast for linear LDPE ... It now appears that the success of the new technology, which rests largely on energy and equipment cost savings, could be overwhelming. ...

1980-08-25T23:59:59.000Z

206

NOAA GREAT LAKES COASTAL FORECASTING SYSTEM Forecasts (up to 5 days in the future)  

E-Print Network [OSTI]

conditions for up to 5 days in the future. These forecasts are run twice daily, and you can step through are generated every 6 hours and you can step backward in hourly increments to view conditions over the previousNOAA GREAT LAKES COASTAL FORECASTING SYSTEM Forecasts (up to 5 days in the future) and Nowcasts

207

,"Texas Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_stx_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_stx_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

208

,"Oregon Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oregon Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sor_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sor_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

209

,"Mississippi Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sms_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sms_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

210

,"Michigan Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_smi_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_smi_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

211

,"Arkansas Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Arkansas Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sar_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sar_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

212

,"Nebraska Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Nebraska Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sne_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sne_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

213

,"Utah Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sut_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sut_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

214

,"California Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sca_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sca_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

215

,"South Dakota Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","South Dakota Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_ssd_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_ssd_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

216

,"Kentucky Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sky_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sky_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

217

,"Colorado Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sco_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sco_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

218

,"Missouri Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Missouri Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",1997 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_smo_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_smo_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

219

,"Pennsylvania Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_spa_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_spa_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

220

,"Iowa Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Iowa Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035ia3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035ia3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

Note: This page contains sample records for the topic "forecast thousand barrels" 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

,"Alabama Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alabama Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sal_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sal_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

222

,"Maryland Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Maryland Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_smd_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_smd_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

223

,"Oklahoma Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sok_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sok_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

224

,"Illinois Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035il3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035il3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

225

,"Indiana Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Indiana Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sin_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sin_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

226

,"Illinois Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sil_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sil_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

227

,"Washington Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Washington Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_swa_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_swa_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

228

,"Pennsylvania Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_spa_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_spa_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

229

,"Minnesota Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Minnesota Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_smn_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_smn_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

230

,"Arizona Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Arizona Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_saz_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_saz_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

231

,"Florida Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sfl_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sfl_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

232

,"South Dakota Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","South Dakota Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_ssd_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_ssd_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

233

,"Mississippi Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sms_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sms_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

234

,"Louisiana Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sla_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sla_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

235

,"Massachusetts Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Massachusetts Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sma_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sma_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

236

,"Wisconsin Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Wisconsin Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_swi_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_swi_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

237

,"Alaska Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alaska Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sak_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sak_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

238

,"Ohio Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_soh_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_soh_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

239

,"California Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sca_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sca_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

240

,"Wyoming Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_swy_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_swy_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

Note: This page contains sample records for the topic "forecast thousand barrels" 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

,"Kansas Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_sks_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_sks_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

242

,"Montana Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_smt_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_smt_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

243

,"Tennessee Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)"  

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

Wellhead Price (Dollars per Thousand Cubic Feet)" Wellhead Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Tennessee Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)",1,"Annual",2010 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1140_stn_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1140_stn_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

244

,"South Carolina Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","South Carolina Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_ssc_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_ssc_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

245

,"Louisiana Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sla_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sla_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

246

Annual Energy Outlook Forecast Evaluation - Table 1. Forecast Evaluations:  

Gasoline and Diesel Fuel Update (EIA)

Average Absolute Percent Errors from AEO Forecast Evaluations: Average Absolute Percent Errors from AEO Forecast Evaluations: 1996 to 2000 Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Variable 1996 Evaluation: AEO82 to AEO93 1997 Evaluation: AEO82 to AEO97 1998 Evaluation: AEO82 to AEO98 1999 Evaluation: AEO82 to AEO99 2000 Evaluation: AEO82 to AEO2000 Consumption Total Energy Consumption 1.8 1.6 1.7 1.7 1.8 Total Petroleum Consumption 3.2 2.8 2.9 2.8 2.9 Total Natural Gas Consumption 6.0 5.8 5.7 5.6 5.6 Total Coal Consumption 2.9 2.7 3.0 3.2 3.3 Total Electricity Sales 1.8 1.6 1.7 1.8 2.0 Production Crude Oil Production 5.1 4.2 4.3 4.5 4.5

247

Optimal combined wind power forecasts using exogeneous variables  

E-Print Network [OSTI]

Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

248

Ensemble typhoon quantitative precipitation forecasts model in Taiwan  

Science Journals Connector (OSTI)

In this study, an ensemble typhoon quantitative precipitation forecast (ETQPF) model was developed to provide typhoon rainfall forecasts for Taiwan. The ETQPF rainfall forecast is obtained by averaging the pick-out cases, which are screened at a ...

Jing-Shan Hong; Chin-Tzu Fong; Ling-Feng Hsiao; Yi-Chiang Yu; Chian-You Tzeng

249

A New Four-Barrel Pellet Injection System for the TJ-II Stellarator  

SciTech Connect (OSTI)

A new pellet injection system for the TJ-II stellarator has been developed/constructed as part of a collaboration between the Oak Ridge National Laboratory (ORNL) and the Centro de Investigaciones Energ ticas, Medioambientales y Tecnol gicas (CIEMAT). ORNL is providing most of the injector hardware and instrumentation, the pellet diagnostics, and the pellet transport tubes; CIEMAT is responsible for the injector stand/interface to the stellarator, cryogenic refrigerator, vacuum pumps/ballast volumes, gas manifolds, remote operations, plasma diagnostics, and data acquisition. The pellet injector design is an upgraded version of that used for the ORNL injector installed on the Madison Symmetric Torus (MST). It is a four-barrel system equipped with a cryogenic refrigerator for in situ hydrogen pellet formation and a combined mechanical punch/propellant valve system for pellet acceleration (speeds ~100 to 1000 m/s). On TJ-II, it will be used as an active diagnostic and for fueling. To accommodate the plasma experiments planned for TJ-II, pellet sizes significantly smaller than those typically used for the MST application are required. The system will initially be equipped with four different pellet sizes, with the gun barrel bores ranging between ~0.5 to 1.0 mm. The new system is almost complete and is described briefly here, highlighting the new features added since the original MST injector was constructed. Also, the future installation on TJ-II is reviewed.

Combs, Stephen Kirk [ORNL] [ORNL; Foust, Charles R [ORNL] [ORNL; McGill, James M [ORNL] [ORNL; Baylor, Larry R [ORNL] [ORNL; Caughman, John B [ORNL] [ORNL; Fehling, Dan T [ORNL] [ORNL; Harris, Jeffrey H [ORNL] [ORNL; Meitner, Steven J [ORNL] [ORNL; Rasmussen, David A [ORNL] [ORNL; McCarthy, K. J. [EURATOM-CIEMAT, Madrid, Spain] [EURATOM-CIEMAT, Madrid, Spain; Chamorro, M. [Laboratory Nacional de Fusion, Madrid, Spain] [Laboratory Nacional de Fusion, Madrid, Spain; Garcia, R. [Laboratory Nacional de Fusion, Madrid, Spain] [Laboratory Nacional de Fusion, Madrid, Spain; Hildago, C. [Laboratory Nacional de Fusion, Madrid, Spain] [Laboratory Nacional de Fusion, Madrid, Spain; Medrano, M. [Laboratory Nacional de Fusion, Madrid, Spain] [Laboratory Nacional de Fusion, Madrid, Spain; Unamuno, R. [Laboratory Nacional de Fusion, Madrid, Spain] [Laboratory Nacional de Fusion, Madrid, Spain

2011-01-01T23:59:59.000Z

250

The Common Cryogenic Test Facility for the ATLAS Barrel and End-Cap Toroid Magnets  

SciTech Connect (OSTI)

The large ATLAS toroidal superconducting magnet made of the Barrel and two End-Caps needs extensive testing at the surface of the individual components prior to their final assembly into the underground cavern of LHC. A cryogenic test facility specifically designed for cooling sequentially the eight coils making the Barrel Toroid (BT) has been fully commissioned and is now ready for final acceptance of these magnets. This facility, originally designed for testing individually the 46 tons BT coils, will be upgraded to allow the acceptance tests of the two End-Caps, each of them having a 160 tons cold mass. The integrated system mainly comprises a 1.2 kW at 4.5 K refrigerator, a 10 kW liquid-nitrogen precooler, two cryostats housing liquid helium centrifugal pumps of respectively 80 g/s and 600 g/s nominal flow and specific instrumentation to measure the thermal performances of the magnets. This paper describes the overall facility with particular emphasis to the cryogenic features adopted to match the specific requirements of the magnets in the various operating scenarios.

Delruelle, N.; Haug, F.; Junker, S.; Passardi, G.; Pengo, R.; Pirotte, O. [CERN, AT division, 1211 Geneva 23 (Switzerland)

2004-06-23T23:59:59.000Z

251

Soil Sampling At Valley Of Ten Thousand Smokes Region Area (Kodosky &  

Open Energy Info (EERE)

Soil Sampling At Valley Of Ten Thousand Smokes Region Area (Kodosky & Soil Sampling At Valley Of Ten Thousand Smokes Region Area (Kodosky & Keith, 1993) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Soil Sampling At Valley Of Ten Thousand Smokes Region Area (Kodosky & Keith, 1993) Exploration Activity Details Location Valley Of Ten Thousand Smokes Region Area Exploration Technique Soil Sampling Activity Date Usefulness not indicated DOE-funding Unknown Notes The purpose of this paper is to examine whether statistical analysis of encrustation chemistries, when supplemented with petrologic data, can identify the individual processes that generate and degrade fumarolic encrustations. Knowledge of these specific processes broadens the applications of fumarolic alteration studies. Geochemical data for a

252

Geochemistry Of Waters In The Valley Of Ten Thousand Smokes Region, Alaska  

Open Energy Info (EERE)

Waters In The Valley Of Ten Thousand Smokes Region, Alaska Waters In The Valley Of Ten Thousand Smokes Region, Alaska Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Journal Article: Geochemistry Of Waters In The Valley Of Ten Thousand Smokes Region, Alaska Details Activities (3) Areas (1) Regions (0) Abstract: Meteoric waters from cold springs and streams outside of the 1912 eruptive deposits filling the Valley of Ten Thousand Smokes (VTTS) and in the upper parts of the two major rivers draining the 1912 deposits have similar chemical trends. Thermal springs issue in the mid-valley area along a 300-m lateral section of ash-flow tuff, and range in temperature from 21 to 29.8°C in early summer and from 15 to 17°C in mid-summer. Concentrations of major and minor chemical constituents in the thermal waters are nearly identical regardless of temperature. Waters in the

253

Mercury Vapor At Valley Of Ten Thousand Smokes Region Area (Kodosky, 1989)  

Open Energy Info (EERE)

Mercury Vapor At Valley Of Ten Thousand Smokes Region Area (Kodosky, 1989) Mercury Vapor At Valley Of Ten Thousand Smokes Region Area (Kodosky, 1989) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Mercury Vapor At Valley Of Ten Thousand Smokes Region Area (Kodosky, 1989) Exploration Activity Details Location Valley Of Ten Thousand Smokes Region Area Exploration Technique Mercury Vapor Activity Date Usefulness useful DOE-funding Unknown Notes One-hundred twelve samples were collected from relatively unaltered air-fall ejecta along two Novarupta Basin traverse lines (Fig. 5). One hundred eighty-two samples were taken from active/fossil fumaroles in Novarupta Basin (22 sites, Fig. 5), fossil fumaroles (41 sites) and air-fall tephra (2 sites) within and immediately adjacent to the remainder of the VTTS (Fig. 6). In total, 294 samples were collected from 127 sites

254

Fact #697: October 17, 2011 Comparison of Vehicles per Thousand People in Selected Countries/Regions  

Broader source: Energy.gov [DOE]

The U S. data for vehicles per thousand people are displayed in the line which goes from 1900 to 2009. The points labeled on that line show data for other countries/regions around the world and how...

255

Fact #841: October 6, 2014 Vehicles per Thousand People: U.S. vs. Other World Regions  

Broader source: Energy.gov [DOE]

The graphs below show the number of motor vehicles per thousand people for select countries and regions. The data for the United States are displayed in the line which goes from 1900 to 2012. The...

256

,"U.S. Natural Gas Electric Power Price (Dollars per Thousand...  

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

,,"(202) 586-8800",,,"1302015 12:55:12 PM" "Back to Contents","Data 1: U.S. Natural Gas Electric Power Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3045US3"...

257

,"U.S. Natural Gas Pipeline Imports Price (Dollars per Thousand...  

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

586-8800",,,"9262014 4:20:00 PM" "Back to Contents","Data 1: U.S. Natural Gas Pipeline Imports Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N9102US3" "Date","U.S....

258

,"U.S. Natural Gas Pipeline Imports Price (Dollars per Thousand...  

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

586-8800",,,"9262014 4:19:59 PM" "Back to Contents","Data 1: U.S. Natural Gas Pipeline Imports Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N9102US3" "Date","U.S....

259

Fact #745: September 17, 2012 Vehicles per Thousand People: U.S. Compared to Other Countries  

Broader source: Energy.gov [DOE]

The graphs below show the number of motor vehicles per thousand people for various countries. The data for the United States are displayed in the line which goes from 1900 to 2010. The points...

260

Soil Sampling At Valley Of Ten Thousand Smokes Region Area (Kodosky, 1989)  

Open Energy Info (EERE)

Valley Of Ten Thousand Smokes Region Area (Kodosky, 1989) Valley Of Ten Thousand Smokes Region Area (Kodosky, 1989) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Soil Sampling At Valley Of Ten Thousand Smokes Region Area (Kodosky, 1989) Exploration Activity Details Location Valley Of Ten Thousand Smokes Region Area Exploration Technique Soil Sampling Activity Date Usefulness useful DOE-funding Unknown Notes One-hundred twelve samples were collected from relatively unaltered air-fall ejecta along two Novarupta Basin traverse lines (Fig. 5). One hundred eighty-two samples were taken from active/fossil fumaroles in Novarupta Basin (22 sites, Fig. 5), fossil fumaroles (41 sites) and air-fall tephra (2 sites) within and immediately adjacent to the remainder of the VTTS (Fig. 6). In total, 294 samples were collected from 127 sites

Note: This page contains sample records for the topic "forecast thousand barrels" 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

Forecast of geothermal drilling activity  

SciTech Connect (OSTI)

The numbers of each type of geothermal well expected to be drilled in the United States for each 5-year period to 2000 AD are specified. Forecasts of the growth of geothermally supplied electric power and direct heat uses are presented. The different types of geothermal wells needed to support the forecasted capacity are quantified, including differentiation of the number of wells to be drilled at each major geothermal resource for electric power production. The rate of growth of electric capacity at geothermal resource areas is expected to be 15 to 25% per year (after an initial critical size is reached) until natural or economic limits are approached. Five resource areas in the United States should grow to significant capacity by the end of the century (The Geysers; Imperial Valley; Valles Caldera, NM; Roosevelt Hot Springs, UT; and northern Nevada). About 3800 geothermal wells are expected to be drilled in support of all electric power projects in the United States between 1981 and 2000 AD. Half of the wells are expected to be drilled in the Imperial Valley. The Geysers area is expected to retain most of the drilling activity for the next 5 years. By the 1990's, the Imperial Valley is expected to contain most of the drilling activity.

Brown, G.L.; Mansure, A.J.

1981-10-01T23:59:59.000Z

262

New Concepts in Wind Power Forecasting Models  

E-Print Network [OSTI]

New Concepts in Wind Power Forecasting Models Vladimiro Miranda, Ricardo Bessa, João Gama, Guenter to the training of mappers such as neural networks to perform wind power prediction as a function of wind for more accurate short term wind power forecasting models has led to solid and impressive development

Kemner, Ken

263

QUIKSCAT MEASUREMENTS AND ECMWF WIND FORECASTS  

E-Print Network [OSTI]

. (2004) this forecast error was encountered when assimilating satellite measurements of zonal wind speeds between satellite measurements and meteorological forecasts of near-surface ocean winds. This type of covariance enters in assimilation techniques such as Kalman filtering. In all, six residual fields

Malmberg, Anders

264

QUIKSCAT MEASUREMENTS AND ECMWF WIND FORECASTS  

E-Print Network [OSTI]

. (2004) this forecast error was encountered when assimilating satellite measurements of zonal wind speeds between satellite measurements and meteorological forecasts of near­surface ocean winds. This type of covariance enters in assimilation techniques such as Kalman filtering. In all, six residual fields

Malmberg, Anders

265

PROBLEMS OF FORECAST1 Dmitry KUCHARAVY  

E-Print Network [OSTI]

: Technology Forecast, Laws of Technical systems evolution, Analysis of Contradictions. 1. Introduction Let us: If technology forecasting practice remains at the present level, it is necessary to significantly improve to new demands (like Green House Gases - GHG Effect reduction or covering exploded nuclear reactor

Paris-Sud XI, Université de

266

UHERO FORECAST PROJECT DECEMBER 5, 2014  

E-Print Network [OSTI]

deficits. After solid 3% growth this year, real GDP growth will recede a bit for the next two years. New household spending. Real GDP will firm above 3% in 2015. · The pace of growth in China has continuedUHERO FORECAST PROJECT DECEMBER 5, 2014 Asia-Pacific Forecast: Press Version: Embargoed Until 2

267

Amending Numerical Weather Prediction forecasts using GPS  

E-Print Network [OSTI]

. Satellite images and Numerical Weather Prediction (NWP) models are used together with the synoptic surfaceAmending Numerical Weather Prediction forecasts using GPS Integrated Water Vapour: a case study to validate the amounts of humidity in Numerical Weather Prediction (NWP) model forecasts. This paper presents

Stoffelen, Ad

268

A Forecasting Support System Based on Exponential Smoothing  

Science Journals Connector (OSTI)

This chapter presents a forecasting support system based on the exponential smoothing scheme to forecast time-series data. Exponential smoothing methods are simple to apply, which facilitates...

Ana Corberán-Vallet; José D. Bermúdez; José V. Segura…

2010-01-01T23:59:59.000Z

269

ANL Software Improves Wind Power Forecasting | Department of...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

principal investigator for the project. For wind power point forecasting, ARGUS PRIMA trains a neural network using data from weather forecasts, observations, and actual wind...

270

Improved Prediction of Runway Usage for Noise Forecast :.  

E-Print Network [OSTI]

??The research deals with improved prediction of runway usage for noise forecast. Since the accuracy of the noise forecast depends on the robustness of runway… (more)

Dhanasekaran, D.

2014-01-01T23:59:59.000Z

271

The Wind Forecast Improvement Project (WFIP): A Public/Private...  

Energy Savers [EERE]

Improvement Project (WFIP): A PublicPrivate Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The Wind Forecast...

272

PBL FY 2002 Third Quarter Review Forecast of Generation Accumulated...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Power Business Line Generation Accumulated Net Revenues Forecast for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) FY 2002 Third Quarter Review Forecast in Millions...

273

An Investigation of an Interontologia: Comparison of the Thousand-Character Text and Roget’s Thesaurus  

Science Journals Connector (OSTI)

The present study presents the lexical category analysis of the Thousand-Character Text and Roget’s Thesaurus. Through preprocessing, the Thousand-Character Text and Roget’s Thesaurus have been built into databas...

Sang-Rak Kim; Jae-Gun Yang; Jae-Hak J. Bae

2009-01-01T23:59:59.000Z

274

1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.  

SciTech Connect (OSTI)

This publication documents the load forecast scenarios and assumptions used to prepare BPA`s Whitebook. It is divided into: intoduction, summary of 1993 Whitebook electricity demand forecast, conservation in the load forecast, projection of medium case electricity sales and underlying drivers, residential sector forecast, commercial sector forecast, industrial sector forecast, non-DSI industrial forecast, direct service industry forecast, and irrigation forecast. Four appendices are included: long-term forecasts, LTOUT forecast, rates and fuel price forecasts, and forecast ranges-calculations.

United States. Bonneville Power Administration.

1994-02-01T23:59:59.000Z

275

A hybrid procedure for MSW generation forecasting at multiple time scales in Xiamen City, China  

SciTech Connect (OSTI)

Highlights: ? We propose a hybrid model that combines seasonal SARIMA model and grey system theory. ? The model is robust at multiple time scales with the anticipated accuracy. ? At month-scale, the SARIMA model shows good representation for monthly MSW generation. ? At medium-term time scale, grey relational analysis could yield the MSW generation. ? At long-term time scale, GM (1, 1) provides a basic scenario of MSW generation. - Abstract: Accurate forecasting of municipal solid waste (MSW) generation is crucial and fundamental for the planning, operation and optimization of any MSW management system. Comprehensive information on waste generation for month-scale, medium-term and long-term time scales is especially needed, considering the necessity of MSW management upgrade facing many developing countries. Several existing models are available but of little use in forecasting MSW generation at multiple time scales. The goal of this study is to propose a hybrid model that combines the seasonal autoregressive integrated moving average (SARIMA) model and grey system theory to forecast MSW generation at multiple time scales without needing to consider other variables such as demographics and socioeconomic factors. To demonstrate its applicability, a case study of Xiamen City, China was performed. Results show that the model is robust enough to fit and forecast seasonal and annual dynamics of MSW generation at month-scale, medium- and long-term time scales with the desired accuracy. In the month-scale, MSW generation in Xiamen City will peak at 132.2 thousand tonnes in July 2015 – 1.5 times the volume in July 2010. In the medium term, annual MSW generation will increase to 1518.1 thousand tonnes by 2015 at an average growth rate of 10%. In the long term, a large volume of MSW will be output annually and will increase to 2486.3 thousand tonnes by 2020 – 2.5 times the value for 2010. The hybrid model proposed in this paper can enable decision makers to develop integrated policies and measures for waste management over the long term.

Xu, Lilai, E-mail: llxu@iue.ac.cn [Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen 361021 (China); Xiamen Key Lab of Urban Metabolism, Xiamen 361021 (China); Gao, Peiqing, E-mail: peiqing15@yahoo.com.cn [Xiamen City Appearance and Environmental Sanitation Management Office, 51 Hexiangxi Road, Xiamen 361004 (China); Cui, Shenghui, E-mail: shcui@iue.ac.cn [Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen 361021 (China); Xiamen Key Lab of Urban Metabolism, Xiamen 361021 (China); Liu, Chun, E-mail: xmhwlc@yahoo.com.cn [Xiamen City Appearance and Environmental Sanitation Management Office, 51 Hexiangxi Road, Xiamen 361004 (China)

2013-06-15T23:59:59.000Z

276

Experimental investigation of a cook-off temperature in a hot barrel  

Science Journals Connector (OSTI)

Abstract The experimental investigations of the effect of contact time/temperature on initiating the cook-off using 7.62 mm calibre cartridge cases (CC) were conducted previously. These cartridges were filled with commercial off-the-shelf (COTS) double based (DB) propellant (Bulls Eye) and were loaded in a hot chamber. The thermal explosion temperature is of great significance to both weapon designers and safety inspectors as it provides the operational limit and safe operating temperature. For CC under test, it was found that the cook-off temperatures of this propellant were encountered with the heat transfer profile of the simulated gun barrel between 151.4 °C and 153.4 °C, with a reaction occurring in less than 300 s after the round was chambered. Usefully, each experiment was found to be consistent and repeatable.

Amer Hameed; Mathew Azavedo; Philip Pitcher

2014-01-01T23:59:59.000Z

277

Performance of the prototype module of the GlueX electromagnetic barrel calorimeter  

SciTech Connect (OSTI)

A photon beam test of the 4 m long prototype lead/scintillating-fibre module for the GlueX electromagnetic barrel calorimeter was carried out in Hall B at the Thomas Jefferson National Accelerator Facility with the objective of measuring the energy and timing resolutions of the module as well as the number of photoelectrons generated. Data were collected over an energy range of 150 - â 650 MeV at multiple positions and angles along the module. Details of the analysis at the centre of and perpendicular to the module are shown herein; the results are View the MathML source, View the MathML source ps, and 660 photoelectrons for 1 GeV at each end of the module.

Leverington, Blake; Lolos, George; Papandreou, Zisis; Hakobyan, Rafael; Huber, Garth; Janzen, Kathryn; Semenov, Andrei; Scott, Eric; Shepherd, Matthew; Carman, Daniel; Lawrence, David; Smith, Elton; Taylor, Simon; Wolin, Elliott; Klein, Franz; Santoro, Joseph; Sober, Daniel; Kourkoumeli, Christina

2008-11-01T23:59:59.000Z

278

1993 Solid Waste Reference Forecast Summary  

SciTech Connect (OSTI)

This report, which updates WHC-EP-0567, 1992 Solid Waste Reference Forecast Summary, (WHC 1992) forecasts the volumes of solid wastes to be generated or received at the US Department of Energy Hanford Site during the 30-year period from FY 1993 through FY 2022. The data used in this document were collected from Westinghouse Hanford Company forecasts as well as from surveys of waste generators at other US Department of Energy sites who are now shipping or plan to ship solid wastes to the Hanford Site for disposal. These wastes include low-level and low-level mixed waste, transuranic and transuranic mixed waste, and nonradioactive hazardous waste.

Valero, O.J.; Blackburn, C.L. [Westinghouse Hanford Co., Richland, WA (United States); Kaae, P.S.; Armacost, L.L.; Garrett, S.M.K. [Pacific Northwest Lab., Richland, WA (United States)

1993-08-01T23:59:59.000Z

279

20 InsideGNSS SEP T EMBER /OC T OBER 2011 www.insidegnss.com he Arctic houses an estimated 90 billion barrels of  

E-Print Network [OSTI]

billion barrels of undiscovered, technically recoverable oil and 44 billion barrels of natural gas liquids) reference stations in or near the Arctic, integration of Iridium satellites with GNSS, and use of multi, and MSAS. More specifically, it analyzes the potential benefit of adding new SBAS reference stations

Stanford University

280

Metrics for Evaluating the Accuracy of Solar Power Forecasting (Presentation)  

SciTech Connect (OSTI)

This presentation proposes a suite of metrics for evaluating the performance of solar power forecasting.

Zhang, J.; Hodge, B.; Florita, A.; Lu, S.; Hamann, H.; Banunarayanan, V.

2013-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast thousand barrels" 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.


281

PSO (FU 2101) Ensemble-forecasts for wind power  

E-Print Network [OSTI]

PSO (FU 2101) Ensemble-forecasts for wind power Analysis of the Results of an On-line Wind Power Ensemble- forecasts for wind power (FU2101) a demo-application producing quantile forecasts of wind power correct) quantile forecasts of the wind power production are generated by the application. However

282

Forecasting Uncertainty Related to Ramps of Wind Power Production  

E-Print Network [OSTI]

Forecasting Uncertainty Related to Ramps of Wind Power Production Arthur Bossavy, Robin Girard - The continuous improvement of the accuracy of wind power forecasts is motivated by the increasing wind power study. Key words : wind power forecast, ramps, phase er- rors, forecasts ensemble. 1 Introduction Most

Boyer, Edmond

283

The effect of multinationality on management earnings forecasts  

E-Print Network [OSTI]

and number of countries withforeign subsidiaries) are significantly positively related to more optimistic management earnings forecasts....

Runyan, Bruce Wayne

2005-08-29T23:59:59.000Z

284

Distribution of Wind Power Forecasting Errors from Operational Systems (Presentation)  

SciTech Connect (OSTI)

This presentation offers new data and statistical analysis of wind power forecasting errors in operational systems.

Hodge, B. M.; Ela, E.; Milligan, M.

2011-10-01T23:59:59.000Z

285

72657Federal Register / Vol. 72, No. 245 / Friday, December 21, 2007 / Proposed Rules lease in million barrels of oil equivalent  

E-Print Network [OSTI]

in million barrels of oil equivalent (MMBOE): Water depth Minimum royalty sus- pension volume (MMBOE) (1) 200 of paragraph (b) are revised to read as follows: § 260.124 How will royalty suspension apply if MMS assigns establish a royalty suspension volume for a field as a result of an approved application for royalty relief

286

,"Utah Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sut_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sut_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:52:03 PM"

287

,"U.S. Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_nus_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_nus_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:03 PM"

288

,"Indiana Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Indiana Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sin_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sin_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:23 PM"

289

,"Colorado Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sco_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sco_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:10 PM"

290

,"Maine Natural Gas Imports Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Maine Natural Gas Imports Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1274_sme_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1274_sme_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:40:04 PM"

291

,"Oklahoma Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sok_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sok_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:51 PM"

292

,"Virginia Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Virginia Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sva_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sva_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:52:04 PM"

293

,"Wyoming Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_swy_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_swy_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:52:09 PM"

294

,"Idaho Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Idaho Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sid_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sid_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:20 PM"

295

,"Minnesota Natural Gas Imports Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Minnesota Natural Gas Imports Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1274_smn_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1274_smn_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:40:06 PM"

296

,"Arkansas Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Arkansas Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sar_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sar_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:06 PM"

297

,"Massachusetts Natural Gas Imports Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Massachusetts Natural Gas Imports Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1274_sma_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1274_sma_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:40:03 PM"

298

,"Michigan Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_smi_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_smi_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:32 PM"

299

Thousands of Americans Innovate for Good on the National Day of Civic  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Thousands of Americans Innovate for Good on the National Day of Civic Thousands of Americans Innovate for Good on the National Day of Civic Hacking Thousands of Americans Innovate for Good on the National Day of Civic Hacking Submitted by Anonymous on Fri, 06/07/2013 - 12:00am Log in to vote 0 This past weekend, more than 11,000 people in 83 cities across America participated in 95 open data hacking events as part of the National Day of Civic Hacking. This huge turnout is an unmistakable mark of the growing interest and enthusiasm of American innovators in applying their tech skills for social good. At events across the country, participants in Civic Hacking Day were set loose on open government data, building tools, apps, and solutions that can help address challenges faced by communities across America and form the basis of products and companies that contribute to our economy.

300

,"Kentucky Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sky_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sky_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:26 PM"

Note: This page contains sample records for the topic "forecast thousand barrels" 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

,"Delaware Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Delaware Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sde_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sde_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:13 PM"

302

,"Montana Natural Gas Imports Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Imports Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1274_smt_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1274_smt_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:40:07 PM"

303

,"Florida Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sfl_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sfl_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:15 PM"

304

,"Michigan Natural Gas Imports Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Imports Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1274_smi_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1274_smi_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:40:05 PM"

305

,"Georgia Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Georgia Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sga_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sga_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:16 PM"

306

,"Arizona Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Arizona Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_saz_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_saz_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:08 PM"

307

,"Montana Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_smt_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_smt_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:37 PM"

308

,"Louisiana Natural Gas Imports Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Imports Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1274_sla_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1274_sla_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:40:02 PM"

309

,"Texas Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_stx_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_stx_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:52:01 PM"

310

,"Nevada Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Nevada Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_snv_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_snv_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:47 PM"

311

Thousands of Students Prepare to Compete in the National Science Bowl |  

Broader source: Energy.gov (indexed) [DOE]

Thousands of Students Prepare to Compete in the National Science Thousands of Students Prepare to Compete in the National Science Bowl Thousands of Students Prepare to Compete in the National Science Bowl January 29, 2013 - 5:00pm Addthis Members of the Los Alamos High School team, Los Alamos, New Mexico, concentrates on the answer to a question at the 2012 National Science Bowl in Washington D.C. on April 29, 2012. | Photograph by Dennis Brack, Office of Science Members of the Los Alamos High School team, Los Alamos, New Mexico, concentrates on the answer to a question at the 2012 National Science Bowl in Washington D.C. on April 29, 2012. | Photograph by Dennis Brack, Office of Science Charles Rousseaux Charles Rousseaux Senior Writer, Office of Science What are the key facts? To learn more about the individual high school regional

312

,"Ohio Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_soh_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_soh_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:50 PM"

313

,"Missouri Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Missouri Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_smo_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_smo_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:34 PM"

314

,"Idaho Natural Gas Imports Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Idaho Natural Gas Imports Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1274_sid_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1274_sid_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:40:02 PM"

315

,"Oregon Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oregon Natural Gas Vehicle Fuel Price (Dollars per Thousand Cubic Feet)",1,"Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1570_sor_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1570_sor_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:51:52 PM"

316

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network [OSTI]

J.B. , 2004: Probabilistic wind power forecasts using localforecast intervals for wind power output using NWP-predictedsources such as wind and solar power. Integration of this

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

317

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network [OSTI]

United States California Solar Initiative Coastally Trappedparticipants in the California Solar Initiative (CSI)on location. In California, solar irradiance forecasts near

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

318

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Analysis Papers > Annual Energy Outlook Forecast Evaluation>Tables Analysis Papers > Annual Energy Outlook Forecast Evaluation>Tables Annual Energy Outlook Forecast Evaluation Download Adobe Acrobat Reader Printer friendly version on our site are provided in Adobe Acrobat Spreadsheets are provided in Excel Actual vs. Forecasts Formats Table 2. Total Energy Consumption Excel, PDF Table 3. Total Petroleum Consumption Excel, PDF Table 4. Total Natural Gas Consumption Excel, PDF Table 5. Total Coal Consumption Excel, PDF Table 6. Total Electricity Sales Excel, PDF Table 7. Crude Oil Production Excel, PDF Table 8. Natural Gas Production Excel, PDF Table 9. Coal Production Excel, PDF Table 10. Net Petroleum Imports Excel, PDF Table 11. Net Natural Gas Imports Excel, PDF Table 12. World Oil Prices Excel, PDF Table 13. Natural Gas Wellhead Prices

319

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Annual Energy Outlook Forecast Evaluation Actual vs. Forecasts Available formats Excel (.xls) for printable spreadsheet data (Microsoft Excel required) MS Excel Viewer PDF (Acrobat Reader required Download Acrobat Reader ) Adobe Acrobat Reader Logo Table 2. Total Energy Consumption Excel, PDF Table 3. Total Petroleum Consumption Excel, PDF Table 4. Total Natural Gas Consumption Excel, PDF Table 5. Total Coal Consumption Excel, PDF Table 6. Total Electricity Sales Excel, PDF Table 7. Crude Oil Production Excel, PDF Table 8. Natural Gas Production Excel, PDF Table 9. Coal Production Excel, PDF Table 10. Net Petroleum Imports Excel, PDF Table 11. Net Natural Gas Imports Excel, PDF

320

Annual Energy Outlook Forecast Evaluation 2004  

Gasoline and Diesel Fuel Update (EIA)

2004 2004 * The Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) has produced annual evaluations of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and replacing the historical year of data with the most recent. The forecast evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute percent errors for several of the major variables for AEO82 through AEO2004. (There is no report titled Annual Energy Outlook 1988 due to a change in the naming convention of the AEOs.) The average absolute percent error is the simple mean of the absolute values of the percentage difference between the Reference Case projection and the

Note: This page contains sample records for the topic "forecast thousand barrels" 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

Annual Energy Outlook 2001 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Economic Growth World Oil Prices Total Energy Consumption Residential and Commercial Sectors Industrial Sector Transportation Sector Electricity Natural Gas Petroleum Coal Three other organizations—Standard & Poor’s DRI (DRI), the WEFA Group (WEFA), and the Gas Research Institute (GRI) [95]—also produce comprehensive energy projections with a time horizon similar to that of AEO2001. The most recent projections from those organizations (DRI, Spring/Summer 2000; WEFA, 1st Quarter 2000; GRI, January 2000), as well as other forecasts that concentrate on petroleum, natural gas, and international oil markets, are compared here with the AEO2001 projections. Economic Growth Differences in long-run economic forecasts can be traced primarily to

322

energy data + forecasting | OpenEI Community  

Open Energy Info (EERE)

energy data + forecasting energy data + forecasting Home FRED Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in formulating policies and energy plans based on easy to use forecasting tools, visualizations, sankey diagrams, and open data. The platform will live on OpenEI and this community was established to initiate discussion around continuous development of this tool, integrating it with new datasets, and connecting with the community of users who will want to contribute data to the tool and use the tool for planning purposes. Links: FRED beta demo energy data + forecasting Syndicate content 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2084382122

323

Wind Speed Forecasting for Power System Operation  

E-Print Network [OSTI]

In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

Zhu, Xinxin

2013-07-22T23:59:59.000Z

324

Evaluation of hierarchical forecasting for substitutable products  

Science Journals Connector (OSTI)

This paper addresses hierarchical forecasting in a production planning environment. Specifically, we examine the relative effectiveness of Top-Down (TD) and Bottom-Up (BU) strategies for forecasting the demand for a substitutable product (which belongs to a family) as well as the demand for the product family under different types of family demand processes. Through a simulation study, it is revealed that the TD strategy consistently outperforms the BU strategy for forecasting product family demand. The relative superiority of the TD strategy further improves by as much as 52% as the product demand variability increases and the degree of substitutability between the products decreases. This phenomenon, however, is not always true for forecasting the demand for the products within the family. In this case, it is found that there are a few situations wherein the BU strategy marginally outperforms the TD strategy, especially when the product demand variability is high and the degree of product substitutability is low.

S. Viswanathan; Handik Widiarta; R. Piplani

2008-01-01T23:59:59.000Z

325

Testing Competing High-Resolution Precipitation Forecasts  

E-Print Network [OSTI]

Testing Competing High-Resolution Precipitation Forecasts Eric Gilleland Research Prediction Comparison Test D1 D2 D = D1 ­ D2 copyright NCAR 2013 Loss Differential Field #12;Spatial Prediction Comparison Test Introduced by Hering and Genton

Gilleland, Eric

326

Forecasting Capital Expenditure with Plan Data  

Science Journals Connector (OSTI)

The short-term forecasting of capital expenditure presents one of the most difficult problems ... reason is that year-to-year fluctuations in capital expenditure are extremely wide. Some simple methods which...

W. Gerstenberger

1977-01-01T23:59:59.000Z

327

Forecasting Agriculturally Driven Global Environmental Change  

Science Journals Connector (OSTI)

...of each variable on GDP (13, 17), combined with global GDP projections (14...population, and per capita GDP, combined with projected...measure of agricultural demand for water, is forecast...Just as demand for energy is the major cause...

David Tilman; Joseph Fargione; Brian Wolff; Carla D'Antonio; Andrew Dobson; Robert Howarth; David Schindler; William H. Schlesinger; Daniel Simberloff; Deborah Swackhamer

2001-04-13T23:59:59.000Z

328

Medium- and Long-Range Forecasting  

Science Journals Connector (OSTI)

In contrast to short and extended range forecasts, predictions for periods beyond 5 days use time-averaged, midtropospheric height fields as their primary guidance. As time ranges are increased to 3O- and 90-day outlooks, guidance increasingly ...

A. James Wagner

1989-09-01T23:59:59.000Z

329

Updated Satellite Technique to Forecast Heavy Snow  

Science Journals Connector (OSTI)

Certain satellite interpretation techniques have proven quite useful in the heavy snow forecast process. Those considered best are briefly reviewed, and another technique is introduced. This new technique was found to be most valuable in cyclonic ...

Edward C. Johnston

1995-06-01T23:59:59.000Z

330

Annual Energy Outlook Forecast Evaluation 2005  

Gasoline and Diesel Fuel Update (EIA)

Forecast Evaluation 2005 Forecast Evaluation 2005 Annual Energy Outlook Forecast Evaluation 2005 Annual Energy Outlook Forecast Evaluation 2005 * Then Energy Information Administration (EIA) produces projections of energy supply and demand each year in the Annual Energy Outlook (AEO). The projections in the AEO are not statements of what will happen but of what might happen, given the assumptions and methodologies used. The projections are business-as-usual trend projections, given known technology, technological and demographic trends, and current laws and regulations. Thus, they provide a policy-neutral reference case that can be used to analyze policy initiatives. EIA does not propose or advocate future legislative and regulatory changes. All laws are assumed to remain as currently enacted; however, the impacts of emerging regulatory changes, when defined, are reflected.

331

Revenue from Retail Sales of Electricity (Thousands Dollars) by State by Provide  

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

Revenue from Retail Sales of Electricity (Thousands Dollars) by State by Provider, 1990-2012" Revenue from Retail Sales of Electricity (Thousands Dollars) by State by Provider, 1990-2012" "Year","State","Industry Sector Category","Residential","Commercial","Industrial","Transportation","Other","Total" 2012,"AK","Total Electric Industry",386304,429152,232325,0,"NA",1047781 2012,"AL","Total Electric Industry",3491380,2318146,2100936,0,"NA",7910462 2012,"AR","Total Electric Industry",1664696,933567,971266,52,"NA",3569581 2012,"AZ","Total Electric Industry",3718357,2829551,813094,0,"NA",7361001 2012,"CA","Total Electric Industry",13821565,16327164,4925482,49095,"NA",35123306

332

Forecasting energy markets using support vector machines  

Science Journals Connector (OSTI)

Abstract In this paper we investigate the efficiency of a support vector machine (SVM)-based forecasting model for the next-day directional change of electricity prices. We first adjust the best autoregressive SVM model and then we enhance it with various related variables. The system is tested on the daily Phelix index of the German and Austrian control area of the European Energy Exchange (???) wholesale electricity market. The forecast accuracy we achieved is 76.12% over a 200 day period.

Theophilos Papadimitriou; Periklis Gogas; Efthimios Stathakis

2014-01-01T23:59:59.000Z

333

Bioscience Connecticut is a forward-thinking plan to create thousands  

E-Print Network [OSTI]

Bioscience Connecticut is a forward- thinking plan to create thousands of construction and related by the Connecticut General Assembly, it is a multifaceted plan that will help to reinvent the state's economy, drawing upon research resources from the University of Connecticut, UConn Health Center, Yale University

Lozano-Robledo, Alvaro

334

Pictures worth a thousand tiles, a geometrical programming language for self-assembly  

E-Print Network [OSTI]

Pictures worth a thousand tiles, a geometrical programming language for self-assembly Florent.becker@ens-lyon.fr February 14, 2008 Abstract We present a novel way to design self-assembling systems using a notion of signals for a given set of shapes, and how to transform these signals into a set of tiles which self-assemble

Paris-Sud XI, Université de

335

Search thousands of travel therapy destinations at: http://www.advanced-medical.net  

E-Print Network [OSTI]

Search thousands of travel therapy destinations at: http://www.advanced-medical.net Why do new grads travel with Advanced Medical? Mentorship: With accomplished mentors, new grad friendly facilities, and robust clinical support, trust Advanced Medical to take your professional growth seriously. Advanced

Weber, David J.

336

PetaScale Calculations of the Electronic Structures of Nanostructures with Hundreds of Thousands of Processors  

E-Print Network [OSTI]

PetaScale Calculations of the Electronic Structures of Nanostructures with Hundreds of Thousands in the material science category. The DFT can be used to calculate the electronic structure, the charge density selfconsistent calculation without atomic relaxation). But there are many problems which either requires much

337

Forecasting aggregate time series with intermittent subaggregate components: top-down versus bottom-up forecasting  

Science Journals Connector (OSTI)

......optimum value through a grid-search algorithm...method outperformed TD for estimating the aggregate data series...variable, there is no benefit of forecasting each subaggregate...forecasting strategies in estimating the `component'-level...WILLEMAIN, T. R., SMART, C. N., SHOCKOR......

S. Viswanathan; Handik Widiarta; Rajesh Piplani

2008-07-01T23:59:59.000Z

338

Ramp Forecasting Performance from Improved Short-Term Wind Power Forecasting: Preprint  

SciTech Connect (OSTI)

The variable and uncertain nature of wind generation presents a new concern to power system operators. One of the biggest concerns associated with integrating a large amount of wind power into the grid is the ability to handle large ramps in wind power output. Large ramps can significantly influence system economics and reliability, on which power system operators place primary emphasis. The Wind Forecasting Improvement Project (WFIP) was performed to improve wind power forecasts and determine the value of these improvements to grid operators. This paper evaluates the performance of improved short-term wind power ramp forecasting. The study is performed for the Electric Reliability Council of Texas (ERCOT) by comparing the experimental WFIP forecast to the current short-term wind power forecast (STWPF). Four types of significant wind power ramps are employed in the study; these are based on the power change magnitude, direction, and duration. The swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental short-term wind power forecasts improve the accuracy of the wind power ramp forecasting, especially during the summer.

Zhang, J.; Florita, A.; Hodge, B. M.; Freedman, J.

2014-05-01T23:59:59.000Z

339

Emissions of Polychlorinated Dibenzo-p-dioxins and Polychlorinated Dibenzofurans from the Open Burning of Household Waste in Barrels  

Science Journals Connector (OSTI)

This study measured the emissions of several pollutants, including polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDDs/PCDFs), from burning mixtures designed to simulate waste generated by a “recycling” and a “nonrecycling” family in a 208-L (55-gal) burn barrel at the EPA's Open Burning Test Facility. ... Four test burns were made in which the amount of waste placed in the barrel varied from 6.4 to 13.6 kg and the amount actually burned varied from 46.6% to 68.1%. ... This study included a survey of 187 residents in rural counties of Illinois to determine the quantity and type of wastes burned, the management of the ash, and the motivation for burning. ...

Paul M. Lemieux; Christopher C. Lutes; Judith A. Abbott; Kenneth M. Aldous

2000-01-04T23:59:59.000Z

340

Radar-Derived Forecasts of Cloud-to-Ground Lightning Over Houston, Texas  

E-Print Network [OSTI]

Lightning Forecasts..........................................................................................45 2.7 First Flash Forecasts and Lead Times.....................................................................47 vii... Cell Number ? 25 August 2000..............................................68 3.4 First Flash Forecast Time........................................................................................70 3.5 Lightning Forecasting Algorithm (LFA) Development...

Mosier, Richard Matthew

2011-02-22T23:59:59.000Z

Note: This page contains sample records for the topic "forecast thousand barrels" 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.


341

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation Actual vs. Forecasts Available formats Excel (.xls) for printable spreadsheet data (Microsoft Excel required) PDF (Acrobat Reader required) Table 2. Total Energy Consumption HTML, Excel, PDF Table 3. Total Petroleum Consumption HTML, Excel, PDF Table 4. Total Natural Gas Consumption HTML, Excel, PDF Table 5. Total Coal Consumption HTML, Excel, PDF Table 6. Total Electricity Sales HTML, Excel, PDF Table 7. Crude Oil Production HTML, Excel, PDF Table 8. Natural Gas Production HTML, Excel, PDF Table 9. Coal Production HTML, Excel, PDF Table 10. Net Petroleum Imports HTML, Excel, PDF Table 11. Net Natural Gas Imports HTML, Excel, PDF Table 12. Net Coal Exports HTML, Excel, PDF Table 13. World Oil Prices HTML, Excel, PDF

342

A Scenario-Based Hydrocarbon Production Forecast for Louisiana  

Science Journals Connector (OSTI)

Fields are classified as oil or gas based on the volume of ... in cubic feet) per unit of produced oil (measured in barrels), and described through the gas–oil ratio (GOR). Cumulative GOR (CGOR) is the aggregate ...

Mark J. Kaiser; Yunke Yu

2012-03-01T23:59:59.000Z

343

,"Colorado Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Monthly","9/2013" Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035co3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035co3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:24:00 PM" "Back to Contents","Data 1: Colorado Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035CO3" "Date","Colorado Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 36906,9.36 36937,10.07

344

,"Alabama Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Monthly","9/2013" Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035al3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035al3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:23:53 PM" "Back to Contents","Data 1: Alabama Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035AL3" "Date","Alabama Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 36906,9.55 36937,8.54

345

,"California Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Monthly","9/2013" Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035ca3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035ca3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:23:58 PM" "Back to Contents","Data 1: California Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035CA3" "Date","California Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 36906,7.75

346

,"Colorado Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Annual",2012 Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035co3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035co3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:24:00 PM" "Back to Contents","Data 1: Colorado Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035CO3" "Date","Colorado Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 35611,3.02 35976,2.55 36341,3.08

347

,"Connecticut Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Monthly","9/2013" Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035ct3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035ct3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:24:02 PM" "Back to Contents","Data 1: Connecticut Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035CT3" "Date","Connecticut Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 36906,10.11

348

,"Alaska Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Annual",2012 Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035ak3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035ak3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:23:51 PM" "Back to Contents","Data 1: Alaska Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035AK3" "Date","Alaska Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 35611,1.54 35976,1.34 36341,1.25

349

,"Georgia Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Monthly","9/2013" Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035ga3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035ga3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:24:08 PM" "Back to Contents","Data 1: Georgia Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035GA3" "Date","Georgia Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 36906,10.05 36937,9.35

350

,"Florida Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Annual",2012 Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035fl3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035fl3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:24:06 PM" "Back to Contents","Data 1: Florida Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035FL3" "Date","Florida Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 35611,4.41 35976,3.98 36341,4.12

351

,"California Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Annual",2012 Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035ca3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035ca3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:23:58 PM" "Back to Contents","Data 1: California Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035CA3" "Date","California Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 35611,4.18 35976,3.75 36341,3.33

352

,"Alaska Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Monthly","9/2013" Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035ak3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035ak3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:23:51 PM" "Back to Contents","Data 1: Alaska Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035AK3" "Date","Alaska Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 36906,1.57 36937,1.55

353

,"Florida Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Monthly","9/2013" Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035fl3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035fl3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:24:06 PM" "Back to Contents","Data 1: Florida Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035FL3" "Date","Florida Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 36906,8.27 36937,8.02

354

,"Delaware Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Monthly","9/2013" Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035de3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035de3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:24:04 PM" "Back to Contents","Data 1: Delaware Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035DE3" "Date","Delaware Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 36906,7.37 36937,4.61

355

,"South Carolina Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Annual",2012 Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035sc3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035sc3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:25:02 PM" "Back to Contents","Data 1: South Carolina Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035SC3" "Date","South Carolina Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 35611,3.72 35976,3.29

356

,"Idaho Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Annual",2012 Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035id3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035id3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:24:13 PM" "Back to Contents","Data 1: Idaho Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035ID3" "Date","Idaho Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 35611,2.76 35976,3.09 36341,3.29 36707,4.02

357

,"Georgia Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Annual",2012 Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035ga3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035ga3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:24:07 PM" "Back to Contents","Data 1: Georgia Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035GA3" "Date","Georgia Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 35611,4.55 35976,3.92 36341,3.41

358

,"Hawaii Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Monthly","9/2013" Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035hi3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035hi3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:24:09 PM" "Back to Contents","Data 1: Hawaii Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035HI3" "Date","Hawaii Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 36906,11.65 36937,11.84

359

,"South Carolina Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Monthly","9/2013" Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035sc3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035sc3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:25:02 PM" "Back to Contents","Data 1: South Carolina Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035SC3" "Date","South Carolina Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"

360

Compound and Elemental Analysis At Valley Of Ten Thousand Smokes Region  

Open Energy Info (EERE)

Kodosky & Keith, 1993) Kodosky & Keith, 1993) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Compound and Elemental Analysis At Valley Of Ten Thousand Smokes Region Area (Kodosky & Keith, 1993) Exploration Activity Details Location Valley Of Ten Thousand Smokes Region Area Exploration Technique Compound and Elemental Analysis Activity Date Usefulness not indicated DOE-funding Unknown Notes The purpose of this paper is to examine whether statistical analysis of encrustation chemistries, when supplemented with petrologic data, can identify the individual processes that generate and degrade fumarolic encrustations. Knowledge of these specific processes broadens the applications of fumarolic alteration studies. Geochemical data for a 47-element suite were obtained for an air-dried subset of the collected

Note: This page contains sample records for the topic "forecast thousand barrels" 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

,"South Dakota Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)"  

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

Annual",2012 Annual",2012 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n3035sd3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n3035sd3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov" ,,"(202) 586-8800",,,"12/12/2013 5:25:04 PM" "Back to Contents","Data 1: South Dakota Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" "Sourcekey","N3035SD3" "Date","South Dakota Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)" 35611,4.02 35976,3.28

362

12-32021E2_Forecast  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

FORECAST OF VACANCIES FORECAST OF VACANCIES Until end of 2014 (Issue No. 20) Page 2 OVERVIEW OF BASIC REQUIREMENTS FOR PROFESSIONAL VACANCIES IN THE IAEA Education, Experience and Skills: Professional staff at the P4-P5 levels: * Advanced university degree (or equivalent postgraduate degree); * 7 or 10 years, respectively, of experience in a field of relevance to the post; * Resource management experience; * Strong analytical skills; * Computer skills: standard Microsoft Office software; * Languages: Fluency in English. Working knowledge of other official languages (Arabic, Chinese, French, Russian, Spanish) advantageous; * Ability to work effectively in multidisciplinary and multicultural teams; * Ability to communicate effectively. Professional staff at the P1-P3 levels:

363

Building Energy Software Tools Directory: Degree Day Forecasts  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Forecasts Forecasts Degree Day Forecasts example chart Quick and easy web-based tool that provides free 14-day ahead degree day forecasts for 1,200 stations in the U.S. and Canada. Degree Day Forecasts charts show this year, last year and three-year average. Historical degree day charts and energy usage forecasts are available from the same site. Keywords degree days, historical weather, mean daily temperature Validation/Testing Degree day data provided by AccuWeather.com, updated daily at 0700. Expertise Required No special expertise required. Simple to use. Users Over 1,000 weekly users. Audience Anyone who needs degree day forecasts (next 14 days) for the U.S. and Canada. Input Select a weather station (1,200 available) and balance point temperature. Output Charts show (1) degree day (heating and cooling) forecasts for the next 14

364

Building Energy Software Tools Directory: Energy Usage Forecasts  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Energy Usage Forecasts Energy Usage Forecasts Energy Usage Forecasts Quick and easy web-based tool that provides free 14-day ahead energy usage forecasts based on the degree day forecasts for 1,200 stations in the U.S. and Canada. The user enters the daily non-weather base load and the usage per degree day weather factor; the tool applies the degree day forecast and displays the total energy usage forecast. Helpful FAQs explain the process and describe various options for the calculation of the base load and weather factor. Historical degree day reports and 14-day ahead degree day forecasts are available from the same site. Keywords degree days, historical weather, mean daily temperature, load calculation, energy simulation Validation/Testing Degree day data provided by AccuWeather.com, updated daily at 0700.

365

Forecasting Market Demand for New Telecommunications Services: An Introduction  

E-Print Network [OSTI]

Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc The marketing team of a new telecommunications company is usually tasked with producing forecasts for diverse three decades of experience working with telecommunications operators around the world we seek

McBurney, Peter

366

River Forecast Application for Water Management: Oil and Water?  

Science Journals Connector (OSTI)

Managing water resources generally and managing reservoir operations specifically have been touted as opportunities for applying forecasts to improve decision making. Previous studies have shown that the application of forecasts into water ...

Kevin Werner; Kristen Averyt; Gigi Owen

2013-07-01T23:59:59.000Z

367

Data Mining in Load Forecasting of Power System  

Science Journals Connector (OSTI)

This project applies Data Mining technology to the prediction of electric power system load forecast. It proposes a mining program of electric power load forecasting data based on the similarity of time series .....

Guang Yu Zhao; Yan Yan; Chun Zhou Zhao…

2013-01-01T23:59:59.000Z

368

Operational Rainfall and Flow Forecasting for the Panama Canal Watershed  

Science Journals Connector (OSTI)

An integrated hydrometeorological system was designed for the utilization of data from various sensors in the 3300 km2 Panama Canal Watershed for the purpose of producing ... forecasts. These forecasts are used b...

Konstantine P. Georgakakos; Jason A. Sperfslage

2005-01-01T23:59:59.000Z

369

Power System Load Forecasting Based on EEMD and ANN  

Science Journals Connector (OSTI)

In order to fully mine the characteristics of load data and improve the accuracy of power system load forecasting, a load forecasting model based on Ensemble Empirical Mode ... is proposed in this paper. Firstly,...

Wanlu Sun; Zhigang Liu; Wenfan Li

2011-01-01T23:59:59.000Z

370

U.S. Regional Demand Forecasts Using NEMS and GIS  

E-Print Network [OSTI]

Forecasts Using NEMS and GIS National Climatic Data Center.with Changing Boundaries." Use of GIS to Understand Socio-Forecasts Using NEMS and GIS Appendix A. Map Results Gallery

Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

2005-01-01T23:59:59.000Z

371

Beyond "Partly Sunny": A Better Solar Forecast | Department of...  

Energy Savers [EERE]

Beyond "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast December 7, 2012 - 10:00am Addthis The Energy Department is investing in better solar...

372

The Energy Demand Forecasting System of the National Energy Board  

Science Journals Connector (OSTI)

This paper presents the National Energy Board’s long term energy demand forecasting model in its present state of ... results of recent research at the NEB. Energy demand forecasts developed with the aid of this....

R. A. Preece; L. B. Harsanyi; H. M. Webster

1980-01-01T23:59:59.000Z

373

Forecasting Energy Demand Using Fuzzy Seasonal Time Series  

Science Journals Connector (OSTI)

Demand side energy management has become an important issue for energy management. In order to support energy planning and policy decisions forecasting the future demand is very important. Thus, forecasting the f...

?Irem Uçal Sar?; Ba¸sar Öztay¸si

2012-01-01T23:59:59.000Z

374

New York Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) New York Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.31 0.30 0.30 1970's 0.30 0.30 0.33 0.35 0.55 0.74 1.13 1.16 1.19 1.27 1980's 1.95 2.67 3.75 3.85 4.00 3.37 3.39 2.00 2.30 2.20 1990's 2.20 2.15 2.25 2.40 2.35 2.30 2.56 2.56 2.16 2000's 3.75 5.00 3.03 5.78 6.98 7.78 7.13 8.85 8.94 4.21 2010's 4.65 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price New York Natural Gas Prices

375

New Mexico Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)  

Gasoline and Diesel Fuel Update (EIA)

Wellhead Price (Dollars per Thousand Cubic Feet) Wellhead Price (Dollars per Thousand Cubic Feet) New Mexico Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.13 0.13 0.14 1970's 0.14 0.15 0.19 0.24 0.31 0.40 0.56 0.81 0.99 1.37 1980's 1.76 2.13 2.47 2.68 2.71 2.62 1.87 1.66 1.70 1.56 1990's 1.69 1.37 1.60 1.79 1.58 1.26 1.67 1.76 1.76 2.11 2000's 3.43 3.89 2.68 4.56 4.97 6.91 6.18 6.88 8.40 4.17 2010's 5.32 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Natural Gas Wellhead Price New Mexico Natural Gas Prices

376

U.S. Natural Gas Average Consumption per Industrial Consumer (Thousand  

Gasoline and Diesel Fuel Update (EIA)

Industrial Consumer (Thousand Cubic Feet) Industrial Consumer (Thousand Cubic Feet) U.S. Natural Gas Average Consumption per Industrial Consumer (Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 0 0 0 0 0 0 0 1980's 39,245 37,530 30,909 29,915 24,309 30,956 29,057 30,423 32,071 30,248 1990's 32,144 33,395 35,908 38,067 40,244 40,973 43,050 36,239 36,785 35,384 2000's 36,968 33,840 36,458 34,793 34,645 31,991 33,597 33,561 29,639 29,705 2010's 35,418 36,947 38,155 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 1/7/2014 Next Release Date: 1/31/2014 Referring Pages: Average Natural Gas Consumption per Industrial

377

Texas Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand  

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

Price (Dollars per Thousand Cubic Feet) Price (Dollars per Thousand Cubic Feet) Texas Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.16 0.17 0.17 1970's 0.17 0.18 0.19 0.20 0.28 0.37 0.51 0.68 0.73 1.19 1980's 1.56 2.24 3.09 3.11 2.98 2.80 2.18 2.01 1.98 1.81 1990's 1.74 1.62 1.66 1.82 1.64 1.64 2.40 2.36 2.02 1.99 2000's 2.99 3.13 NA -- -- - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Price for Natural Gas Pipeline and Distribution Use Texas Natural Gas Prices Price for Natural Gas Pipeline and Distribution Use

378

Ohio Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand  

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

Price (Dollars per Thousand Cubic Feet) Price (Dollars per Thousand Cubic Feet) Ohio Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.22 0.23 0.23 1970's 0.23 0.27 0.28 0.30 0.32 0.43 0.53 0.87 1.01 1.37 1980's 1.92 2.33 3.04 3.42 3.28 3.28 2.79 2.64 2.43 2.54 1990's 2.61 2.66 2.83 2.53 2.50 2.03 2.88 2.80 3.20 2.63 2000's 3.41 5.18 NA -- -- -- - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Price for Natural Gas Pipeline and Distribution Use Ohio Natural Gas Prices Price for Natural Gas Pipeline and Distribution Use

379

U.S. Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand  

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

Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet) Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet) U.S. Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.20 0.20 0.21 1970's 0.21 0.22 0.23 0.25 0.30 0.40 0.51 0.77 0.90 1.32 1980's 1.85 2.39 2.97 3.15 3.04 2.92 2.52 2.17 2.10 2.01 1990's 1.95 1.87 2.07 1.97 1.70 1.49 2.27 2.29 2.01 1.88 2000's 2.97 3.55 NA -- -- -- - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Price for Natural Gas Pipeline and Distribution Use U.S. Natural Gas Prices

380

Iowa Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand  

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

Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet) Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet) Iowa Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.17 0.16 0.17 1970's 0.17 0.19 0.20 0.22 0.26 0.34 0.52 0.73 0.99 1.17 1980's 1.55 1.89 2.50 2.73 2.71 2.83 2.57 2.75 2.01 2.02 1990's 1.52 1.54 1.71 1.25 1.39 1.40 2.37 2.46 2.06 2.16 2000's 3.17 3.60 NA -- -- -- - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Price for Natural Gas Pipeline and Distribution Use Iowa Natural Gas Prices

Note: This page contains sample records for the topic "forecast thousand barrels" 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

Idaho Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand  

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

Price (Dollars per Thousand Cubic Feet) Price (Dollars per Thousand Cubic Feet) Idaho Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.21 0.21 0.22 1970's 0.22 0.24 0.28 0.34 0.44 0.60 0.72 1.65 1.95 2.45 1980's 3.93 3.95 4.19 3.69 3.55 3.15 2.67 2.08 2.00 2.05 1990's 2.06 1.99 1.89 1.76 1.86 1.78 1.79 1.83 1.67 2.04 2000's 3.52 3.49 NA -- -- -- - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Price for Natural Gas Pipeline and Distribution Use Idaho Natural Gas Prices Price for Natural Gas Pipeline and Distribution Use

382

Utah Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand  

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

Price (Dollars per Thousand Cubic Feet) Price (Dollars per Thousand Cubic Feet) Utah Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 0.21 0.21 0.21 1970's 0.21 0.22 0.28 0.29 0.34 0.54 0.67 1.40 1.72 1.88 1980's 2.94 3.17 2.67 2.94 2.99 3.19 2.93 2.66 2.84 2.18 1990's 2.25 2.51 2.25 1.91 1.94 1.57 1.68 2.20 2.05 1.92 2000's 3.19 2.97 NA -- -- -- - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 12/12/2013 Next Release Date: 1/7/2014 Referring Pages: Price for Natural Gas Pipeline and Distribution Use Utah Natural Gas Prices Price for Natural Gas Pipeline and Distribution Use

383

Wind power forecasting in U.S. electricity markets.  

SciTech Connect (OSTI)

Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts.

Botterud, A.; Wang, J.; Miranda, V.; Bessa, R. J.; Decision and Information Sciences; INESC Porto

2010-04-01T23:59:59.000Z

384

Wind power forecasting in U.S. Electricity markets  

SciTech Connect (OSTI)

Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts. (author)

Botterud, Audun; Wang, Jianhui; Miranda, Vladimiro; Bessa, Ricardo J.

2010-04-15T23:59:59.000Z

385

Sandia National Laboratories: Solar Energy Forecasting and Resource...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Energy, Modeling & Analysis, News, News & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource...

386

Application of a Combination Forecasting Model in Logistics Parks' Demand  

Science Journals Connector (OSTI)

Logistics parks’ demand is an important basis of establishing the development policy of logistics industry and logistics infrastructure for planning. In order to improve the forecast accuracy of logistics parks’ demand, a combination forecasting ... Keywords: Logistics parks' demand, combine, simulated annealing algorithm, grey forecast model, exponential smoothing method

Chen Qin; Qi Ming

2010-05-01T23:59:59.000Z

387

A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION  

E-Print Network [OSTI]

in the realm of solar radiation forecasting. In this work, two forecasting models: Autoregressive Moving1 A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION. The very first results show an improvement brought by this approach. 1. INTRODUCTION Solar radiation

Boyer, Edmond

388

PSO (FU 2101) Ensemble-forecasts for wind power  

E-Print Network [OSTI]

PSO (FU 2101) Ensemble-forecasts for wind power Wind Power Ensemble Forecasting Using Wind Speed the problems of (i) transforming the meteorological ensembles to wind power ensembles and, (ii) correcting) data. However, quite often the actual wind power production is outside the range of ensemble forecast

389

Accuracy of near real time updates in wind power forecasting  

E-Print Network [OSTI]

· advantage: no NWP data necessary ­ very actual shortest term forecasts possible · wind power inputAccuracy of near real time updates in wind power forecasting with regard to different weather October 2007 #12;EMS/ECAM 2007 ­ Nadja Saleck Outline · Study site · Wind power forecasting - method

Heinemann, Detlev

390

CSUF ECONOMIC OUTLOOK AND FORECASTS MIDYEAR UPDATE -APRIL 2014  

E-Print Network [OSTI]

CSUF ECONOMIC OUTLOOK AND FORECASTS MIDYEAR UPDATE - APRIL 2014 Anil Puri, Ph.D. -- Director, Center for Economic Analysis and Forecasting -- Dean, Mihaylo College of Business and Economics Mira Farka, Ph.D. -- Co-Director, Center for Economic Analysis and Forecasting -- Associate Professor

de Lijser, Peter

391

Forecasting wave height probabilities with numerical weather prediction models  

E-Print Network [OSTI]

Forecasting wave height probabilities with numerical weather prediction models Mark S. Roulstona; Numerical weather prediction 1. Introduction Wave forecasting is now an integral part of operational weather methods for generating such forecasts from numerical model output from the European Centre for Medium

Stevenson, Paul

392

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data in California and for climate zones within those areas. The staff California Energy Demand 2008-2018 forecast

393

AUTOMATION OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S.  

E-Print Network [OSTI]

AUTOMATION OF ENERGY DEMAND FORECASTING by Sanzad Siddique, B.S. A Thesis submitted to the Faculty OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S. Marquette University, 2013 Automation of energy demand of the energy demand forecasting are achieved by integrating nonlinear transformations within the models

Povinelli, Richard J.

394

Wind and Load Forecast Error Model for Multiple Geographically Distributed Forecasts  

SciTech Connect (OSTI)

The impact of wind and load forecast errors on power grid operations is frequently evaluated by conducting multi-variant studies, where these errors are simulated repeatedly as random processes based on their known statistical characteristics. To generate these errors correctly, we need to reflect their distributions (which do not necessarily follow a known distribution law), standard deviations, auto- and cross-correlations. For instance, load and wind forecast errors can be closely correlated in different zones of the system. This paper introduces a new methodology for generating multiple cross-correlated random processes to simulate forecast error curves based on a transition probability matrix computed from an empirical error distribution function. The matrix will be used to generate new error time series with statistical features similar to observed errors. We present the derivation of the method and present some experimental results by generating new error forecasts together with their statistics.

Makarov, Yuri V.; Reyes Spindola, Jorge F.; Samaan, Nader A.; Diao, Ruisheng; Hafen, Ryan P.

2010-11-02T23:59:59.000Z

395

Forecasting the Market Penetration of Energy Conservation Technologies: The Decision Criteria for Choosing a Forecasting Model  

E-Print Network [OSTI]

An important determinant of our energy future is the rate at which energy conservation technologies, once developed, are put into use. At Synergic Resources Corporation, we have adapted and applied a methodology to forecast the use of conservation...

Lang, K.

1982-01-01T23:59:59.000Z

396

Forecasting the Locational Dynamics of Transnational Terrorism  

E-Print Network [OSTI]

Forecasting the Locational Dynamics of Transnational Terrorism: A Network Analytic Approach Bruce A-0406 Fax: (919) 962-0432 Email: skyler@unc.edu Abstract--Efforts to combat and prevent transnational terror of terrorism. We construct the network of transnational terrorist attacks, in which source (sender) and target

Massachusetts at Amherst, University of

397

Do quantitative decadal forecasts from GCMs provide  

E-Print Network [OSTI]

' · Empirical models quantify our ability to predict without knowing the laws of physics · Climatology skill' model? 2. Dynamic climatology (DC) is a more appropriate benchmark for near- term (initialised) climate forecasts · A conditional climatology, initialised at launch and built from the historical archive

Stevenson, Paul

398

Sunny outlook for space weather forecasters  

Science Journals Connector (OSTI)

... For decades, companies have tailored public weather data for private customers from farmers to airlines. On Wednesday, a group of businesses said that they ... utilities and satellite operators. But Terry Onsager, a physicist at the SWPC, says that private forecasting firms are starting to realize that they can add value to these predictions. ...

Eric Hand

2012-04-27T23:59:59.000Z

399

Modeling of Uncertainty in Wind Energy Forecast  

E-Print Network [OSTI]

regression and splines are combined to model the prediction error from Tunø Knob wind power plant. This data of the thesis is quantile regression and splines in the context of wind power modeling. Lyngby, February 2006Modeling of Uncertainty in Wind Energy Forecast Jan Kloppenborg Møller Kongens Lyngby 2006 IMM-2006

400

Prediction versus Projection: How weather forecasting and  

E-Print Network [OSTI]

Prediction versus Projection: How weather forecasting and climate models differ. Aaron B. Wilson Context: Global http://data.giss.nasa.gov/ #12;Numerical Weather Prediction Collect Observations alters associated weather patterns. Models used to predict weather depend on the current observed state

Howat, Ian M.

Note: This page contains sample records for the topic "forecast thousand barrels" 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

Customized forecasting tool improves reserves estimation  

SciTech Connect (OSTI)

Unique producing characteristics of the Teapot sandstone formation, Powder River basin, Wyoming, necessitated the creation of individualized production forecasting methods for wells producing from this reservoir. The development and use of a set of production type curves and correlations for Teapot wells are described herein.

Mian, M.A.

1986-04-01T23:59:59.000Z

402

Storm-in-a-Box Forecasting  

Science Journals Connector (OSTI)

...But the WRF has no immediate...being tuned to local conditions...temperatures and winds with altitude...resulting WRF forecasts...captured the local sea-breeze winds better...spread the local operation of mesoscale...to be the WRF model now...

Richard A. Kerr

2004-05-14T23:59:59.000Z

403

FORECAST OF VACANCIES Until end of 2016  

E-Print Network [OSTI]

#12;FORECAST OF VACANCIES Until end of 2016 (Issue No. 22) #12;Page 2 OVERVIEW OF BASIC REQUIREMENTS FOR PROFESSIONAL VACANCIES IN THE IAEA Education, Experience and Skills: Professional staff the team of professionals. Second half 2015 VACANCY GRADE REQUIREMENTS / ROLE EXPECTED DATE OF VACANCY

404

Online short-term solar power forecasting  

SciTech Connect (OSTI)

This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model. (author)

Bacher, Peder; Madsen, Henrik [Informatics and Mathematical Modelling, Richard Pedersens Plads, Technical University of Denmark, Building 321, DK-2800 Lyngby (Denmark); Nielsen, Henrik Aalborg [ENFOR A/S, Lyngsoe Alle 3, DK-2970 Hoersholm (Denmark)

2009-10-15T23:59:59.000Z

405

Operational forecasting based on a modified Weather Research and Forecasting model  

SciTech Connect (OSTI)

Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

Lundquist, J; Glascoe, L; Obrecht, J

2010-03-18T23:59:59.000Z

406

UNCERTAINTY IN THE GLOBAL FORECAST SYSTEM  

SciTech Connect (OSTI)

We validated one year of Global Forecast System (GFS) predictions of surface meteorological variables (wind speed, air temperature, dewpoint temperature, air pressure) over the entire planet for forecasts extending from zero hours into the future (an analysis) to 36 hours. Approximately 12,000 surface stations world-wide were included in this analysis. Root-Mean-Square- Errors (RMSE) increased as the forecast period increased from zero to 36 hours, but the initial RMSE were almost as large as the 36 hour forecast RMSE for all variables. Typical RMSE were 3 C for air temperature, 2-3mb for sea-level pressure, 3.5 C for dewpoint temperature and 2.5 m/s for wind speed. Approximately 20-40% of the GFS errors can be attributed to a lack of resolution of local features. We attribute the large initial RMSE for the zero hour forecasts to the inability of the GFS to resolve local terrain features that often dominate local weather conditions, e.g., mountain- valley circulations and sea and land breezes. Since the horizontal resolution of the GFS (about 1{sup o} of latitude and longitude) prevents it from simulating these locally-driven circulations, its performance will not improve until model resolution increases by a factor of 10 or more (from about 100 km to less than 10 km). Since this will not happen in the near future, an alternative for the near term to improve surface weather analyses and predictions for specific points in space and time would be implementation of a high-resolution, limited-area mesoscale atmospheric prediction model in regions of interest.

Werth, D.; Garrett, A.

2009-04-15T23:59:59.000Z

407

Forecastability as a Design Criterion in Wind Resource Assessment: Preprint  

SciTech Connect (OSTI)

This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

Zhang, J.; Hodge, B. M.

2014-04-01T23:59:59.000Z

408

ANL Wind Power Forecasting and Electricity Markets | Open Energy  

Open Energy Info (EERE)

ANL Wind Power Forecasting and Electricity Markets ANL Wind Power Forecasting and Electricity Markets Jump to: navigation, search Logo: Wind Power Forecasting and Electricity Markets Name Wind Power Forecasting and Electricity Markets Agency/Company /Organization Argonne National Laboratory Partner Institute for Systems and Computer Engineering of Porto (INESC Porto) in Portugal, Midwest Independent System Operator and Horizon Wind Energy LLC, funded by U.S. Department of Energy Sector Energy Focus Area Wind Topics Pathways analysis, Technology characterizations Resource Type Software/modeling tools Website http://www.dis.anl.gov/project References Argonne National Laboratory: Wind Power Forecasting and Electricity Markets[1] Abstract To improve wind power forecasting and its use in power system and electricity market operations Argonne National Laboratory has assembled a team of experts in wind power forecasting, electricity market modeling, wind farm development, and power system operations.

409

,"Price of U.S. Liquefied Natural Gas Imports From Egypt (Dollars per Thousand Cubic Feet)"  

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

Egypt (Dollars per Thousand Cubic Feet)" Egypt (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Price of U.S. Liquefied Natural Gas Imports From Egypt (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n9103eg3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n9103eg3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

410

,"South Carolina Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","South Carolina Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)",1,"Annual",2005 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1480_ssc_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1480_ssc_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

411

,"North Carolina Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Carolina Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)",1,"Annual",2005 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1480_snc_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1480_snc_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

412

,"New Hampshire Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Hampshire Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)",1,"Annual",2005 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1480_snh_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1480_snh_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

413

,"North Dakota Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)",1,"Annual",2005 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1480_snd_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1480_snd_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

414

,"Price of U.S. Liquefied Natural Gas Imports From Nigeria (Dollars per Thousand Cubic Feet)"  

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

Nigeria (Dollars per Thousand Cubic Feet)" Nigeria (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Price of U.S. Liquefied Natural Gas Imports From Nigeria (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n9103ng3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n9103ng3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

415

,"New York Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New York Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)",1,"Annual",2005 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1480_sny_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1480_sny_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

416

,"Price of U.S. Liquefied Natural Gas Imports From Indonesia (Dollars per Thousand Cubic Feet)"  

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

Indonesia (Dollars per Thousand Cubic Feet)" Indonesia (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Price of U.S. Liquefied Natural Gas Imports From Indonesia (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n9103id3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n9103id3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

417

,"West Virginia Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","West Virginia Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)",1,"Annual",2005 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1480_swv_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1480_swv_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

418

,"New Mexico Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)",1,"Annual",2005 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1480_snm_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1480_snm_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

419

,"Price of U.S. Liquefied Natural Gas Imports From Malaysia (Dollars per Thousand Cubic Feet)"  

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

Malaysia (Dollars per Thousand Cubic Feet)" Malaysia (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Price of U.S. Liquefied Natural Gas Imports From Malaysia (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n9103my3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n9103my3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

420

,"Price of U.S. Liquefied Natural Gas Imports From Australia (Dollars per Thousand Cubic Feet)"  

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

Australia (Dollars per Thousand Cubic Feet)" Australia (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Price of U.S. Liquefied Natural Gas Imports From Australia (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n9103au3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n9103au3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

Note: This page contains sample records for the topic "forecast thousand barrels" 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

,"New Jersey Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Jersey Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)",1,"Annual",2005 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1480_snj_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1480_snj_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

422

,"Price of U.S. Liquefied Natural Gas Imports From Qatar (Dollars per Thousand Cubic Feet)"  

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

Qatar (Dollars per Thousand Cubic Feet)" Qatar (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Price of U.S. Liquefied Natural Gas Imports From Qatar (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n9103qr3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n9103qr3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

423

,"Price of U.S. Liquefied Natural Gas Imports From Brunei (Dollars per Thousand Cubic Feet)"  

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

Brunei (Dollars per Thousand Cubic Feet)" Brunei (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Price of U.S. Liquefied Natural Gas Imports From Brunei (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n9103bx3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n9103bx3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

424

,"Price of U.S. Natural Gas Pipeline Imports From Mexico (Dollars per Thousand Cubic Feet)"  

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

Mexico (Dollars per Thousand Cubic Feet)" Mexico (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Price of U.S. Natural Gas Pipeline Imports From Mexico (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n9102mx3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n9102mx3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

425

,"Price of U.S. Liquefied Natural Gas Imports From Oman (Dollars per Thousand Cubic Feet)"  

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

Oman (Dollars per Thousand Cubic Feet)" Oman (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Price of U.S. Liquefied Natural Gas Imports From Oman (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","n9103mu3m.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/n9103mu3m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

426

,"South Dakota Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)"  

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

Price (Dollars per Thousand Cubic Feet)" Price (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","South Dakota Natural Gas Pipeline and Distribution Use Price (Dollars per Thousand Cubic Feet)",1,"Annual",2005 ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","na1480_ssd_3a.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/na1480_ssd_3a.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

427

Workbook Contents  

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

Products (Thousand Barrels)","Midwest (PADD 2) Imports by PADD of Processing from Germany of Crude Oil and Petroleum Products (Thousand Barrels)","Midwest (PADD 2) Imports by...

428

Workbook Contents  

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

(Thousand Barrels)","Rocky Mountain (PADD 4) Imports by PADD of Processing from Russia of Crude Oil and Petroleum Products (Thousand Barrels)" 29767,18390 30132,21766...

429

Workbook Contents  

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

(Thousand Barrels)","Rocky Mountain (PADD 4) Imports by PADD of Processing from Russia of Crude Oil and Petroleum Products (Thousand Barrels)" 29601,2712 29632,1641...

430

Workbook Contents  

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

Marketable Petroleum Coke Consumed at Refineries (Thousand Barrels)","U.S. Catalyst Petroleum Coke Consumed at Refineries (Thousand Barrels)","U.S. Other Products...

431

California Onshore Natural Gas Total Liquids Extracted in California...  

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

Total Liquids Extracted in California (Thousand Barrels) California Onshore Natural Gas Total Liquids Extracted in California (Thousand Barrels) Decade Year-0 Year-1 Year-2 Year-3...

432

,"U.S. Blender Net Input"  

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

Blender Net Input of Residuum (Thousand Barrels)","U.S. Blender Net Input of Gasoline Blending Components (Thousand Barrels)","U.S. Blender Net Input of Reformulated...

433

This Week In Petroleum Printer-Friendly Version  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Hydrogen, and Oxygenates (including fuel ethanol) 493 thousand barrels per day Motor Gasoline Blending Components (net) 152 thousand barrels per day Adjusted Finished Motor...

434

OpenEI Community - energy data + forecasting  

Open Energy Info (EERE)

FRED FRED http://en.openei.org/community/group/fred Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in formulating policies and energy plans based on easy to use forecasting tools, visualizations, sankey diagrams, and open data. The platform will live on OpenEI and this community was established to initiate discussion around continuous development of this tool, integrating it with new datasets, and connecting with the community of users who will want to contribute data to the tool and use the tool for planning purposes. energy data + forecasting Fri, 22 Jun 2012 15:30:20 +0000 Dbrodt 34

435

Voluntary Green Power Market Forecast through 2015  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

158 158 May 2010 Voluntary Green Power Market Forecast through 2015 Lori Bird National Renewable Energy Laboratory Ed Holt Ed Holt & Associates, Inc. Jenny Sumner and Claire Kreycik National Renewable Energy Laboratory National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 * www.nrel.gov NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Operated by the Alliance for Sustainable Energy, LLC Contract No. DE-AC36-08-GO28308 Technical Report NREL/TP-6A2-48158 May 2010 Voluntary Green Power Market Forecast through 2015 Lori Bird National Renewable Energy Laboratory Ed Holt Ed Holt & Associates, Inc. Jenny Sumner and Claire Kreycik National Renewable Energy Laboratory

436

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Highlights Highlights World energy consumption is projected to increase by 57 percent from 2002 to 2025. Much of the growth in worldwide energy use in the IEO2005 reference case forecast is expected in the countries with emerging economies. Figure 1. World Marketed Energy Consumptiion by Region, 1970-2025. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data In the International Energy Outlook 2005 (IEO2005) reference case, world marketed energy consumption is projected to increase on average by 2.0 percent per year over the 23-year forecast horizon from 2002 to 2025—slightly lower than the 2.2-percent average annual growth rate from 1970 to 2002. Worldwide, total energy use is projected to grow from 412 quadrillion British thermal units (Btu) in 2002 to 553 quadrillion Btu in

437

FORSITE: a geothermal site development forecasting system  

SciTech Connect (OSTI)

The Geothermal Site Development Forecasting System (FORSITE) is a computer-based system being developed to assist DOE geothermal program managers in monitoring the progress of multiple geothermal electric exploration and construction projects. The system will combine conceptual development schedules with site-specific status data to predict a time-phased sequence of development likely to occur at specific geothermal sites. Forecasting includes estimation of industry costs and federal manpower requirements across sites on a year-by-year basis. The main advantage of the system, which relies on reporting of major, easily detectable industry activities, is its ability to use relatively sparse data to achieve a representation of status and future development.

Entingh, D.J.; Gerstein, R.E.; Kenkeremath, L.D.; Ko, S.M.

1981-10-01T23:59:59.000Z

438

Forecasting hotspots using predictive visual analytics approach  

SciTech Connect (OSTI)

A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.

Maciejewski, Ross; Hafen, Ryan; Rudolph, Stephen; Cleveland, William; Ebert, David

2014-12-30T23:59:59.000Z

439

Exponential smoothing model selection for forecasting  

Science Journals Connector (OSTI)

Applications of exponential smoothing to forecasting time series usually rely on three basic methods: simple exponential smoothing, trend corrected exponential smoothing and a seasonal variation thereof. A common approach to selecting the method appropriate to a particular time series is based on prediction validation on a withheld part of the sample using criteria such as the mean absolute percentage error. A second approach is to rely on the most appropriate general case of the three methods. For annual series this is trend corrected exponential smoothing: for sub-annual series it is the seasonal adaptation of trend corrected exponential smoothing. The rationale for this approach is that a general method automatically collapses to its nested counterparts when the pertinent conditions pertain in the data. A third approach may be based on an information criterion when maximum likelihood methods are used in conjunction with exponential smoothing to estimate the smoothing parameters. In this paper, such approaches for selecting the appropriate forecasting method are compared in a simulation study. They are also compared on real time series from the M3 forecasting competition. The results indicate that the information criterion approaches provide the best basis for automated method selection, the Akaike information criteria having a slight edge over its information criteria counterparts.

Baki Billah; Maxwell L. King; Ralph D. Snyder; Anne B. Koehler

2006-01-01T23:59:59.000Z

440

Solar Wind Forecasting with Coronal Holes  

E-Print Network [OSTI]

An empirical model for forecasting solar wind speed related geomagnetic events is presented here. The model is based on the estimated location and size of solar coronal holes. This method differs from models that are based on photospheric magnetograms (e.g., Wang-Sheeley model) to estimate the open field line configuration. Rather than requiring the use of a full magnetic synoptic map, the method presented here can be used to forecast solar wind velocities and magnetic polarity from a single coronal hole image, along with a single magnetic full-disk image. The coronal hole parameters used in this study are estimated with Kitt Peak Vacuum Telescope He I 1083 nm spectrograms and photospheric magnetograms. Solar wind and coronal hole data for the period between May 1992 and September 2003 are investigated. The new model is found to be accurate to within 10% of observed solar wind measurements for its best one-month periods, and it has a linear correlation coefficient of ~0.38 for the full 11 years studied. Using a single estimated coronal hole map, the model can forecast the Earth directed solar wind velocity up to 8.5 days in advance. In addition, this method can be used with any source of coronal hole area and location data.

S. Robbins; C. J. Henney; J. W. Harvey

2007-01-09T23:59:59.000Z

Note: This page contains sample records for the topic "forecast thousand barrels" 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

Today's Forecast: Improved Wind Predictions | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

442

Annual Energy Outlook with Projections to 2025-Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Annual Energy Outlook 2004 with Projections to 2025 Forecast Comparisons Index (click to jump links) Economic Growth World Oil Prices Total Energy Consumption Electricity Natural Gas Petroleum Coal The AEO2004 forecast period extends through 2025. One other organization—Global Insight, Incorporated (GII)—produces a comprehensive energy projection with a similar time horizon. Several others provide forecasts that address one or more aspects of energy markets over different time horizons. Recent projections from GII and others are compared here with the AEO2004 projections. Economic Growth Printer Friendly Version Average annual percentage growth Forecast 2002-2008 2002-2013 2002-2025 AEO2003 3.2 3.3 3.1 AEO2004 Reference 3.3 3.2 3.0

443

Today's Forecast: Improved Wind Predictions | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

444

Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint  

SciTech Connect (OSTI)

Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The results show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.

Zhang, J.; Hodge, B. M.; Florita, A.; Lu, S.; Hamann, H. F.; Banunarayanan, V.

2013-10-01T23:59:59.000Z

445

Electric Grid - Forecasting system licensed | ornl.gov  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Electric Grid - Forecasting system licensed Location Based Technologies has signed an agreement to integrate and market an Oak Ridge National Laboratory technology that provides...

446

Managing Wind Power Forecast Uncertainty in Electric Grids.  

E-Print Network [OSTI]

??Electricity generated from wind power is both variable and uncertain. Wind forecasts provide valuable information for wind farm management, but they are not perfect. Chapter… (more)

Mauch, Brandon Keith

2012-01-01T23:59:59.000Z

447

Forecasting supply/demand and price of ethylene feedstocks  

SciTech Connect (OSTI)

The history of the petrochemical industry over the past ten years clearly shows that forecasting in a turbulent world is like trying to predict tomorrow's headlines.

Struth, B.W.

1984-08-01T23:59:59.000Z

448

PBL FY 2003 Third Quarter Review Forecast of Generation Accumulated...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net Cost Recovery Adjustment Clause (SN CRAC) FY 2003 Third Quarter Review Forecast in Millions...

449

FY 2004 Second Quarter Review Forecast of Generation Accumulated...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net Cost Recovery Adjustment Clause (SN CRAC) FY 2004 Second Quarter Review Forecast In Millions...

450

Integrating agricultural pest biocontrol into forecasts of energy biomass production  

E-Print Network [OSTI]

Analysis Integrating agricultural pest biocontrol into forecasts of energy biomass production T pollution, greenhouse gas emissions, and soil erosion (Nash, 2007; Searchinger et al., 2008). On the other

Gratton, Claudio

451

Forecasting for inventory control with exponential smoothing  

Science Journals Connector (OSTI)

Exponential smoothing, often used in sales forecasting for inventory control, has always been rationalized in terms of statistical models that possess errors with constant variances. It is shown in this paper that exponential smoothing remains appropriate under more general conditions, where the variance is allowed to grow or contract with corresponding movements in the underlying level. The implications for estimation and prediction are explored. In particular, the problem of finding the predictive distribution of aggregate lead-time demand, for use in inventory control calculations, is considered using a bootstrap approach. A method for establishing order-up-to levels directly from the simulated predictive distribution is also explored.

Ralph D. Snyder; Anne B. Koehler; J.Keith Ord

2002-01-01T23:59:59.000Z

452

Probabilistic Verification of Global and Mesoscale Ensemble Forecasts of Tropical Cyclogenesis  

Science Journals Connector (OSTI)

Probabilistic forecasts of tropical cyclogenesis have been evaluated for two samples: a near-homogeneous sample of ECMWF and Weather Research and Forecasting (WRF) Model–ensemble Kalman filter (EnKF) ensemble forecasts during the National Science ...

Sharanya J. Majumdar; Ryan D. Torn

2014-10-01T23:59:59.000Z

453

"Economic","per Employee","of Value Added","of Shipments" "Characteristic(a)","(million Btu)","(thousand Btu)","(thousand Btu)"  

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

2 Relative Standard Errors for Table 6.2;" 2 Relative Standard Errors for Table 6.2;" " Unit: Percents." ,,,"Consumption" " ",,"Consumption","per Dollar" " ","Consumption","per Dollar","of Value" "Economic","per Employee","of Value Added","of Shipments" "Characteristic(a)","(million Btu)","(thousand Btu)","(thousand Btu)" ,"Total United States" "Value of Shipments and Receipts" "(million dollars)" " Under 20",3,3,3 " 20-49",5,5,4 " 50-99",6,5,4 " 100-249",5,5,4 " 250-499",7,9,7 " 500 and Over",3,2,2 "Total",2,2,2

454

,"Price of U.S. Liquefied Natural Gas Imports From Canada (Dollars per Thousand Cubic Feet)"  

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

Canada (Dollars per Thousand Cubic Feet)" Canada (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Price of U.S. Liquefied Natural Gas Imports From Canada (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","ngm_epg0_nus-nca_pml_dmcfm.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/ngm_epg0_nus-nca_pml_dmcfm.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

455

,"Price of U.S. Liquefied Natural Gas Imports From Norway (Dollars per Thousand Cubic Feet)"  

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

Norway (Dollars per Thousand Cubic Feet)" Norway (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Price of U.S. Liquefied Natural Gas Imports From Norway (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","ngm_epg0_nus-nno_pml_dmcfm.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/ngm_epg0_nus-nno_pml_dmcfm.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

456

,"Price of U.S. Liquefied Natural Gas Imports From Yemen (Dollars per Thousand Cubic Feet)"  

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

Yemen (Dollars per Thousand Cubic Feet)" Yemen (Dollars per Thousand Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Price of U.S. Liquefied Natural Gas Imports From Yemen (Dollars per Thousand Cubic Feet)",1,"Monthly","9/2013" ,"Release Date:","12/12/2013" ,"Next Release Date:","1/7/2014" ,"Excel File Name:","ngm_epg0_pml_nus-nye_dmcfm.xls" ,"Available from Web Page:","http://tonto.eia.gov/dnav/ng/hist/ngm_epg0_pml_nus-nye_dmcfm.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.doe.gov"

457

Random switching exponential smoothing and inventory forecasting  

Science Journals Connector (OSTI)

Abstract Exponential smoothing models represent an important prediction tool both in business and in macroeconomics. This paper provides the analytical forecasting properties of the random coefficient exponential smoothing model in the “multiple source of error” framework. The random coefficient state-space representation allows for switching between simple exponential smoothing and local linear trend. Therefore it enables controlling, in a flexible manner, the random changing dynamic behavior of the time series. The paper establishes the algebraic mapping between the state-space parameters and the implied reduced form ARIMA parameters. In addition, it shows that the parametric mapping allows overcoming the difficulties that are likely to emerge in estimating directly the random coefficient state-space model. Finally, it presents an empirical application comparing the forecast accuracy of the suggested model vis-à-vis other benchmark models, both in the ARIMA and in the exponential smoothing class. Using time series relative to wholesalers inventories in the USA, the out-of-sample results show that the reduced form of the random coefficient exponential smoothing model tends to be superior to its competitors.

Giacomo Sbrana; Andrea Silvestrini

2014-01-01T23:59:59.000Z

458

Voluntary Green Power Market Forecast through 2015  

SciTech Connect (OSTI)

Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

2010-05-01T23:59:59.000Z

459

Expert Panel: Forecast Future Demand for Medical Isotopes  

Broader source: Energy.gov (indexed) [DOE]

Expert Panel: Expert Panel: Forecast Future Demand for Medical Isotopes March 1999 Expert Panel: Forecast Future Demand for Medical Isotopes September 25-26, 1998 Arlington, Virginia The Expert Panel ............................................................................................. Page 1 Charge To The Expert Panel........................................................................... Page 2 Executive Summary......................................................................................... Page 3 Introduction ...................................................................................................... Page 4 Rationale.......................................................................................................... Page 6 Economic Analysis...........................................................................................

460

A robust automatic phase-adjustment method for financial forecasting  

Science Journals Connector (OSTI)

In this work we present the robust automatic phase-adjustment (RAA) method to overcome the random walk dilemma for financial time series forecasting. It consists of a hybrid model composed of a qubit multilayer perceptron (QuMLP) with a quantum-inspired ... Keywords: Financial forecasting, Hybrid models, Quantum-inspired evolutionary algorithm, Qubit multilayer perceptron, Random walk dilemma

Ricardo de A. Araújo

2012-03-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecast thousand barrels" 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

Short term forecasting of solar radiation based on satellite data  

E-Print Network [OSTI]

Short term forecasting of solar radiation based on satellite data Elke Lorenz, Annette Hammer University, D-26111 Oldenburg Forecasting of solar irradiance will become a major issue in the future integration of solar energy resources into existing energy supply structures. Fluctuations of solar irradiance

Heinemann, Detlev

462

Developing electricity forecast web tool for Kosovo market  

Science Journals Connector (OSTI)

In this paper is presented a web tool for electricity forecast for Kosovo market for the upcoming ten years. The input data i.e. electricity generation capacities, demand and consume are taken from the document "Kosovo Energy Strategy 2009-2018" compiled ... Keywords: .NET, database, electricity forecast, internet, simulation, web

Blerim Rexha; Arben Ahmeti; Lule Ahmedi; Vjollca Komoni

2011-02-01T23:59:59.000Z

463

FORECASTING WATER DEMAND USING CLUSTER AND REGRESSION ANALYSIS  

E-Print Network [OSTI]

resources resulting in water stress. Effective water management ­ a solution Supply side management Demand side management #12;Developing a regression equation based on cluster analysis for forecasting waterFORECASTING WATER DEMAND USING CLUSTER AND REGRESSION ANALYSIS by Bruce Bishop Professor of Civil

Keller, Arturo A.

464

Impact of PV forecasts uncertainty in batteries management in microgrids  

E-Print Network [OSTI]

production forecast algorithm is used in combination with a battery schedule optimisation algorithm. The size. On the other hand if forecasted high production events do not occur, the cost of de- optimisation Energies and Energy Systems Sophia Antipolis, France andrea.michiorri@mines-paristech.fr Abstract

Paris-Sud XI, Université de

465

Revised 1997 Retail Electricity Price Forecast Principal Author: Ben Arikawa  

E-Print Network [OSTI]

Revised 1997 Retail Electricity Price Forecast March 1998 Principal Author: Ben Arikawa Electricity 1997 FORE08.DOC Page 1 CALIFORNIA ENERGY COMMISSION ELECTRICITY ANALYSIS OFFICE REVISED 1997 RETAIL ELECTRICITY PRICE FORECAST Introduction The Electricity Analysis Office of the California Energy Commission

466

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center  

E-Print Network [OSTI]

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at wind energy sites are becoming paramount. Regime-switching space-time (RST) models merge meteorological forecast regimes at the wind energy site and fits a conditional predictive model for each regime

Washington at Seattle, University of

467

A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size  

E-Print Network [OSTI]

A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size Andrew. R.Lawrence@ecmwf.int #12;Abstract An ensemble-based data assimilation approach is used to transform old en- semble. The impact of the transformations are propagated for- ward in time over the ensemble's forecast period

Hansens, Jim

468

Improving baseline forecasts in a 500-industry dynamic CGE model of the USA.  

E-Print Network [OSTI]

??MONASH-style CGE models have been used to generate baseline forecasts illustrating how an economy is likely to evolve through time. One application of such forecasts… (more)

Mavromatis, Peter George

2013-01-01T23:59:59.000Z

469

E-Print Network 3.0 - africa conditional forecasts Sample Search...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Search Powered by Explorit Topic List Advanced Search Sample search results for: africa conditional forecasts Page: << < 1 2 3 4 5 > >> 1 COLORADO STATE UNIVERSITY FORECAST...

470

Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA  

SciTech Connect (OSTI)

In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction intervals of forecasts. We use automatically coupled wavelet transform and autoregressive integrated moving-average (ARIMA) forecasting to reflect multi-scale variability of forecast errors. The proposed analysis reveals slow-changing “quasi-deterministic” components of forecast errors. This helps improve forecasts produced by other means, e.g., using weather-based models, and reduce forecast errors prediction intervals.

Hou, Zhangshuan; Etingov, Pavel V.; Makarov, Yuri V.; Samaan, Nader A.

2014-10-27T23:59:59.000Z

471

Of the estimated 5 million barrels of crude oil released into the Gulf of Mexico from the Deepwater Horizon oil spill, a  

E-Print Network [OSTI]

Of the estimated 5 million barrels of crude oil released into the Gulf of Mexico from the Deepwater Horizon oil spill, a fraction washed ashore onto sandy beaches from Louisiana to the Florida panhandle. Researchers at the MagLab compare the detailed molecular analysis of hydrocarbons in oiled sands from

Weston, Ken

472

Microbial Fuel Cells -Solar Times http://solar.rain-barrel.net/microbial-fuel-cells/ 1 of 3 6/28/2006 11:32 AM  

E-Print Network [OSTI]

.com Hydrogen Fuel Cells Buy Commercial & Educational Stacks PEM, Fuel Cell Generators & More! www.TheHydrogenCompany.com Hydrogen Fuel Cell Improve Your Fuel Economy 20 to 50% Begin Saving Fuel Now www.SaveMoreWithHydrogenMicrobial Fuel Cells - Solar Times http://solar.rain-barrel.net/microbial-fuel-cells/ 1 of 3 6

Lovley, Derek

473

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Electricity Electricity Electricity consumption nearly doubles in the IEO2005 projection period. The emerging economies of Asia are expected to lead the increase in world electricity use. Figure 58. World Net Electricity Consumption, 2002-2025 (Billion Kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 59. World Net Electricity Consumption by Region, 2002-2025 (Billion Kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data The International Energy Outlook 2005 (IEO2005) reference case projects that world net electricity consumption will nearly double over the next two decades.10 Over the forecast period, world electricity demand is projected to grow at an average rate of 2.6 percent per year, from 14,275 billion

474

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Contacts Contacts The International Energy Outlook is prepared by the Energy Information Administration (EIA). General questions concerning the contents of the report should be referred to John J. Conti (john.conti@eia.doe.gov, 202-586-2222), Director, Office of Integrated Analysis and Forecasting. Specific questions about the report should be referred to Linda E. Doman (202/586-1041) or the following analysts: World Energy and Economic Outlook Linda Doman (linda.doman@eia.doe.gov, 202-586-1041) Macroeconomic Assumptions Nasir Khilji (nasir.khilji@eia.doe.gov, 202-586-1294) Energy Consumption by End-Use Sector Residential Energy Use John Cymbalsky (john.cymbalsky@eia.doe.gov, 202-586-4815) Commercial Energy Use Erin Boedecker (erin.boedecker@eia.doe.gov, 202-586-4791)

475

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Natural Gas Natural gas is the fastest growing primary energy source in the IEO2005 forecast. Consumption of natural gas is projected to increase by nearly 70 percent between 2002 and 2025, with the most robust growth in demand expected among the emerging economies. Figure 34. World Natural Gas Consumption, 1980-2025 (Trillion Cubic Feet). Need help, contact the National Energy Information Center on 202-586-8800. Figure Data Figure 35. Natural Gas Consumption by Region, 1980-2025 (Trillion Cubic Feet). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 36. Increase in Natural Gas Consumption by Region and Country, 2002-2025. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data

476

Annual Energy Outlook 1998 Forecasts - Preface  

Gasoline and Diesel Fuel Update (EIA)

1998 With Projections to 2020 1998 With Projections to 2020 Annual Energy Outlook 1999 Report will be Available on December 9, 1998 Preface The Annual Energy Outlook 1998 (AEO98) presents midterm forecasts of energy supply, demand, and prices through 2020 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA's National Energy Modeling System (NEMS). The report begins with an “Overview” summarizing the AEO98 reference case. The next section, “Legislation and Regulations,” describes the assumptions made with regard to laws that affect energy markets and discusses evolving legislative and regulatory issues. “Issues in Focus” discusses three current energy issues—electricity restructuring, renewable portfolio standards, and carbon emissions. It is followed by the analysis

477

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Energy Consumption by End-Use Sector Energy Consumption by End-Use Sector In the IEO2005 projections, end-use energy consumption in the residential, commercial, industrial, and transportation sectors varies widely among regions and from country to country. One way of looking at the future of world energy markets is to consider trends in energy consumption at the end-use sector level. With the exception of the transportation sector, which is almost universally dominated by petroleum products at present, the mix of energy use in the residential, commercial, and industrial sectors can vary widely from country to country, depending on a combination of regional factors, such as the availability of energy resources, the level of economic development, and political, social, and demographic factors. This chapter outlines the International Energy Outlook 2005 (IEO2005) forecast for regional energy consumption by end-use sector.

478

Volatility forecasting with smooth transition exponential smoothing  

Science Journals Connector (OSTI)

Adaptive exponential smoothing methods allow smoothing parameters to change over time, in order to adapt to changes in the characteristics of the time series. This paper presents a new adaptive method for predicting the volatility in financial returns. It enables the smoothing parameter to vary as a logistic function of user-specified variables. The approach is analogous to that used to model time-varying parameters in smooth transition generalised autoregressive conditional heteroskedastic (GARCH) models. These non-linear models allow the dynamics of the conditional variance model to be influenced by the sign and size of past shocks. These factors can also be used as transition variables in the new smooth transition exponential smoothing (STES) approach. Parameters are estimated for the method by minimising the sum of squared deviations between realised and forecast volatility. Using stock index data, the new method gave encouraging results when compared to fixed parameter exponential smoothing and a variety of GARCH models.

James W. Taylor

2004-01-01T23:59:59.000Z

479

Incorporating Forecast Uncertainty in Utility Control Center  

SciTech Connect (OSTI)

Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)

Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian

2014-07-09T23:59:59.000Z

480

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Table 1. Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Table 1. Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Average Absolute Percent Error Variable AEO82 to AEO98 AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 AEO82 to AEO2003 Consumption Total Energy Consumption 1.7 1.7 1.8 1.9 1.9 2.1 Total Petroleum Consumption 2.9 2.8 2.9 3.0 2.9 2.9 Total Natural Gas Consumption 5.7 5.6 5.6 5.5 5.5 6.5 Total Coal Consumption 3.0 3.2 3.3 3.5 3.6 3.7 Total Electricity Sales 1.7 1.8 1.9 2.4 2.5 2.4 Production Crude Oil Production 4.3 4.5 4.5 4.5 4.5 4.7 Natural Gas Production 4.8 4.7 4.6 4.6 4.4 4.4 Coal Production 3.6 3.6 3.5 3.7 3.6 3.8 Imports and Exports Net Petroleum Imports 9.5 8.8 8.4 7.9 7.4 7.5 Net Natural Gas Imports 16.7 16.0 15.9 15.8 15.8 15.4

Note: This page contains sample records for the topic "forecast thousand barrels" 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

Coal production forecast and low carbon policies in China  

Science Journals Connector (OSTI)

With rapid economic growth and industrial expansion, China consumes more coal than any other nation. Therefore, it is particularly crucial to forecast China's coal production to help managers make strategic decisions concerning China's policies intended to reduce carbon emissions and concerning the country's future needs for domestic and imported coal. Such decisions, which must consider results from forecasts, will have important national and international effects. This article proposes three improved forecasting models based on grey systems theory: the Discrete Grey Model (DGM), the Rolling DGM (RDGM), and the p value RDGM. We use the statistical data of coal production in China from 1949 to 2005 to validate the effectiveness of these improved models to forecast the data from 2006 to 2010. The performance of the models demonstrates that the p value RDGM has the best forecasting behaviour over this historical time period. Furthermore, this paper forecasts coal production from 2011 to 2015 and suggests some policies for reducing carbon and other emissions that accompany the rise in forecasted coal production.

Jianzhou Wang; Yao Dong; Jie Wu; Ren Mu; He Jiang

2011-01-01T23:59:59.000Z

482

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect (OSTI)

The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

2005-07-01T23:59:59.000Z

483

Measuring the forecasting accuracy of models: evidence from industrialised countries  

Science Journals Connector (OSTI)

This paper uses the approach suggested by Akrigay (1989), Tse and Tung (1992) and Dimson and Marsh (1990) to examine the forecasting accuracy of stock price index models for industrialised markets. The focus of this paper is to compare the Mean Absolute Percentage Error (MAPE) of three models, that is, the Random Walk model, the Single Exponential Smoothing model and the Conditional Heteroskedastic model with the MAPE of the benchmark Naive Forecast 1 case. We do not evidence that a single model to provide better forecasting accuracy results compared to other models.

Athanasios Koulakiotis; Apostolos Dasilas

2009-01-01T23:59:59.000Z

484

Solar irradiance forecasting at multiple time horizons and novel methods to evaluate uncertainty  

E-Print Network [OSTI]

Solar irradiance data . . . . . . . . . . . . .Accuracy . . . . . . . . . . . . . . . . . Solar Resourcev Uncertainty In Solar Resource: Forecasting

Marquez, Ricardo

2012-01-01T23:59:59.000Z

485

18 Bureau of Meteorology Annual Report 201314 Hazards, warnings and forecasts  

E-Print Network [OSTI]

and numerical prediction models. #12;19Bureau of Meteorology Annual Report 2013­14 2 Performance Performance programs: · Weather forecasting services; · Flood forecasting and warning services; · Hazard prediction, Warnings and Forecasts portfolio provides a range of forecast and warning services covering weather, ocean

Greenslade, Diana

486

Sunco Oil manufactures three types of gasoline (gas 1, gas 2 and gas 3). Each type is produced by blending three types of crude oil (crude 1, crude 2 and crude 3). The sales price per barrel of gasoline and the purchase price per  

E-Print Network [OSTI]

Sunco Oil manufactures three types of gasoline (gas 1, gas 2 and gas 3). Each type is produced by blending three types of crude oil (crude 1, crude 2 and crude 3). The sales price per barrel of gasoline and the purchase price per barrel of crude oil are given in following table: Gasoline Sale Price per barrel Gas 1

Phillips, David

487

THE GALEX TIME DOMAIN SURVEY. I. SELECTION AND CLASSIFICATION OF OVER A THOUSAND ULTRAVIOLET VARIABLE SOURCES  

SciTech Connect (OSTI)

We present the selection and classification of over a thousand ultraviolet (UV) variable sources discovered in {approx}40 deg{sup 2} of GALEX Time Domain Survey (TDS) NUV images observed with a cadence of 2 days and a baseline of observations of {approx}3 years. The GALEX TDS fields were designed to be in spatial and temporal coordination with the Pan-STARRS1 Medium Deep Survey, which provides deep optical imaging and simultaneous optical transient detections via image differencing. We characterize the GALEX photometric errors empirically as a function of mean magnitude, and select sources that vary at the 5{sigma} level in at least one epoch. We measure the statistical properties of the UV variability, including the structure function on timescales of days and years. We report classifications for the GALEX TDS sample using a combination of optical host colors and morphology, UV light curve characteristics, and matches to archival X-ray, and spectroscopy catalogs. We classify 62% of the sources as active galaxies (358 quasars and 305 active galactic nuclei), and 10% as variable stars (including 37 RR Lyrae, 53 M dwarf flare stars, and 2 cataclysmic variables). We detect a large-amplitude tail in the UV variability distribution for M-dwarf flare stars and RR Lyrae, reaching up to |{Delta}m| = 4.6 mag and 2.9 mag, respectively. The mean amplitude of the structure function for quasars on year timescales is five times larger than observed at optical wavelengths. The remaining unclassified sources include UV-bright extragalactic transients, two of which have been spectroscopically confirmed to be a young core-collapse supernova and a flare from the tidal disruption of a star by dormant supermassive black hole. We calculate a surface density for variable sources in the UV with NUV < 23 mag and |{Delta}m| > 0.2 mag of {approx}8.0, 7.7, and 1.8 deg{sup -2} for quasars, active galactic nuclei, and RR Lyrae stars, respectively. We also calculate a surface density rate in the UV for transient sources, using the effective survey time at the cadence appropriate to each class, of {approx}15 and 52 deg{sup -2} yr{sup -1} for M dwarfs and extragalactic transients, respectively.

Gezari, S. [Department of Astronomy, University of Maryland, College Park, MD 20742-2421 (United States)] [Department of Astronomy, University of Maryland, College Park, MD 20742-2421 (United States); Martin, D. C.; Forster, K.; Neill, J. D.; Morrissey, P.; Wyder, T. K. [Astronomy Department, California Institute of Technology, MC 249-17, 1200 East California Boulevard, Pasadena, CA 91125 (United States)] [Astronomy Department, California Institute of Technology, MC 249-17, 1200 East California Boulevard, Pasadena, CA 91125 (United States); Huber, M.; Burgett, W. S.; Chambers, K. C.; Kaiser, N.; Magnier, E. A.; Tonry, J. L. [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States)] [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States); Heckman, T.; Bianchi, L. [Department of Physics and Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States)] [Department of Physics and Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States); Neff, S. G. [Laboratory for Astronomy and Solar Physics, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States)] [Laboratory for Astronomy and Solar Physics, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Seibert, M. [Observatories of the Carnegie Institute of Washington, Pasadena, CA 90095 (United States)] [Observatories of the Carnegie Institute of Washington, Pasadena, CA 90095 (United States); Schiminovich, D. [Department of Astronomy, Columbia University, New York, NY 10027 (United States)] [Department of Astronomy, Columbia University, New York, NY 10027 (United States); Price, P. A., E-mail: suvi@astro.umd.edu [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States)

2013-03-20T23:59:59.000Z

488

"Economic","per Employee","of Value Added","of Shipments" "Characteristic(a)","(million Btu)","(thousand Btu)","(thousand Btu)"  

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

2 Relative Standard Errors for Table 6.2;" 2 Relative Standard Errors for Table 6.2;" " Unit: Percents." ,,,"Consumption" ,,"Consumption","per Dollar" ,"Consumption","per Dollar","of Value" "Economic","per Employee","of Value Added","of Shipments" "Characteristic(a)","(million Btu)","(thousand Btu)","(thousand Btu)" ,"Total United States" "Value of Shipments and Receipts" "(million dollars)" " Under 20",2.5,2.5,2.4 " 20-49",5,5,4.3 " 50-99",5.8,5.8,5.3 " 100-249",6.2,6.2,5.3 " 250-499",8.2,8,7.1 " 500 and Over",4.3,3,2.7

489

Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) | Open  

Open Energy Info (EERE)

Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Jump to: navigation, search LEDSGP green logo.png FIND MORE DIA TOOLS This tool is part of the Development Impacts Assessment (DIA) Toolkit from the LEDS Global Partnership. Tool Summary LAUNCH TOOL Name: Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Agency/Company /Organization: Energy Sector Management Assistance Program of the World Bank Sector: Energy Focus Area: Non-renewable Energy Topics: Baseline projection, Co-benefits assessment, GHG inventory Resource Type: Software/modeling tools User Interface: Spreadsheet Complexity/Ease of Use: Simple Website: www.esmap.org/esmap/EFFECT Cost: Free Equivalent URI: www.esmap.org/esmap/EFFECT Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Screenshot

490

Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory  

Gasoline and Diesel Fuel Update (EIA)

Forecasting Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory Levels MICHAEL YE, ∗ JOHN ZYREN, ∗∗ AND JOANNE SHORE ∗∗ Abstract This paper presents a short-term monthly forecasting model of West Texas Intermedi- ate crude oil spot price using OECD petroleum inventory levels. Theoretically, petroleum inventory levels are a measure of the balance, or imbalance, between petroleum production and demand, and thus provide a good market barometer of crude oil price change. Based on an understanding of petroleum market fundamentals and observed market behavior during the post-Gulf War period, the model was developed with the objectives of being both simple and practical, with required data readily available. As a result, the model is useful to industry and government decision-makers in forecasting price and investigat- ing the impacts of changes on price, should inventories,

491

Adaptive sampling and forecasting with mobile sensor networks  

E-Print Network [OSTI]

This thesis addresses planning of mobile sensor networks to extract the best information possible out of the environment to improve the (ensemble) forecast at some verification region in the future. To define the information ...

Choi, Han-Lim

2009-01-01T23:59:59.000Z

492

Pacific Adaptation Strategy Assistance Program Dynamical Seasonal Forecasting  

E-Print Network [OSTI]

Pacific Adaptation Strategy Assistance Program Dynamical Seasonal Forecasting Seasonal Prediction · POAMA · Issues for future Outline #12;Pacific Adaptation Strategy Assistance Program Major source Adaptation Strategy Assistance Program El Nino Mean State · Easterlies westward surface current upwelling

Lim, Eun-pa

493

Forecasting Volatility in Stock Market Using GARCH Models  

E-Print Network [OSTI]

Forecasting volatility has held the attention of academics and practitioners all over the world. The objective for this master's thesis is to predict the volatility in stock market by using generalized autoregressive ...

Yang, Xiaorong

2008-01-01T23:59:59.000Z

494

Exponential smoothing with covariates applied to electricity demand forecast  

Science Journals Connector (OSTI)

Exponential smoothing methods are widely used as forecasting techniques in industry and business. Their usual formulation, however, does not allow covariates to be used for introducing extra information into the forecasting process. In this paper, we analyse an extension of the exponential smoothing formulation that allows the use of covariates and the joint estimation of all the unknowns in the model, which improves the forecasting results. The whole procedure is detailed with a real example on forecasting the daily demand for electricity in Spain. The time series of daily electricity demand contains two seasonal patterns: here the within-week seasonal cycle is modelled as usual in exponential smoothing, while the within-year cycle is modelled using covariates, specifically two harmonic explanatory variables. Calendar effects, such as national and local holidays and vacation periods, are also introduced using covariates. [Received 28 September 2010; Revised 6 March 2011, 2 October 2011; Accepted 16 October 2011

José D. Bermúdez

2013-01-01T23:59:59.000Z

495

Initial conditions estimation for improving forecast accuracy in exponential smoothing  

Science Journals Connector (OSTI)

In this paper we analyze the importance of initial conditions in exponential smoothing models on forecast errors and prediction intervals. We work with certain exponential smoothing models, namely Holt’s additive...

E. Vercher; A. Corberán-Vallet; J. V. Segura; J. D. Bermúdez

2012-07-01T23:59:59.000Z

496

A Bayesian approach to forecast intermittent demand for seasonal products  

Science Journals Connector (OSTI)

This paper investigates the forecasting of a large fluctuating seasonal demand prior to peak sale season using a practical time series, collected from the US Census Bureau. Due to the extreme natural events (e.g. excessive snow fall and calamities), sales may not occur, inventory may not replenish and demand may set off unrecorded during the peak sale season. This characterises a seasonal time series to an intermittent category. A seasonal autoregressive integrated moving average (SARIMA), a multiplicative exponential smoothing (M-ES) and an effective modelling approach using Bayesian computational process are analysed in the context of seasonal and intermittent forecast. Several forecast error indicators and a cost factor are used to compare the models. In cost factor analysis, cost is measured optimally using dynamic programming model under periodic review policy. Experimental results demonstrate that Bayesian model performance is much superior to SARIMA and M-ES models, and efficient to forecast seasonal and intermittent demand.

Mohammad Anwar Rahman; Bhaba R. Sarker

2012-01-01T23:59:59.000Z

497

Review/Verify Strategic Skills Needs/Forecasts/Future Mission...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ReviewVerify Strategic Skills NeedsForecastsFuture Mission Shifts Annual Lab Plan (1-10 yrs) Fermilab Strategic Agenda (2-5 yrs) Sector program Execution Plans (1-3...

498

A Parameter for Forecasting Tornadoes Associated with Landfalling Tropical Cyclones  

Science Journals Connector (OSTI)

The authors develop a statistical guidance product, the tropical cyclone tornado parameter (TCTP), for forecasting the probability of one or more tornadoes during a 6-h period that are associated with landfalling tropical cyclones affecting the ...

Matthew J. Onderlinde; Henry E. Fuelberg

2014-10-01T23:59:59.000Z

499

Wind Power Forecasting: State-of-the-Art 2009  

E-Print Network [OSTI]

Wind Power Forecasting: State-of-the-Art 2009 ANL/DIS-10-1 Decision and Information Sciences about Argonne and its pioneering science and technology programs, see www.anl.gov. #12;Wind Power

Kemner, Ken

500

2007 National Hurricane Center Forecast Verification Report James L. Franklin  

E-Print Network [OSTI]

storms 17 4. Genesis Forecasts 17 5. Summary and Concluding Remarks 18 a. Atlantic Summary 18 statistical models, provided the best intensity guidance at each time period. The 2007 season marked the first