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1

Definition: Dynamic Pricing Program | Open Energy Information  

Open Energy Info (EERE)

Pricing Program Pricing Program Jump to: navigation, search Dictionary.png Dynamic Pricing Program Dynamic pricing refers to the family of rates that offer customers time-varying electricity prices on a day-ahead or real-time basis.[1] Related Terms electricity generation References ↑ https://www.smartgrid.gov/category/technology/dynamic_pricing_program [[C LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ategory: Smart Grid Definitionssmart grid,smart grid, |Template:BASEPAGENAME]]smart grid,smart grid, Retrieved from "http://en.openei.org/w/index.php?title=Definition:Dynamic_Pricing_Program&oldid=502620" Category: Definitions What links here Related changes Special pages Printable version Permanent link Browse properties 429 Throttled (bot load)

2

Essays on Price Dynamics  

E-Print Network (OSTI)

Small Regular Price Changes . . . . . . . . . . . . . . .4 The Cyclicality of Effective Prices2.3 Wholesale Price vs. Retail

Hong, Gee Hee

2012-01-01T23:59:59.000Z

3

Dynamic Pricing: A learning Approach  

E-Print Network (OSTI)

We present an optimization approach for jointly learning the demand as a functionof price, and dynamically setting prices of products in an oligopoly environment in order to maximize expected revenue. The models we consider ...

Bertsimas, Dimitris J.

4

Fairness and dynamic pricing: comments  

Science Conference Proceedings (OSTI)

In ''The Ethics of Dynamic Pricing,'' Ahmad Faruqui lays out a case for improved efficiency in using dynamic prices for retail electricity tariffs and addresses various issues about the distributional effects of alternative pricing mechanisms. The principal contrast is between flat or nearly constant energy prices and time-varying prices that reflect more closely the marginal costs of energy and capacity. The related issues of fairness criteria, contracts, risk allocation, cost allocation, means testing, real-time pricing, and ethical policies of electricity market design also must be considered. (author)

Hogan, William W.

2010-07-15T23:59:59.000Z

5

The Dynamics of Price Discovery ?  

E-Print Network (OSTI)

When arbitrage related prices share the same underlying asset, there are multiple channels to incorporate new information on the fundamental value of the asset. In this paper, we present an empirical microstructure model to characterize each channel’s price discovery speed. We identify the information sources of price adjustments to separate price discovery from the market responses to liquidity shocks. We assess market efficiency of price discovery visually, by the time paths of price convergence toward the new fundamental value, and numerically, by the magnitude of pricing errors during the price discovery process. We also use our price discovery model to illustrate the structural determinants of two often used price discovery measures: the information share and component share. We show that two measures are static and unable to reveal the underlying price discovery dynamics between markets. Applying our new measures to quotes from spot foreign exchange rates, we find that substantial price discovery of the yen/euro exchange rate occurs through the US dollar. The dollar’s price discovery contribution is positively related to the relative liquidity of the dollar markets versus the cross rate market, and reaches a minimum during the European business hours.

Bingcheng Yan; Eric Zivot

2004-01-01T23:59:59.000Z

6

Conspicuous Consumption and Dynamic Pricing  

Science Conference Proceedings (OSTI)

How do firms develop marketing strategy when consumers seek to satisfy both quality and status-related considerations? We develop an analytical model to study this issue, examining both pricing and product management decisions in markets for conspicuous ... Keywords: conspicuous consumption, durable goods, dynamic pricing, game theory, status

Raghunath Singh Rao, Richard Schaefer

2013-09-01T23:59:59.000Z

7

The power of dynamic pricing  

SciTech Connect

Using data from a generic California utility, it can be shown that it is feasible to develop dynamic pricing rates for all customer classes. These rates have the potential to reduce system peak demands from 1 to 9 percent. (author)

Faruqui, Ahmad; Hledik, Ryan; Tsoukalis, John

2009-04-15T23:59:59.000Z

8

Dynamic Pricing and Learning in Electricity Markets  

Science Conference Proceedings (OSTI)

We analyze the price-formation process in an infinite-horizon oligopoly model where hydroelectric generators engage in dynamic price-based competition. The analysis focuses on the role of "indifference" prices, i.e., prices that equate the gains from ... Keywords: Dynamic auctions, Economics, Games: stochastic, Natural resources: energy, Noncooperative, Restructured electricity markets, Water resources

Alfredo Garcia; Enrique Campos-Nańez; James Reitzes

2005-03-01T23:59:59.000Z

9

Utility green pricing programs: A statistical analysis of program effectiveness  

E-Print Network (OSTI)

Consumer Demand for ‘Green Power’ and Energy Efficiency. ”of renewable energy supported by green pricing programs (renewable energy purchases through green pricing programs (

Wiser, Ryan; Olson, Scott; Bird, Lori; Swezey, Blair

2004-01-01T23:59:59.000Z

10

Utility Green Pricing Programs: A Statistical Analysis of Program Effectiveness  

DOE Green Energy (OSTI)

This report analyzes actual utility green pricing program data to provide further insight into which program features might help maximize both customer participation in green pricing programs and the amount of renewable energy purchased by customers in those programs.

Wiser, R.; Olson, S.; Bird, L.; Swezey, B.

2004-02-01T23:59:59.000Z

11

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

SciTech Connect

This study examines the use of OpenADR communications specification, related data models, technologies, and strategies to send dynamic prices (e.g., real time prices and peak prices) and Time of Use (TOU) rates to commercial and industrial electricity customers. OpenADR v1.0 is a Web services-based flexible, open information model that has been used in California utilities' commercial automated demand response programs since 2007. We find that data models can be used to send real time prices. These same data models can also be used to support peak pricing and TOU rates. We present a data model that can accommodate all three types of rates. For demonstration purposes, the data models were generated from California Independent System Operator's real-time wholesale market prices, and a California utility's dynamic prices and TOU rates. Customers can respond to dynamic prices by either using the actual prices, or prices can be mapped into"operation modes," which can act as inputs to control systems. We present several different methods for mapping actual prices. Some of these methods were implemented in demonstration projects. The study results demonstrate show that OpenADR allows interoperability with existing/future systems/technologies and can be used within related dynamic pricing activities within Smart Grid.

Ghatikar, Girish; Mathieu, Johanna L.; Piette, Mary Ann; Koch, Ed; Hennage, Dan

2010-08-02T23:59:59.000Z

12

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

left) and High (right) Electricity Price References..32 Listin response to dynamic electricity prices using the Opena variety of dynamic electricity price structures. In this

Ghatikar, Girish

2010-01-01T23:59:59.000Z

13

Adaptive genetic programming for option pricing  

Science Conference Proceedings (OSTI)

Genetic Programming (GP) is an automated computational programming methodology, inspired by the workings of natural evolution techniques. It has been applied to solve complex problems in multiple domains including finance. This paper illustrates the ... Keywords: enetic programming, options pricing

Zheng Yin; Anthony Brabazon; Conall O'Sullivan

2007-07-01T23:59:59.000Z

14

A price discrimination modeling using geometric programming  

Science Conference Proceedings (OSTI)

This paper presents a price discrimination model which determines the product's selling price and marketing expenditure in two markets. We assume production as a function of price and marketing cost in two states. The cost of production is also assumed ... Keywords: economics, mathematical programming, production and operations management

Seyed J. Sadjadi; M. Ziaee

2006-05-01T23:59:59.000Z

15

MATHEMATICS Price dynamics in political prediction markets  

E-Print Network (OSTI)

- gate the price dynamics of prediction markets with the goal of developing methods to identify the trulyAPPLIED MATHEMATICS POLITICAL SCIENCES Price dynamics in political prediction markets Saikat Ray City, IA 52242; and d Department Chemical and Biological Engineering, Northwestern University, Evanston

Amaral, Luis A.N.

16

Utility Green Pricing Programs: A Statistical Analysis of Program...  

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

NRELTP-620-35609 ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY NATIONAL RENEWABLE ENERGY LABORATORY Utility Green Pricing Programs: A Statistical Analysis of Program...

17

Dynamic Pricing, Advanced Metering, and Demand Response in Electricity Markets  

E-Print Network (OSTI)

as Large Comm. Interval metering system with monthly dataDynamic Pricing, Advanced Metering and Demand Response inE Dynamic Pricing, Advanced Metering, and Demand Response in

Borenstein, Severin; Jaske, Michael; Rosenfeld, Arthur

2002-01-01T23:59:59.000Z

18

Utility Green Pricing Programs: What Defines Success?  

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

price premiums for energy-based programs A number of utilities offer programs based on a mix of renewable energy resources. For example, Wisconsin Electric taps a combination of...

19

Price and cost impacts of utility DSM programs  

Science Conference Proceedings (OSTI)

More US utilities are running more and larger demand-side management (DSM) programs. Assessing the cost-effectiveness of these programs raises difficult questions for utilities and their regulators. In particular, should these programs aim to minimize the total cost of providing electric-energy services or should they minimize the price of electricity Most of the debates about the appropriate economic tests to use in assessing utility programs do not address the magnitude of the impacts. As a result, questions remain about the relationships among utility DSM programs and acquisition of supply resources and the effects of these choices on electricity prices and costs. This study offers quantitative estimates on the tradeoffs between total costs and electricity prices. A dynamic model is used to assess the effects of energy-efficiency programs on utility revenues, total resource costs, electricity prices, and electricity consumption for the period 1990 to 2010. These DSM programs are assessed under alternative scenarios for three utilities: a base that is typical of US utilities; a surplus utility that has excess capacity, few planned retirements, and slow growth in fossil-fuel prices and incomes; and a deficit utility that has little excess capacity, many planned retirements, and rapid growth in fossil-fuel prices and incomes. Model results show that DSM programs generally reduce electricity costs and increase electricity prices. However, the percentage reduction in costs is usually greater than the percentage increase in prices. On the other hand, most of the cost benefits of DSM programs can be obtained without raising electricity prices.

Hirst, E. (Oak Ridge National Lab., TN (United States))

1992-01-01T23:59:59.000Z

20

System dynamics, market microstructure and asset pricing  

E-Print Network (OSTI)

Traditional asset pricing approaches are not able to explain extreme volatility and tail events that characterized financial markets in the past decade. System Dynamics theory, which is still underutilized in financial ...

Leika, Mindaugas

2013-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Volatility and commodity price dynamics  

E-Print Network (OSTI)

Commodity prices tend to be volatile, and volatility itself varies over time. changes in volatility can affect market variables by directly affecting the marginal value of storage, and by affecting a component of the total ...

Pindyck, Robert S.

2001-01-01T23:59:59.000Z

22

Three Essays on Retail Price Dynamics  

E-Print Network (OSTI)

of Reference Prices . . . . . . . . . . . . . . . . . . . .2.4.5 Reference Prices andChain-Level Prices . . . . . . . . . . . . . .

Elberg, Andres

2010-01-01T23:59:59.000Z

23

On dynamic prices: a clash of beliefs?  

SciTech Connect

While insightful essays have been written regarding the moral appropriateness of dynamic pricing, they have an implicit underlying framework for determining justness and fairness that may not necessarily accord completely with the view promulgated in regard to utility rate setting generally. (author)

Hanser, Philip Q

2010-07-15T23:59:59.000Z

24

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

Science Conference Proceedings (OSTI)

We present an Open Automated Demand Response Communications Specifications (OpenADR) data model capable of communicating real-time prices to electricity customers. We also show how the same data model could be used to for other types of dynamic pricing tariffs (including peak pricing tariffs, which are common throughout the United States). Customers participating in automated demand response programs with building control systems can respond to dynamic prices by using the actual prices as inputs to their control systems. Alternatively, prices can be mapped into"building operation modes," which can act as inputs to control systems. We present several different strategies customers could use to map prices to operation modes. Our results show that OpenADR can be used to communicate dynamic pricing within the Smart Grid and that OpenADR allows for interoperability with existing and future systems, technologies, and electricity markets.

Ghatikar, Girish; Mathieu, Johanna L.; Piette, Mary Ann; Kiliccote, Sila

2010-06-02T23:59:59.000Z

25

Trends in Utility Green Pricing Programs (2006)  

SciTech Connect

In the early 1990s, only a handful of utilities offered their customers a choice of purchasing electricity generated from renewable energy sources. Today, more than 750 utilities--or about 25% of all utilities nationally--provide their customers a "green power" option. Through these programs, more than 70 million customers have the ability to purchase renewable energy to meet some portion or all of their electricity needs--or make contributions to support the development of renewable energy resources. Typically, customers pay a premium above standard electricity rates for this service. This report presents year-end 2006 data on utility green pricing programs, and examines trends in consumer response and program implementation over time. The data in this report, which were obtained via a questionnaire distributed to utility green pricing program managers, can be used by utilities to benchmark the success of their green power programs.

Bird, L.; Kaiser, M.

2007-10-01T23:59:59.000Z

26

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network (OSTI)

communicate dynamic electricity prices to facilities and howdoes not know the electricity prices more than a day inTime Pricing (RTP): Electricity prices vary continuously

Ghatikar, Girish

2010-01-01T23:59:59.000Z

27

Trends in Utility Green Pricing Programs (2004)  

Science Conference Proceedings (OSTI)

In the early 1990s, only a handful of utilities offered their customers a choice of purchasing electricity generated from renewable energy sources. Today, nearly 600 utilities in regulated electricity markets--or almost 20% of all utilities nationally--provide their customers a "green power" option. Because some utilities offer programs in conjunction with cooperative associations or other publicly owned power entities, the number of distinct programs totals about 125. Through these programs, more than 40 million customers spanning 34 states have the ability to purchase renewable energy to meet some portion or all of their electricity needs--or make contributions to support the development of renewable energy resources. Typically, customers pay a premium above standard electricity rates for this service. This report presents year-end 2004 data on utility green pricing programs, and examines trends in consumer response and program implementation over time. The data in this report, which were obtained via a questionnaire distributed to utility green pricing program managers, can be used by utilities as benchmarks by which to gauge the success of their green power programs.

Bird, L.; Brown, E.

2005-10-01T23:59:59.000Z

28

Trends in Utility Green Pricing Programs (2006)  

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

Trends in Utility Green Trends in Utility Green Pricing Programs (2006) Lori Bird and Marshall Kaiser Technical Report NREL/TP-670-42287 October 2007 NREL is operated by Midwest Research Institute â—Ź Battelle Contract No. DE-AC36-99-GO10337 National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 * www.nrel.gov Operated for the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy by Midwest Research Institute * Battelle Contract No. DE-AC36-99-GO10337 Technical Report NREL/TP-670-42287 October 2007 Trends in Utility Green Pricing Programs (2006) Lori Bird and Marshall Kaiser Prepared under Task No. IGST.7330 NOTICE This report was prepared as an account of work sponsored by an agency of the United States government.

29

Trends in Utility Green Pricing Programs (2004)  

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

Trends in Utility Green Trends in Utility Green Pricing Programs (2004) Lori Bird and Elizabeth Brown Technical Report NREL/TP-620-38800 October 2005 Trends in Utility Green Pricing Programs (2004) Lori Bird and Elizabeth Brown Prepared under Task No. ASG5.1003 Technical Report NREL/TP-620-38800 October 2005 National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 * www.nrel.gov Operated for the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy by Midwest Research Institute * Battelle Contract No. DE-AC36-99-GO10337 NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any

30

Trends in Utility Green Pricing Programs (2003)  

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

33 33 Trends in Utility Green Pricing Programs (2003) Lori Bird and Karen Cardinal National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 * www.nrel.gov Operated for the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy by Midwest Research Institute * Battelle Contract No. DE-AC36-99-GO10337 September 2004 * NREL/TP-620-36833 Trends in Utility Green Pricing Programs (2003) Lori Bird and Karen Cardinal Prepared under Task No. ASG4.1003 National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 * www.nrel.gov Operated for the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy by Midwest Research Institute * Battelle

31

Characterizing the Response of Commercial and Industrial Facilities to Dynamic Pricing Signals from the Utility  

Science Conference Proceedings (OSTI)

We describe a method to generate statistical models of electricity demand from Commercial and Industrial (C&I) facilities including their response to dynamic pricing signals. Models are built with historical electricity demand data. A facility model is the sum of a baseline demand model and a residual demand model; the latter quantifies deviations from the baseline model due to dynamic pricing signals from the utility. Three regression-based baseline computation methods were developed and analyzed. All methods performed similarly. To understand the diversity of facility responses to dynamic pricing signals, we have characterized the response of 44 C&I facilities participating in a Demand Response (DR) program using dynamic pricing in California (Pacific Gas and Electric's Critical Peak Pricing Program). In most cases, facilities shed load during DR events but there is significant heterogeneity in facility responses. Modeling facility response to dynamic price signals is beneficial to the Independent System Operator for scheduling supply to meet demand, to the utility for improving dynamic pricing programs, and to the customer for minimizing energy costs.

Mathieu, Johanna L.; Gadgil, Ashok J.; Callaway, Duncan S.; Price, Phillip N.; Kiliccote, Sila

2010-07-01T23:59:59.000Z

32

Household Response To Dynamic Pricing Of Electricity: A Survey...  

Open Energy Info (EERE)

property. This report surveys evidence from 15 recent experiments with dynamic pricing of electricity in the United States and Canada. The report suggests conclusive evidence that...

33

Variability in Automated Responses of Commercial Buildings and Industrial Facilities to Dynamic Electricity Prices  

E-Print Network (OSTI)

and Industrial Facilities to Dynamic Electricity Pricesand Industrial Facilities to Dynamic Electricity Prices

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

34

Cartel Pricing Dynamics with Cost Variability and Endogenous Buyer Detection  

E-Print Network (OSTI)

of the cartel price to cost is most easily seen for large trends in cost. In Figure 1-b, cost rises over periodsCartel Pricing Dynamics with Cost Variability and Endogenous Buyer Detection Joseph E. Harrington characterizes collusive pricing patterns when buyers may detect the presence of a cartel. Buyers are assumed

Niebur, Ernst

35

Modeling and simulation of consumer response to dynamic pricing.  

Science Conference Proceedings (OSTI)

Assessing the impacts of dynamic-pricing under the smart grid concept is becoming extremely important for deciding its full deployment. In this paper, we develop a model that represents the response of consumers to dynamic pricing. In the model, consumers use forecasted day-ahead prices to shift daily energy consumption from hours when the price is expected to be high to hours when the price is expected to be low while maintaining the total energy consumption as unchanged. We integrate the consumer response model into the Electricity Market Complex Adaptive System (EMCAS). EMCAS is an agent-based model that simulates restructured electricity markets. We explore the impacts of dynamic-pricing on price spikes, peak demand, consumer energy bills, power supplier profits, and congestion costs. A simulation of an 11-node test network that includes eight generation companies and five aggregated consumers is performed for a period of 1 month. In addition, we simulate the Korean power system.

Valenzuela, J.; Thimmapuram, P.; Kim, J (Decision and Information Sciences); (Auburn Univ.)

2012-08-01T23:59:59.000Z

36

Utility Green Pricing Programs: Design, Implementation, and Consumer...  

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

Green Pricing Programs: Design, Implementation, and Consumer Response February 2004 * NRELTP-620-35618 Lori Bird, Blair Swezey, and Jrn Aabakken National Renewable Energy...

37

A semidefinite programming based polyhedral cut and price ...  

E-Print Network (OSTI)

May 17, 2004 ... A semidefinite programming based polyhedral cut and price algorithm for the maxcut problem. Kartik Krishnan (kartik ***at*** rice.edu)

38

HOUSEHOLD RESPONSE TO DYNAMIC PRICING OF ELECTRICITY A SURVEY OF SEVENTEEN PRICING EXPERIMENTS  

E-Print Network (OSTI)

(DOE) defines demand response as "changes in electric usage by end-use customers from their normalHOUSEHOLD RESPONSE TO DYNAMIC PRICING OF ELECTRICITY A SURVEY OF SEVENTEEN PRICING EXPERIMENTS response in electricity markets. One of the best ways to let that happen is to let customers see

39

Dynamic pricing? Not so fast. a residential consumer perspective  

Science Conference Proceedings (OSTI)

With the installation of smart metering, will residential customers be moved to ''dynamic'' pricing? Some supporters of changing residential rate design from a fixed and stable rate structure believe customers should be required to take electric service with time-variant price signals. Not so fast, though. There are real implications associated with this strategy. (author)

Alexander, Barbara R.

2010-07-15T23:59:59.000Z

40

The effects of utility DSM programs on electricity costs and prices  

SciTech Connect

More and more US utilities are running more and larger demand-side management (DSM) programs. Assessing the cost-effectiveness of these programs raises difficult questions for utilities and their regulators. Should these programs aim to minimize the total cost of providing electric-energy services or should they minimize the price of electricity? This study offers quantitative estimates on the tradeoffs between total costs and electricity prices. This study uses a dynamic model to assess the effects of energy-efficiency programs on utility revenues, total resource costs, electricity prices, and electricity consumption for the period 1990 to 2010. These DSM programs are assessed under alternative scenarios. In these cases, fossil-fuel prices, load growth, the amount of excess capacity the utility has in 1990, planned retirements of power plants, the financial treatment of DSM programs, and the costs of energy- efficient programs vary. These analyses are conducted for three utilities: a ``base`` that is typical of US utilities; a ``surplus`` utility that has excess capacity, few planned retirements, and slow growth in fossil-fuel prices and incomes; and a ``deficit`` utility that has little excess capacity, many planned retirements, and rapid growth in fossil-fuel prices and incomes. 28 refs.

Hirst, E.

1991-11-01T23:59:59.000Z

Note: This page contains sample records for the topic "dynamic pricing programs" 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

The effects of utility DSM programs on electricity costs and prices  

SciTech Connect

More and more US utilities are running more and larger demand-side management (DSM) programs. Assessing the cost-effectiveness of these programs raises difficult questions for utilities and their regulators. Should these programs aim to minimize the total cost of providing electric-energy services or should they minimize the price of electricity This study offers quantitative estimates on the tradeoffs between total costs and electricity prices. This study uses a dynamic model to assess the effects of energy-efficiency programs on utility revenues, total resource costs, electricity prices, and electricity consumption for the period 1990 to 2010. These DSM programs are assessed under alternative scenarios. In these cases, fossil-fuel prices, load growth, the amount of excess capacity the utility has in 1990, planned retirements of power plants, the financial treatment of DSM programs, and the costs of energy- efficient programs vary. These analyses are conducted for three utilities: a base'' that is typical of US utilities; a surplus'' utility that has excess capacity, few planned retirements, and slow growth in fossil-fuel prices and incomes; and a deficit'' utility that has little excess capacity, many planned retirements, and rapid growth in fossil-fuel prices and incomes. 28 refs.

Hirst, E.

1991-11-01T23:59:59.000Z

42

Assessing Natural Gas Energy Efficiency Programs in a Low-Price...  

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

Natural Gas Energy Efficiency Programs in a Low-Price Environment Title Assessing Natural Gas Energy Efficiency Programs in a Low-Price Environment Publication Type Policy Brief...

43

Utility Green Pricing Programs: Design, Implementation, and Consumer Response  

DOE Green Energy (OSTI)

The term green pricing refers to programs offered by utilities in traditionally regulated electricity markets, which allow customers to support the development of renewable energy sources by paying a small premium on their electric bills. Since the introduction of the concept in the United States, the number of unique utility green pricing programs has expanded from just a few programs in 1993 to more than 90 in 2002. About 10% of U.S. utilities offered a green pricing option to about 26 million consumers by the end of 2002. This report provides: (1) aggregate industry data on consumer response to utility programs, which indicate the collective impact of green pricing on renewable energy development nationally; and (2) market data that can be used by utilities as a benchmark for gauging the relative success of their green pricing programs. Specifically, the paper presents current data and trends in consumer response to green pricing, as measured by renewable energy sales, participants, participation rates, and new renewable energy capacity supported. It presents data on various aspects of program design and implementation, such as product pricing, ownership of supplies, retention rates, marketing costs, the effectiveness of marketing techniques, and methods of enrolling and providing value to customers.

Bird, L.; Swezey, B.; Aabakken, J.

2004-02-01T23:59:59.000Z

44

Dynamic interactions between electricity prices and the regional economy  

E-Print Network (OSTI)

In this thesis we study characterize the dynamic relationships among two electricity price variables (residential and commercial) and six regional economic variables in order to examine each individual variable??s role in regional economic activity. We also answer the question ??Do electricity prices have impact on regional economic variables??? We use two statistical techniques as engines of analysis. First, we use directed acyclic graphs to discover how surprises (innovations) in prices from each variable are communicated to other variables in contemporaneous time. Second, we use time series methods to capture regularities in time lags among the series. Yearly time series data on two electricity prices and six regional economic variables for Montgomery County (Texas) are studied using time series methods. Directed Acyclic Graphs (DAGs) are used to impose restrictions on the Vector Auto Regression model (VAR). Using Innovation Accounting Analysis of the estimated Vector Auto Regression (VAR) model we unravel the dynamic relationships between the eight variables. We conclude that rising electricity prices have a negative impact on allregional economic variables. The commercial average electricity prices lead residential average electricity prices in the time frame we studied (1969-2000). Rising residential electricity prices also have a positive impact on income derived from transfer payments.

Bethapudi, Daniel Naveen

2003-05-01T23:59:59.000Z

45

Real-time pricing program in a smart grid environment  

Science Conference Proceedings (OSTI)

Improving system efficiency and reliability is motivating countries to design and execute different types of time of use demand response programs. However, certain deficiencies prevent these programs from reaching their goals. Smart meters as a mechanism ... Keywords: real-time pricing, smart grid, time of use programs

Hassan Monsef, Bin Wu

2013-04-01T23:59:59.000Z

46

Oil price; oil demand shocks; oil supply shocks; dynamic effects.  

E-Print Network (OSTI)

Abstract: Using a newly developed measure of global real economic activity, a structural decomposition of the real price of crude oil in four components is proposed: oil supply shocks driven by political events in OPEC countries; other oil supply shocks; aggregate shocks to the demand for industrial commodities; and demand shocks that are specific to the crude oil market. The latter shock is designed to capture shifts in the price of oil driven by higher precautionary demand associated with fears about future oil supplies. The paper quantifies the magnitude and timing of these shocks, their dynamic effects on the real price of oil and their relative importance in determining the real price of oil during 1975-2005. The analysis sheds light on the origin of the observed fluctuations in oil prices, in particular during oil price shocks. For example, it helps gauge the relative importance of these shocks in the build-up of the real price of crude oil since the late 1990s. Distinguishing between the sources of higher oil prices is shown to be crucial in assessing the effect of higher oil prices on U.S. real GDP and CPI inflation, suggesting that policies aimed at dealing with higher oil prices must take careful account of the origins of higher oil prices. The paper also quantifies the extent to which the macroeconomic performance of the U.S. since the mid-1970s has been driven by the external economic shocks driving the real price of oil as opposed to domestic economic factors and policies. Key words: JEL:

Lutz Kilian

2006-01-01T23:59:59.000Z

47

Information Relaxations and Duality in Stochastic Dynamic Programs  

Science Conference Proceedings (OSTI)

We describe a general technique for determining upper bounds on maximal values (or lower bounds on minimal costs) in stochastic dynamic programs. In this approach, we relax the nonanticipativity constraints that require decisions to depend only on the ... Keywords: duality, dynamic programming, inventory control, option pricing

David B. Brown; James E. Smith; Peng Sun

2010-07-01T23:59:59.000Z

48

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

In peak pricing tariffs, electricity prices on peak days areIn peak pricing tariffs, electricity prices on peak days areof California electricity pricing tariffs (including RTP,

Ghatikar, Girish

2010-01-01T23:59:59.000Z

49

An Approximate Dynamic Programming Approach to Benchmark Practice-Based Heuristics for Natural Gas Storage Valuation  

Science Conference Proceedings (OSTI)

The valuation of the real option to store natural gas is a practically important problem that entails dynamic optimization of inventory trading decisions with capacity constraints in the face of uncertain natural gas price dynamics. Stochastic dynamic ... Keywords: Markov, asset pricing, dynamic programming, finance, heuristics, industries, petroleum/natural gas, real options, storage valuation, upper bounds

Guoming Lai; François Margot; Nicola Secomandi

2010-05-01T23:59:59.000Z

50

Household Response To Dynamic Pricing Of Electricity: A Survey Of The  

Open Energy Info (EERE)

Household Response To Dynamic Pricing Of Electricity: A Survey Of The Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Focus Area: Crosscutting Topics: Market Analysis Website: www.hks.harvard.edu/hepg/Papers/2009/The%20Power%20of%20Experimentatio Equivalent URI: cleanenergysolutions.org/content/household-response-dynamic-pricing-el Language: English Policies: "Deployment Programs,Regulations,Financial Incentives" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Demonstration & Implementation Regulations: "Mandates/Targets,Cost Recovery/Allocation,Enabling Legislation" is not in the list of possible values (Agriculture Efficiency Requirements, Appliance & Equipment Standards and Required Labeling, Audit Requirements, Building Certification, Building Codes, Cost Recovery/Allocation, Emissions Mitigation Scheme, Emissions Standards, Enabling Legislation, Energy Standards, Feebates, Feed-in Tariffs, Fuel Efficiency Standards, Incandescent Phase-Out, Mandates/Targets, Net Metering & Interconnection, Resource Integration Planning, Safety Standards, Upgrade Requirements, Utility/Electricity Service Costs) for this property.

51

Green Pricing Program Marketing Expenditures: Finding the Right Balance  

SciTech Connect

In practice, it is difficult to determine the optimal amount to spend on marketing and administering a green pricing program. Budgets for marketing and administration of green pricing programs are a function of several factors: the region of the country; the size of the utility service area; the customer base and media markets encompassed within that service area; the point or stage in the lifespan of the program; and certainly, not least, the utility's commitment to and goals for the program. All of these factors vary significantly among programs. This report presents data on programs that have funded both marketing and program administration. The National Renewable Energy Laboratory (NREL) gathers the data annually from utility green pricing program managers. Programs reporting data to NREL spent a median of 18.8% of program revenues on marketing their programs in 2008 and 16.6% in 2007. The smallest utilities (those with less than 25,000 in their eligible customer base) spent 49% of revenues on marketing, significantly more than the overall median. This report addresses the role of renewable energy credit (REC) marketers and start-up costs--and the role of marketing, generally, in achieving program objectives, including expansion of renewable energy.

Friedman, B.; Miller, M.

2009-09-01T23:59:59.000Z

52

Utility green pricing programs: A statistical analysis of program effectiveness  

E-Print Network (OSTI)

Size Participation Rate (%) Utility Size (# customers) Non-Size Participation Rate (%) Utility Size (# customers)non-residential participation rates in utility green pricing

Wiser, Ryan; Olson, Scott; Bird, Lori; Swezey, Blair

2004-01-01T23:59:59.000Z

53

Branch-and-Price Guided Search for Integer Programs with an ...  

E-Print Network (OSTI)

solved with a branch-and-price algorithm, which, when run to completion, ... small restricted integer programs, and a branch-and-price approach for solving it.

54

Price impacts of electric-utility DSM programs  

Science Conference Proceedings (OSTI)

As competition in the electricity industry increases, utilities (and others) worry more about the upward pressure on electricity prices that demand-side management (DSM) programs often impose. Because of these concerns, several utilities have recently reduced the scope of their DSM programs or focused these programs more on customer service and peak-demand reductions and less on improving energy efficiency. This study uses the Oak Ridge Financial Model (ORFIN) to calculate the rate impacts of DSM. The authors use ORFIN to examine the two factors that contribute to DSM`s upward pressure on prices: the cost of the programs themselves and the loss of revenue associated with fixed-cost recovery. This second factor reflects the reduction in revenues caused by the DSM-induced energy and demand savings that exceed the reduction in utility costs. This analysis examines DSM price impacts as functions of the following factors: the DSM program itself (cost, conservation load factor, geographic focus on deferral of transmission and distribution investments, and mix across customer classes); the utility`s cost and pricing structures (factors at least partly under the utility`s control, such as retail tariffs, fixed vs variable operating costs, and capital costs not related to kW or kWh growth); and external economic and regulatory factors (the level and temporal pattern of avoided energy and capacity costs; ratebasing vs expensing of DSM-program costs; shareholder incentives for DSM programs; load growth; and the rates for income, property, and revenue taxes).

Hirst, E.; Hadley, S.

1994-11-01T23:59:59.000Z

55

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

link wholesale and retail real-time prices. 6.0 Referencesdynamic prices such as real-time prices and peak prices andFigure 5. Average Daily Real-Time Prices and Price Duration

Ghatikar, Girish

2010-01-01T23:59:59.000Z

56

Utility green pricing programs: A statistical analysis of program effectiveness  

E-Print Network (OSTI)

Bird, L. , Swezey, B. 2003. Green Power Marketing in theR. , Aabakken, J. 2002. Green Power Marketing Abroad: RecentHolt, E. , Holt, M. 2004. Green Pricing Resource Guide.

Wiser, Ryan; Olson, Scott; Bird, Lori; Swezey, Blair

2004-01-01T23:59:59.000Z

57

Integrating Renewable Energy Contracts and Wholesale Dynamic Pricing to Serve Aggregate  

E-Print Network (OSTI)

1 Integrating Renewable Energy Contracts and Wholesale Dynamic Pricing to Serve Aggregate Flexible batteries, with renewable energy resources. We formulate a stochastic optimal control problem that describes and the degree to which the aggregator can respond to dynamic pricing. Index Terms--Dynamic pricing, renewable

Oren, Shmuel S.

58

Practice Prize Report---An Assortmentwide Decision-Support System for Dynamic Pricing and Promotion Planning in DIY Retailing  

Science Conference Proceedings (OSTI)

The main objective of this report is to describe a decision-support system for dynamic retail pricing and promotion planning. Our weekly demand model incorporates price, reference price effects, seasonality, article availability information, features, ... Keywords: demand interdependency, dynamic pricing, pricing research, reference price, retail strategy, revenue management

Martin Natter; Thomas Reutterer; Andreas Mild; Alfred Taudes

2007-07-01T23:59:59.000Z

59

Oil Price Shocks, Inventories, and Macroeconomic Dynamics,” mimeo  

E-Print Network (OSTI)

This paper employs disaggregated manufacturing data to investigate the causes of the time delay between an increase in oil prices and the following slowdown in economic activity. VAR results show that, unlike aggregate GDP, the effect of an oil price shock on new motor vehicles production shows up immediately and is statistically significantly. After one quarter, similar patterns are observed for industries that are oil-intensive or for which motor vehicles constitute a demand-shifter. The continuing fall in manufacturing production then leads the economy into a recession. The paper then estimates a modified linear-quadratic inventory model and shows that this description of the oil price dynamics is consistent with rational behavior by firms. An increase in oil prices leads to a decline in manufacturing sales; partly because the shock catches manufacturers by surprise and partly because of their desire to balance the accelerator and production smoothing motives, manufacturers deviate from the target level of inventories and spread the decline in production over various quarters. Moreover, the dynamics entailed by the structural estimates capture two stylized facts about inventory behavior: procyclicality and persistence.

Ana María Herrera

2008-01-01T23:59:59.000Z

60

2009 Rate Design Window Dynamic Pricing  

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

Compressed Air Energy Compressed Air Energy Storage (CAES) Hal LaFlash Director Emerging Clean Technologies Pacific Gas and Electric Company November 3, 2010 Funded in part by the Energy Storage Systems Program of the U.S. Department Of Energy through National Energy Technology Laboratory 1 Project Need * California regulations will require that utilities procure 33% of their energy from eligible renewables * Scenario projections show that nearly 70% of the renewable energy (23% of total energy) is likely to be provided by variable solar and wind resources. * The CA ISO expects it will need high amounts of flexible resources, especially energy storage, to integrate renewable energy into the grid. * Compressed Air Energy Storage has a long history of being one of the most economic forms of energy storage.

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Renewable Energy Price-Stability Benefits in Utility Green Power Programs  

SciTech Connect

This paper examines utility experiences when offering the fixed-price benefits of renewable energy in green pricing programs, including the methods utilized and the impact on program participation. It focuses primarily on utility green pricing programs in states that have not undergone electric industry restructuring.

Bird, L. A.; Cory, K. S.; Swezey, B. G.

2008-08-01T23:59:59.000Z

62

UDP: Usage-based Dynamic Pricing with Privacy Preservation for Smart Grid  

E-Print Network (OSTI)

UDP: Usage-based Dynamic Pricing with Privacy Preservation for Smart Grid Xiaohui Liang, Student for smart grid in a community environment, which enables the electricity price to correspond-preserving manner. Index Terms--Smart grid; dynamic price; privacy preserva- tion; community-specific I

Shen, Xuemin "Sherman"

63

Green Pricing Program Marketing Expenditures: Finding the Right Balance  

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

449 449 September 2009 Green Pricing Program Marketing Expenditures: Finding the Right Balance Barry Friedman and Mackay Miller 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-6A2-46449 September 2009 Green Pricing Program Marketing Expenditures: Finding the Right Balance Barry Friedman and Mackay Miller Prepared under Task No. SAO9.3003 NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any

64

Automated Critical Peak Pricing Field Tests: Program Description and Results  

E-Print Network (OSTI)

Moderate Price (real-time) High Price (real-time) Note:Into EMCS Moderate Price (real-time) Indicator Light Same asIndication (optional) High Price (real-time) Indicator Light

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Xu, Peng

2006-01-01T23:59:59.000Z

65

Price-Anderson Nuclear Safety Enforcement Program. 1997 annual report  

SciTech Connect

This report summarizes activities in the Department of Energy's Price-Anderson Amendments Act (PAAA) Enforcement Program in calendar year 1997 and highlights improvements planned for 1998. The DOE Enforcement Program involves the Office of Enforcement and Investigation in the DOE Headquarters Office of Environment, Safety and Health, as well as numerous PAAA Coordinators and technical advisors in DOE Field and Program Offices. The DOE Enforcement Program issued 13 Notices of Violation (NOV`s) in 1997 for cases involving significant or potentially significant nuclear safety violations. Six of these included civil penalties totaling $440,000. Highlights of these actions include: (1) Brookhaven National Laboratory Radiological Control Violations / Associated Universities, Inc.; (2) Bioassay Program Violations at Mound / EG and G, Inc.; (3) Savannah River Crane Operator Uptake / Westinghouse Savannah River Company; (4) Waste Calciner Worker Uptake / Lockheed-Martin Idaho Technologies Company; and (5) Reactor Scram and Records Destruction at Sandia / Sandia Corporation (Lockheed-Martin).

NONE

1998-01-01T23:59:59.000Z

66

Livestock Risk Protection-Lamb: New Insurance Program to Help Ranchers Manage Lamb Price Risk  

E-Print Network (OSTI)

USDA is offering a new insurance program to help livestock producers manage lamb price risk. This publication explains requirements of the program and the way it works.

Pena, Jose G.; Thompson, Bill; Bevers, Stan; Anderson, David P.

2008-10-07T23:59:59.000Z

67

Customer response to day-ahead wholesale market electricity prices: Case study of RTP program experience in New York  

Science Conference Proceedings (OSTI)

There is growing interest in policies, programs and tariffs that encourage customer loads to provide demand response (DR) to help discipline wholesale electricity markets. Proposals at the retail level range from eliminating fixed rate tariffs as the default service for some or all customer groups to reinstituting utility-sponsored load management programs with market-based inducements to curtail. Alternative rate designs include time-of-use (TOU), day-ahead real-time pricing (RTP), critical peak pricing, and even pricing usage at real-time market balancing prices. Some Independent System Operators (ISOs) have implemented their own DR programs whereby load curtailment capabilities are treated as a system resource and are paid an equivalent value. The resulting load reductions from these tariffs and programs provide a variety of benefits, including limiting the ability of suppliers to increase spot and long-term market-clearing prices above competitive levels (Neenan et al., 2002; Boren stein, 2002; Ruff, 2002). Unfortunately, there is little information in the public domain to characterize and quantify how customers actually respond to these alternative dynamic pricing schemes. A few empirical studies of large customer RTP response have shown modest results for most customers, with a few very price-responsive customers providing most of the aggregate response (Herriges et al., 1993; Schwarz et al., 2002). However, these studies examined response to voluntary, two-part RTP programs implemented by utilities in states without retail competition.1 Furthermore, the researchers had limited information on customer characteristics so they were unable to identify the drivers to price response. In the absence of a compelling characterization of why customers join RTP programs and how they respond to prices, many initiatives to modernize retail electricity rates seem to be stymied.

Goldman, C.; Hopper, N.; Sezgen, O.; Moezzi, M.; Bharvirkar, R.; Neenan, B.; Boisvert, R.; Cappers, P.; Pratt, D.

2004-07-01T23:59:59.000Z

68

Utility green pricing programs: A statistical analysis of program effectiveness  

E-Print Network (OSTI)

Total renewable energy purchases of residential program participants in megawatt-hours divided by total eligible residential electrical usage.Total renewable energy purchases of non-residential program participants in megawatt-hours divided by total eligible non- residential electrical usage.

Wiser, Ryan; Olson, Scott; Bird, Lori; Swezey, Blair

2004-01-01T23:59:59.000Z

69

Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions  

Science Conference Proceedings (OSTI)

The benefits of dynamic pricing methods have long been known in industries, such as airlines, hotels, and electric utilities, where the capacity is fixed in the short-term and perishable. In recent years, there has been an increasing adoption of dynamic ... Keywords: Dynamic pricing; e-commerce; revenue management; inventory

Wedad Elmaghraby; Pinar Keskinocak

2003-10-01T23:59:59.000Z

70

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

charges. • Wholesale energy market prices are volatile, andCAISO’s Wholesale Energy Market Prices PG&E’s PDP RetailWe used the CAISO wholesale energy market prices for the RTP

Ghatikar, Girish

2010-01-01T23:59:59.000Z

71

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network (OSTI)

for Automated Demand Response in Commercial Buildings. ” In2010. “Open Automated Demand Response Dynamic Pricing2009. “Open Automated Demand Response Communications

Ghatikar, Girish

2010-01-01T23:59:59.000Z

72

Essays on price dynamics, discovery, and dynamic threshold effects among energy spot markets in North America  

E-Print Network (OSTI)

Given the role electricity and natural gas sectors play in the North American economy, an understanding of how markets for these commodities interact is important. This dissertation independently characterizes the price dynamics of major electricity and natural gas spot markets in North America by combining directed acyclic graphs with time series analyses. Furthermore, the dissertation explores a generalization of price difference bands associated with the law of one price. Interdependencies among 11 major electricity spot markets are examined in Chapter II using a vector autoregression model. Results suggest that the relationships between the markets vary by time. Western markets are separated from the eastern markets and the Electricity Reliability Council of Texas. At longer time horizons these separations disappear. Palo Verde is the important spot market in the west for price discovery. Southwest Power Pool is the dominant market in Eastern Interconnected System for price discovery. Interdependencies among eight major natural gas spot markets are investigated using a vector error correction model and the Greedy Equivalence Search Algorithm in Chapter III. Findings suggest that the eight price series are tied together through sixlong-run cointegration relationships, supporting the argument that the natural gas market has developed into a single integrated market in North America since deregulation. Results indicate that price discovery tends to occur in the excess consuming regions and move to the excess producing regions. Across North America, the U.S. Midwest region, represented by the Chicago spot market, is the most important for price discovery. The Ellisburg-Leidy Hub in Pennsylvania and Malin Hub in Oregon are important for eastern and western markets. In Chapter IV, a threshold vector error correction model is applied to the natural gas markets to examine nonlinearities in adjustments to the law of one price. Results show that there are nonlinear adjustments to the law of one price in seven pair-wise markets. Four alternative cases for the law of one price are presented as a theoretical background. A methodology is developed for finding a threshold cointegration model that accounts for seasonality in the threshold levels. Results indicate that dynamic threshold effects vary depending on geographical location and whether the markets are excess producing or excess consuming markets.

Park, Haesun

2005-08-01T23:59:59.000Z

73

Introduction to Macroeconomic Dynamics Special Issue on Oil Price Shocks  

E-Print Network (OSTI)

, as director of the National Economic Council, stated that "if energy prices will trend higher, you invest one, in which global real economic activity and real oil prices share a common stochastic trend, they ...nd way; if energy prices will be lower, you invest a di¤erent way. But if you don't know what prices

Garousi, Vahid

74

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

peak prices) to reduce electricity bill volatility. Smallwith higher or lower electricity bills than desired, since

Ghatikar, Girish

2010-01-01T23:59:59.000Z

75

Prices  

Gasoline and Diesel Fuel Update (EIA)

Information AdministrationPetroleum Marketing Annual 1998 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) -...

76

Prices  

Gasoline and Diesel Fuel Update (EIA)

Information AdministrationPetroleum Marketing Annual 2001 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) -...

77

Prices  

Annual Energy Outlook 2012 (EIA)

Information AdministrationPetroleum Marketing Annual 1999 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) -...

78

Price-Responsive Load (PRL) Program - Framing Paper No.1  

SciTech Connect

By definition, effective and efficient competitive markets need a supply side and a demand side. One criticism of electric restructuring efforts in many states is that most of the attention has been focused on the supply side, in a market focused on the short term. In general, the demand side of the market has been under-addressed. The objective of the New England Demand Response Initiative (NEDRI) is to develop a comprehensive, coordinated set of demand response programs for the New England regional power markets. NEDRI aims to maximize the capability of demand response to compete in the wholesale market and to improve the economic efficiency and environmental profile of the electric sector. To those ends, NEDRI is focusing its efforts in four interrelated areas: (1) ISO-level reliability programs, (2) Market-based price-responsive load programs, (3) Demand response at retail through pricing, rate design, and advanced metering, and (4) End-use energy efficiency resources as demand response. The fourth area, energy efficiency, is the subject of this framing paper. Energy efficiency reduces the energy used by specific end-use devices and systems, typically without affecting the level of service and without loss of amenity. Energy savings and peak load reductions are achieved by substituting technically more advanced equipment, processes, or operational strategies to produce the same or an improved level of end-use service with less electricity. In contrast, load management programs lower peak demand during specific, limited time periods by either (1) influencing the timing of energy use by shifting load to another time period, or (2) reducing the level of energy use by curtailing or interrupting the load, typically with some loss of service or amenity.

Goldman, Charles A.

2002-03-01T23:59:59.000Z

79

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

aim to minimize energy costs over time. Note that becausedue to increased energy costs over time. Customers couldtime prices and price duration curves for a facility in Year 1 (low energy cost

Ghatikar, Girish

2010-01-01T23:59:59.000Z

80

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

oasis. Last accessed: Con Edison. 2010. “Demand Response/is Southern California Edison’s real-time pricing tariff. 2.and Southern California Edison’s Critical Peak Pricing

Ghatikar, Girish

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Dynamic pricing for residential electric customers: a ratepayer advocate's perspective  

SciTech Connect

New Jersey's Rate Counsel urges that the consideration of alternative pricing mechanisms aimed at encouraging a reduction or shift in residential electricity usage include recognition of the needs and wishes of consumers. Without consumer buy-in, any such pricing mechanisms will fail. To achieve the desired goals, customers must be able to understand and react to the pricing signals. (author)

Brand, Stefanie A.

2010-07-15T23:59:59.000Z

82

Dynamical genetic programming in xcsf  

Science Conference Proceedings (OSTI)

A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to artificial neural networks. This paper presents results from an investigation into using a temporally dynamic symbolic ... Keywords: Graph-based genetic programming, XCSF, learning classifier systems, multistep-ahead prediction, reinforcement learning, self-adaptation, symbolic regression

Richard J. Preen, Larry Bull

2013-09-01T23:59:59.000Z

83

Pricing to Accelerate Demand Learning in Dynamic Assortment ...  

E-Print Network (OSTI)

tomization and shorter product life cycles, make predicting demand more difficult, .... Note that there is full information about price-response function and, as a ...

84

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

prices and time-of-use rates to commercial and industrial electricityprices to commercial and industrial facilities. 2. Evaluate if existing static electricity

Ghatikar, Girish

2010-01-01T23:59:59.000Z

85

Monetary Policy Shocks, Inventory Dynamics, and Price-Setting Behavior  

E-Print Network (OSTI)

Sticky Prices and Inventories: Produc- tion Smoothingbetween monetary shocks and ?nished goods inventories. Fur-nd that allowing for inventory holdings leads to a Phillips

Jung, YongSeung; Yun, Tack

2005-01-01T23:59:59.000Z

86

CSEM WP 105 Dynamic Pricing, Advanced Metering and  

E-Print Network (OSTI)

. As the feed-in tariff is higher than the average electricity price on the wholesale market, the system of the overall cost of green electricity production sought by the government. Guaranteed feed-in tariffs offer environment (feed-in tariffs as price based system on one hand, quotas + green certificates, competitive

California at Berkeley. University of

87

Composition of Electricity Generation Portfolios, Pivotal Dynamics, and Market Prices  

Science Conference Proceedings (OSTI)

We use simulations to study how the diversification of electricity generation portfolios influences wholesale prices. We find that the relationship between technological diversification and market prices is mediated by the supply-to-demand ratio. In ... Keywords: electricity, market power, simulations, technology diversification

Albert Banal-Estaňol; Augusto Rupérez Micola

2009-11-01T23:59:59.000Z

88

Price Responsive Demand in New York Wholesale Electricity Market using OpenADR  

E-Print Network (OSTI)

Dynamic Pricing and Smart Grid. Lawrence Berkeley Nationaland Technology's (NIST) Smart Grid Standards developmentcertification program. The Smart Grid Architectural Council

Kim, Joyce Jihyun

2013-01-01T23:59:59.000Z

89

Information Relaxations, Duality, and Convex Dynamic Programs  

E-Print Network (OSTI)

Oct 15, 2013 ... Abstract: We consider the information relaxation approach for calculating performance bounds for stochastic dynamic programs (DPs), ...

90

Risk-Averse Stochastic Dual Dynamic Programming  

E-Print Network (OSTI)

Feb 27, 2013 ... dynamic programming for hydroelectricity generation, Technical report, Electric Power Opti- mization Centre, University of Auckland, ...

91

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 25, NO. 3, APRIL 2007 613 Price Dynamics in Competitive Agile  

E-Print Network (OSTI)

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 25, NO. 3, APRIL 2007 613 Price Dynamics, Carlos Cordeiro, Member, IEEE Abstract-- We explore the price dynamics in a competitive market consisting and locations. Two different buyer populations, the quality-sensitive and the price-sensitive are investigated

Chandramouli, Rajarathnam "Mouli"

92

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

With such a large number of customers who are now on thebe to have customer-specified daily number of hours for eachnumber or percentage) based on historical prices and customer

Ghatikar, Girish

2010-01-01T23:59:59.000Z

93

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

Center for the Study of Energy Markets Paper CSEMWP-105.OASIS SDO. 2010b. “Energy Market Information Exchange (eMIX)charges. • Wholesale energy market prices are volatile, and

Ghatikar, Girish

2010-01-01T23:59:59.000Z

94

Beyond the Price Effect in Time-of-Use Programs: Results from...  

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

Beyond the Price Effect in Time-of-Use Programs: Results from a Municipal Utility Pilot, 2007-2008 NOTICE Due to the current lapse of federal funding, Berkeley Lab websites are...

95

The Impact of Technical Analysis on Asset Price Dynamics  

E-Print Network (OSTI)

vectors: 0=gl , where ( ) )1(11 1,,...,, +´-= MMM llll , and 1)1( 1 1 ´+* - ÷ ÷ ÷ ř ö çç ç č ć ¶ ¶-= MQ t t Q qg . Using the normalised price given by (20), the 1´M sub-vector in g becomes *1*1*1*1 )0()()( Qt q t Qt q tq t Qt q t Qt...

Yang, J-H Steffi; Satchell, Stephen E

2004-06-16T23:59:59.000Z

96

Variability in Automated Responses of Commercial Buildings and Industrial Facilities to Dynamic Electricity Prices  

Science Conference Proceedings (OSTI)

Changes in the electricity consumption of commercial buildings and industrial facilities (C&I facilities) during Demand Response (DR) events are usually estimated using counterfactual baseline models. Model error makes it difficult to precisely quantify these changes in consumption and understand if C&I facilities exhibit event-to-event variability in their response to DR signals. This paper seeks to understand baseline model error and DR variability in C&I facilities facing dynamic electricity prices. Using a regression-based baseline model, we present a method to compute the error associated with estimates of several DR parameters. We also develop a metric to determine how much observed DR variability results from baseline model error rather than real variability in response. We analyze 38 C&I facilities participating in an automated DR program and find that DR parameter errors are large. Though some facilities exhibit real DR variability, most observed variability results from baseline model error. Therefore, facilities with variable DR parameters may actually respond consistently from event to event. Consequently, in DR programs in which repeatability is valued, individual buildings may be performing better than previously thought. In some cases, however, aggregations of C&I facilities exhibit real DR variability, which could create challenges for power system operation.

Mathieu, Johanna L.; Callaway, Duncan S.; Kiliccote, Sila

2011-08-16T23:59:59.000Z

97

1 HOUSEHOLD RESPONSE TO DYNAMIC PRICING OF ELECTRICITY—A SURVEY OF THE EXPERIMENTAL EVIDENCE  

E-Print Network (OSTI)

Since the energy crisis of 2000-2001 in the western United States, much attention has been given to boosting demand response in electricity markets. One of the best ways to let that happen is to pass through wholesale energy costs to retail customers. This can be accomplished by letting retail prices vary dynamically, either entirely or partly. For the overwhelming majority of customers, that requires a changeout of the metering infrastructure, which may cost as much as $40 billion for the US as a whole. While a good portion of this investment can be covered by savings in distribution system costs, about 40 percent may remain uncovered. This investment gap could be covered by reductions in power generation costs that could be brought about through demand response. Thus, state regulators in many states are investigating whether customers will respond to the higher prices by lowering demand and if so, by how much. To help inform this assessment, we survey the evidence from the 15 most recent experiments with dynamic pricing of electricity. We find conclusive evidence that households (residential customers) respond to higher prices by lowering usage. The magnitude of price response depends on several factors, such as the magnitude of the price increase, the presence of central air conditioning and the availability of enabling technologies such as two-way

Ahmad Faruqui; Sanem Sergici

2009-01-01T23:59:59.000Z

98

Chemical mechanical planarization operation via dynamic programming  

Science Conference Proceedings (OSTI)

In this paper, the impact on non-planarization index by the down force and rotational speed during a SiO"2 or Cu CMP process was investigated. Since the magnitudes of down force and rotational speed have limits, we choose the dynamic programming approach ... Keywords: Chemical mechanical planarization, Copper dishing, Dynamic programming, Non-planarization index, Oxide erosion

Chia-Shui Lin; Yung-Chou Lee

2007-12-01T23:59:59.000Z

99

Three Essays on Price Dynamics and Causations among Energy Markets and Macroeconomic Information  

E-Print Network (OSTI)

This dissertation examines three important issues in energy markets: price dynamics, information flow, and structural change. We discuss each issue in detail, building empirical time series models, analyzing the results, and interpreting the findings. First, we examine the contemporaneous interdependencies and information flows among crude oil, natural gas, and electricity prices in the United States (US) through the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model, Directed Acyclic Graph (DAG) for contemporaneous causal structures and Bernanke factorization for price dynamic processes. Test results show that the DAG from residuals of out-of-sample-forecast is consistent with the DAG from residuals of within-sample-fit. The result supports innovation accounting analysis based on DAGs using residuals of out-of-sample-forecast. Second, we look at the effects of the federal fund rate and/or WTI crude oil price shock on US macroeconomic and financial indicators by using a Factor Augmented Vector Autoregression (FAVAR) model and a graphical model without any deductive assumption. The results show that, in contemporaneous time, the federal fund rate shock is exogenous as the identifying assumption in the Vector Autoregression (VAR) framework of the monetary shock transmission mechanism, whereas the WTI crude oil price return is not exogenous. Third, we examine price dynamics and contemporaneous causality among the price returns of WTI crude oil, gasoline, corn, and the S&P 500. We look for structural break points and then build an econometric model to find the consistent sub-periods having stable parameters in a given VAR framework and to explain recent movements and interdependency among returns. We found strong evidence of two structural breaks and contemporaneous causal relationships among the residuals, but also significant differences between contemporaneous causal structures for each sub-period.

Hong, Sung Wook 1977-

2012-12-01T23:59:59.000Z

100

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

Version 1.0). ” California Energy Commission, PIER Program.Markets. ” University of California Energy Institute: CenterSystem Communications. California Energy Commission, PIER

Ghatikar, Girish

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "dynamic pricing programs" 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

A Dynamic Supply-Demand Model for Electricity Prices Manuela Buzoianu  

E-Print Network (OSTI)

played a role during the crisis period. 1 Introduction The energy industry provides electrical powerA Dynamic Supply-Demand Model for Electricity Prices Manuela Buzoianu , Anthony E. Brockwell of supply and demand equilibrium. The model includes latent supply and demand curves, which may vary over

102

Automated Critical Peak Pricing Field Tests: 2006 Pilot Program...  

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

Center (DRRC) performed a technology evaluation for the Pacific Gas and Electric Company (PG&E) Emerging Technologies Programs. This report summarizes the design, deployment,...

103

Examining Uncertainty in Demand Response Baseline Models and Variability in Automated Response to Dynamic Pricing  

Science Conference Proceedings (OSTI)

Controlling electric loads to deliver power system services presents a number of interesting challenges. For example, changes in electricity consumption of Commercial and Industrial (C&I) facilities are usually estimated using counterfactual baseline models, and model uncertainty makes it difficult to precisely quantify control responsiveness. Moreover, C&I facilities exhibit variability in their response. This paper seeks to understand baseline model error and demand-side variability in responses to open-loop control signals (i.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR) parameters, which characterize changes in electricity use on DR days, and then present a method for computing the error associated with DR parameter estimates. In addition to analyzing the magnitude of DR parameter error, we develop a metric to determine how much observed DR parameter variability is attributable to real event-to-event variability versus simply baseline model error. Using data from 38 C&I facilities that participated in an automated DR program in California, we find that DR parameter errors are large. For most facilities, observed DR parameter variability is likely explained by baseline model error, not real DR parameter variability; however, a number of facilities exhibit real DR parameter variability. In some cases, the aggregate population of C&I facilities exhibits real DR parameter variability, resulting in implications for the system operator with respect to both resource planning and system stability.

Mathieu, Johanna L.; Callaway, Duncan S.; Kiliccote, Sila

2011-08-15T23:59:59.000Z

104

A Price Dynamics in Bandwidth Markets for Point-to-point Connections  

E-Print Network (OSTI)

We simulate a network of N routers and M network users making concurrent point-to-point connections by buying and selling router capacity from each other. The resources need to be acquired in complete sets, but there is only one spot market for each router. In order to describe the internal dynamics of the market, we model the observed prices by N-dimensional Ito-processes. Modeling using stochastic processes is novel in this context of describing interactions between end-users in a system with shared resources, and allows a standard set of mathematical tools to be applied. The derived models can also be used to price contingent claims on network capacity and thus to price complex network services such as quality of service levels, multicast, etc.

Lars Rasmusson; Erik Aurell

2001-02-15T23:59:59.000Z

105

DOE Hydrogen and Fuel Cells Program Record 5014: Electricity Price Effect on Electrolysis Cost  

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

5014 Date: December 15, 2005 5014 Date: December 15, 2005 Title: Electricity Price Effect on Electrolysis Cost Originator: Roxanne Garland Approved by: JoAnn Milliken Date: January 2, 2006 Item: Effect of Electricity Price on Distributed Hydrogen Production Cost (Assumes: 1500 GGE/day, electrolyzer at 76% efficiency, and capital cost of $250/kW) The graph is based on the 2010 target of a 1500 kg/day water electrolysis refueling station described on page 3-12 of the Hydrogen, Fuel Cells and Infrastructure Technologies Program Multi-Year Research, Development and Demonstration Plan, February 2005. The graph uses all the same assumptions associated with the target, except for electricity price: Reference: - 76% efficient electrolyzer - 75% system efficiency

106

Top Ten Utility Green Pricing Programs: November 2000  

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

November 2000 November 2000 Customer Participants (as of November 2000) Rank Utility Program # of Participants 1 Los Angeles Department of Water and Power Green Power for a Green L.A. 65,000* 2 Public Service Company of Colorado Windsource/Renewable Energy Trust 21,000 3 Wisconsin Electric Energy for Tomorrow 12,000 4 Sacramento Municipal Utility District Greenergy/PV Pioneers 8,000 5 Wisconsin Public Service SolarWise for Schools 5,400 6 Madison Gas and Electric Wind Power 4,900 7 Portland General Electric Salmon-Friendly Power/Clean Wind Power 3,900 8 Austin Energy Green Choice 2,800 8 Tennesee Valley Authority Green Power Switch 2,800 10 PacifiCorp Blue Sky 2,700 Source: NREL Notes: * About half of the total are low-income customers that receive existing renewables at no additional cost.

107

Top Ten Utility Green Pricing Programs: April 2000  

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

April 2000 April 2000 Customer Participants (as of April 2000) Rank State Utility Program # of Participants 1 CA Los Angeles Department of Water and Power Green Power for a Green L.A. 31,000 2 CO Public Service Company of Colorado Windsource 14,500 3 WI Wisconsin Electric Energy for Tomorrow 12,000 3 CO Public Service Company of Colorado Renewable Energy Trust 12,000 5 CA Sacramento Municipal Utility District Greenergy 6,100 6 WI Madison Gas and Electric Wind Power 5,200 7 WI Wisconsin Public Service Solar Wise for Schools 4,000 8 OR Eugene Water and Electric Board EWEB Windpower 2,700 9 HI Hawaiian Electric Sun Power for School 2,600 10 OR Portland General Electric Salmon-Friendly Power 2,500 Source: NREL Customer Participation Rates

108

Housing Price Dynamics in Time and Space: Predictability, Liquidity and Investor Returns  

E-Print Network (OSTI)

1991). New evidence on home prices from Freddie Mac repeatmethod for real estate price index construction. Journal ofC. A. (1996). OFHEO house price indexes: HPI technical

Hwang, Min; Quigley, John M.

2010-01-01T23:59:59.000Z

109

Housing Price Dynamics in Time and Space: Predictability, Liquidity and Investor Returns  

E-Print Network (OSTI)

C. A. (1996). OFHEO house price indexes: HPI technicalsense of elevated housing prices. Federal Reserve Bank ofJ. E. (1991). Measuring prices in retransaction housing

Hwang, Min; Quigley, John M.

2010-01-01T23:59:59.000Z

110

Dynamic filter weights neural network model integrated with differential evolution for day-ahead price forecasting in energy market  

Science Conference Proceedings (OSTI)

In this paper a new dynamic model for forecasting electricity prices from 1 to 24h in advance is proposed. The model is a dynamic filter weight Adaline using a sliding mode weight adaptation technique. The filter weights for this neuron constitute of ... Keywords: Differential evolution, Dynamic filter weights neuron, Energy market, Local linear wavelet neural network, Sliding mode control

S. Chakravarty; P. K. Dash

2011-09-01T23:59:59.000Z

111

Western cattle prices vary across video markets and value-adding programs  

E-Print Network (OSTI)

results show average price differences between the regionthe highest average prices. † These values are statisticallyfactors affecting cow auction price differentials. Southern

Blank, Steven C.; Boriss, Hayley; Forero, Larry C.; Nader, Glenn A.

2006-01-01T23:59:59.000Z

112

Unstable Price Dynamics as a Result of Information Absorption in Speculative Markets  

E-Print Network (OSTI)

In speculative markets, risk-free profit opportunities are eliminated by traders exploiting them. Markets are therefore often described as "informationally efficient", rapidly removing predictable price changes, and leaving only residual unpredictable fluctuations. This classical view of markets absorbing information and otherwise operating close to an equilibrium is challenged by extreme price fluctuations, in particular since they occur far more frequently than can be accounted for by external news. Here we show that speculative markets which absorb mainly self-generated information can exhibit both: evolution towards efficient equilibrium states as well as their subsequent destabilization. This peculiar dynamics, a generic instability arising from an adaptive control which annihilates predictable information, is realized in a minimal agent-based market model where the impacts of agents' strategies adapt according to their trading success. This adaptation implements a learning rule for the market as a whole...

Patzelt, Felix

2012-01-01T23:59:59.000Z

113

How and why customers respond to electricity price variability: A study of NYISO and NYSERDA 2002 PRL program performance  

SciTech Connect

This summer was the second year of operation for the New York Independent System Operator's (NYISO) suite of Price Responsive Load (PRL) Programs: the Day-Ahead Demand Response Program (DADRP), the Emergency Demand Response Program (EDRP), and the third year of operation for the Installed Capacity Program/Special Case Resources (ICAP/SCR) program. It also marked the second year that the New York State Energy Research Authority (NYSERDA) provided funding to support participation in these programs. NYISO and NYSERDA commissioned Neenan Associates to conduct a comprehensive evaluation of the performance of these PRL programs, building on methods and protocols developed last year and augmented by significant professional staff resources provided by the Consortium for Electric Reliability Technology Solutions (CERTS) with the U. S. Dept. of Energy (DOE) funding. The PRL program evaluation was undertaken from three perspectives. The first, top-down, perspective looks at the overall impact of PRL programs on New York electricity market prices and system reliability. Quantifying price impacts involves simulating what prices would have been had the curtailments not been undertaken. A supply model developed last year was used to reconstruct this year's market supply curve and estimate the change in hourly prices due to PRL-indiced curtailments. Reliability impacts were estimated by valuing the improvement in the reliability associated with curtailments undertaken through the EDRP and ICAP/SCR programs, which were jointly administered during 2002.

Neenan, Bernie; Pratt, Donna; Cappers, Peter; Doane, James; Anderson, Jeremey; Boisvert, Richard; Goldman, Charles; Sezgen, Osman; Barbose, Galen; Bharvirkar, Ranjit

2003-01-01T23:59:59.000Z

114

Automated Critical Peak Pricing Field Tests: 2006 Program Description and Results APPENDICES  

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

Automated Critical Peak Pricing Field Tests: 2006 Program Description and Results APPENDICES Mary Ann Piette David Watson Naoya Motegi Sila Kiliccote Lawrence Berkeley National Laboratory MS90R3111 1 Cyclotron Road Berkeley, California 94720 August 30, 2007 This work described in this report was coordinated by the Demand Response Research Center and funded by the California Energy Commission, Public Interest Energy Research Program, under Work for Others Contract No. 150-99-003, Am #1 and by the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. LBNL Report Number 62218 2 Table of Contents List of Tables ......................................................................................................................................3

115

Do 'enabling technologies' affect customer performance in price-responsive load programs?  

SciTech Connect

Price-responsive load (PRL) programs vary significantly in overall design, the complexity of relationships between program administrators, load aggregators, and customers, and the availability of ''enabling technologies''. Enabling technologies include such features as web-based power system and price monitoring, control and dispatch of curtailable loads, communications and information systems links to program participants, availability of interval metering data to customers in near real time, and building/facility/end-use automation and management capabilities. Two state agencies - NYSERDA in New York and the CEC in California - have been conspicuous leaders in the demonstration of demand response (DR) programs utilizing enabling technologies. In partnership with key stakeholders in these two states (e.g., grid operator, state energy agencies, and program administrators), Lawrence Berkeley National Laboratory (LBNL) and Pacific Northwest National Laboratory (PNNL) surveyed 56 customers who worked with five contractors participating in CEC or NYSERDA-sponsored DR programs. We combined market research and actual load curtailment data when available (i.e., New York) or customer load reduction targets in order to explore the relative importance of contractor's program design features, sophistication of control strategies, and reliance on enabling technologies in predicting customer's ability to deliver load reductions in DR programs targeted to large commercial/industrial customers. We found preliminary evidence that DR enabling technology has a positive effect on load curtailment potential. Many customers indicated that web-based energy information tools were useful for facilitating demand response (e.g., assessing actual performance compared to load reduction contract commitments), that multiple notification channels facilitated timely response, and that support for and use of backup generation allowed customers to achieve significant and ! predictable load curtailment s. We also found that 60-70 percent of the customers relied on manual approaches to implementing load reductions/curtailments, rather than automated load control response. The long-term sustainability of customer load curtailments would be significantly enhanced by automated load response capabilities, such as optimizing EMCS systems to respond to day-ahead energy market prices or load curtailments in response to system emergencies.

Goldman, Charles A.; Kintner-Meyer, Michael; Heffner, Grayson

2002-05-15T23:59:59.000Z

116

Do 'enabling technologies' affect customer performance in price-responsive load programs?  

SciTech Connect

Price-responsive load (PRL) programs vary significantly in overall design, the complexity of relationships between program administrators, load aggregators, and customers, and the availability of ''enabling technologies''. Enabling technologies include such features as web-based power system and price monitoring, control and dispatch of curtailable loads, communications and information systems links to program participants, availability of interval metering data to customers in near real time, and building/facility/end-use automation and management capabilities. Two state agencies - NYSERDA in New York and the CEC in California - have been conspicuous leaders in the demonstration of demand response (DR) programs utilizing enabling technologies. In partnership with key stakeholders in these two states (e.g., grid operator, state energy agencies, and program administrators), Lawrence Berkeley National Laboratory (LBNL) and Pacific Northwest National Laboratory (PNNL) surveyed 56 customers who worked with five contractors participating in CEC or NYSERDA-sponsored DR programs. We combined market research and actual load curtailment data when available (i.e., New York) or customer load reduction targets in order to explore the relative importance of contractor's program design features, sophistication of control strategies, and reliance on enabling technologies in predicting customer's ability to deliver load reductions in DR programs targeted to large commercial/industrial customers. We found preliminary evidence that DR enabling technology has a positive effect on load curtailment potential. Many customers indicated that web-based energy information tools were useful for facilitating demand response (e.g., assessing actual performance compared to load reduction contract commitments), that multiple notification channels facilitated timely response, and that support for and use of backup generation allowed customers to achieve significant and ! predictable load curtailment s. We also found that 60-70 percent of the customers relied on manual approaches to implementing load reductions/curtailments, rather than automated load control response. The long-term sustainability of customer load curtailments would be significantly enhanced by automated load response capabilities, such as optimizing EMCS systems to respond to day-ahead energy market prices or load curtailments in response to system emergencies.

Goldman, Charles A.; Kintner-Meyer, Michael; Heffner, Grayson

2002-05-15T23:59:59.000Z

117

Automated Critical Peak Pricing Field Tests: 2006 Pilot Program Description and Results  

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

i Automated Critical Peak Pricing Field Tests: 2006 Pilot Program Description and Results Mary Ann Piette David Watson Naoya Motegi Sila Kiliccote Lawrence Berkeley National Laboratory MS90R3111 1 Cyclotron Road Berkeley, California 94720 June 19, 2007 LBNL Report Number 62218 ii Acknowledgements The work described in this report was funded by the Emerging Technologies Program at Pacific Gas and Electric Company. Additional funding was provided by the Demand Response Research Center which is funded by the California Energy Commission (Energy Commission), Public Interest Energy Research (PIER) Program, under Work for Others Contract No.500-03-026, Am #1 and by the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The authors are grateful for the extensive

118

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network (OSTI)

of communicating real-time prices to electricity customers.and demand conditions. Real-time prices can be set with day-e.g. , mapping real-time prices to “normal, moderate, or

Ghatikar, Girish

2010-01-01T23:59:59.000Z

119

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network (OSTI)

CAISO’s Wholesale Energy Market Prices PG&E’s PDP TariffWe used the CAISO wholesale energy market prices for the RTPusing CAISO wholesale energy market prices allowed us to

Ghatikar, Girish

2010-01-01T23:59:59.000Z

120

Gasoline Prices  

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

Gasoline Prices Gasoline Price Data Sign showing gasoline prices Local Prices: Find the cheapest gasoline prices in your area. State & Metro Area Prices: Average prices from AAA's...

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Abstract--A stochastic dynamic programming hydrothermal dispatch model to simulate a bid-based market is  

E-Print Network (OSTI)

on dynamic programming that optimizes and validates the bid prices strategies for each power plant in a hydro-thermal, and simulating them as if they were a single power plant. In a hydro-thermal system as the one simulated several plants. Emphasis is given to hydro reservoir modeling and to the assessment of their market power

Catholic University of Chile (Universidad CatĂłlica de Chile)

122

BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation | Department  

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

BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation The Brattle Group was retained by Baltimore Gas & Electric Company (BGE) in December 2006 to assist in the design of a dynamic pricing pilot program to develop assessments of the likely impact of a variety of dynamic pricing programs on BGE residential customer load shapes. The residential pilot program, Smart Energy Pricing (SEP) Pilot, was subsequently approved by the Maryland Public Service Commission and successfully implemented in the summer of 2008. This report presents the results from the impact evaluation of the BGE's SEP Pilot in the summer of 2008. BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation More Documents & Publications

123

BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation | Department  

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

BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation The Brattle Group was retained by Baltimore Gas & Electric Company (BGE) in December 2006 to assist in the design of a dynamic pricing pilot program to develop assessments of the likely impact of a variety of dynamic pricing programs on BGE residential customer load shapes. The residential pilot program, Smart Energy Pricing (SEP) Pilot, was subsequently approved by the Maryland Public Service Commission and successfully implemented in the summer of 2008. This report presents the results from the impact evaluation of the BGE's SEP Pilot in the summer of 2008. BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation More Documents & Publications

124

The Conservation Reserve Program as a Means to Subsidize Bioenergy Crop Prices  

DOE Green Energy (OSTI)

The Conservation Reserve Program (CRP), enacted in the 1985 Farm Bill, removes environmentally sensitive cropland from production in exchange for annual rental payments from the federal government. To reduce the cost of the program, economic use of CRP acres in exchange for reduced rental payments were proposed, but not implemented in the 1995 Farm Bill. This paper examines the potential impact an economic use policy would have on the market prices of bioenergy crops if they were permitted to be harvested from CRP acres. The analysis shows that at average yields of 11.25 dry Mg/ha/yr (5 dry tons/ac/yr) and total production of 9.1 million dry Mg (10 million dry tons) subsidized farmgate prices of as low as $16.5/dry Mg ($15/dry ton) for switchgrass and $24.2/dry Mg ($22/dry ton) for short-rotation woody crops can be achieved. Furthermore, the government can reduce the cost of the CRP resulting in a potential win-win situation.

Walsh, M.E.; Becker, D.; Graham, R.L.

1996-09-15T23:59:59.000Z

125

Characterizing the Response of Commercial and Industrial Facilities to Dynamic Pricing Signals from the Utility  

E-Print Network (OSTI)

energy costs. However, to participate in real-time electricity markets, facilities would receive pricing information

Mathieu, Johanna L.

2010-01-01T23:59:59.000Z

126

Operation of Distributed Generation Under Stochastic Prices  

E-Print Network (OSTI)

Generation Under Stochastic Prices Afzal S. Siddiqui andGENERATION UNDER STOCHASTIC PRICES AFZAL SIDDIQUI AND CHRIStransactions at stochastic prices. A stochastic dynamic

Siddiqui, Afzal S.; Marnay, Chris

2005-01-01T23:59:59.000Z

127

Real Estate Prices and Economic Cycles  

E-Print Network (OSTI)

Hyclak, T. (1994) “ House Prices, Migration, and RegionalPoterba, J. M. (1991) “House Price Dynamics: The Role of TaxVariations in Regional Housing Prices Predictable? ” mimeo,

Quigley, John M.

2002-01-01T23:59:59.000Z

128

Customer reponse to day-ahead wholesale market electricity prices: Case study of RTP program experience in New York  

E-Print Network (OSTI)

ahead Wholesale Market Electricity Prices: Case Study of RTPahead Wholesale Market Electricity Prices: Case Study of RTPElectricity Prices

2004-01-01T23:59:59.000Z

129

Dynamic pricing and stabilization of supply and demand in modern electric power grids  

E-Print Network (OSTI)

The paper proposes a mechanism for real-time pricing of electricity in smart power grids, with price stability as the primary concern. In previous publications the authors argued that relaying the real-time wholesale market ...

Roozbehani, Mardavij

130

Stochastic dynamic optimization of consumption and the induced price elasticity of demand in smart grids  

E-Print Network (OSTI)

This thesis presents a mathematical model of consumer behavior in response to stochastically-varying electricity prices, and a characterization of price-elasticity of demand created by optimal utilization of storage and ...

Faghih, Ali

2011-01-01T23:59:59.000Z

131

The Luxury casino hotel dynamic price strategy practices for the FIT customer segment.  

E-Print Network (OSTI)

??This research paper compares room rate luxury casino hotel pricing pattern between the periods of 4/1/2009 to 6/30/2009). A good price strategy can help a… (more)

Chen, Lei

2009-01-01T23:59:59.000Z

132

Green Power Network: Top Ten Utility Green Pricing Programs, December 2008  

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

December 2009 December 2009 Green Pricing Program Renewable Energy Sales (as of December 2009) Rank Utility Resources Used Sales (kWh/year) Sales (aMW)a 1 Austin Energy Wind, landfill gas 764,895,830 87.3 2 Portland General Electricb Wind, biomass, geothermal 740,880,487 84.6 3 PacifiCorpcde Wind, biomass, landfill gas, solar 578,744,080 66.1 4 Sacramento Municipal Utility Districtc Wind, hydro, biomass, solar 377,535,530 43.1 5 Xcel Energycf Wind, solar 374,296,375 42.7 6 Puget Sound Energycg Wind, landfill gas, biomass, small hydro, solar 303,046,167 34.6 7 Connecticut Light and Power/ United Illuminating Wind, hydro 197,458,734 22.5 8 National Gridh Biomass, wind, small hydro, solar 174,536,130 19.9 9 Public Service Company of New Mexico Wind 173,863,751 19.8

133

Green Power Network: Top Ten Utility Green Pricing Programs, December 2007  

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

7 7 Green Pricing Program Renewable Energy Sales (as of December 2007) Rank Utility Resources Used Sales (kWh/year) Sales (Avg. MW)a 1 Austin Energy Wind, landfill gas 577,636,840 65.9 2 Portland General Electricb Geothermal, biomass, wind 553,677,903 63.2 3 PacifiCorpcde Wind, biomass, landfill gas, solar 383,618,885 43.8 4 Florida Power & Lightb Biomass, wind, landfill gas, solar 373,596,000 42.6 5 Xcel Energyef Wind 326,553,866 37.3 6 Sacramento Municipal Utility Districte Wind, landfill gas, small hydro, solar 275,481,584 31.4 7 Puget Sound Energye Wind, solar, biomass, landfill gas 246,406,200 28.1 8 Basin Electric Power Cooperative Wind 226,474,000 25.9 9 National Gridgh Biomass, wind, small hydro, solar 180,209,571 20.6

134

Are You Ready Phase Two? Pricing Changes and Commercial Products Added to DOE High-Performance Windows Program  

Science Conference Proceedings (OSTI)

This article, for publication in Door and Window Manufacturer magazine, describes DOE's High Performance Windows Volume Purchase Program, WVPP, and how PNNL, which manages the program for DOE, is assisting DOE in the transition to the next phase (Phase II), which begins in May. While the foundation of the program will remain relatively unchanged, PNNL is employing several new strategies to continue the momentum built during the program's first full year of implementation. The program helps buyers and manufacturers to develop a market for highly insulating windows and low-E storm windows at affordable prices and thereby overcome the principal barrier of cost.

Mapes, Terry S.

2011-05-01T23:59:59.000Z

135

Application of dynamic programming model in inventory management.  

E-Print Network (OSTI)

???This thesis aims to apply dynamic programming approach to formulate three main topics related to inventory management under three real world situations and then propose… (more)

Tao, Feng ( ??)

2011-01-01T23:59:59.000Z

136

2012 SG Peer Review - Recovery Act: NSTAR Automated Mater Reading Based Dynamic Pricing - Douglas Horton, NSTAR Electric & Gas  

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

Peer Peer Review Meeting Peer Review Meeting AMR Based Dynamic Pricing y g Doug Horton NSTAR Electric & Gas Co. 6/8/2012 AMR Based Dynamic Pricing Objective Provide two-way communication of electricity cost & consumption data utilizing the customers existing meter & Internet. Goal to achieve 5% reduction in peak and Goal to achieve 5% reduction in peak and average load. Life-cycle Funding ($K) Total Budget Total DOE Funding to Technical Scope Use customer's existing AMR meter and broadband Internet to achieve two way Total Budget Total DOE Funding Funding to Date $4,900k $2,362k $1,623k broadband Internet to achieve two way communication and "AMI" functionality Cutting-edge solution to integrate: * Existing meters E i ti I t t December 2008 * Existing Internet * Existing billing & CIS

137

Dynamic heap type inference for program understanding and debugging  

Science Conference Proceedings (OSTI)

C programs can be difficult to debug due to lax type enforcement and low-level access to memory. We present a dynamic analysis for C that checks heap snapshots for consistency with program types. Our approach builds on ideas from physical subtyping and ... Keywords: conservative garbage collection, constraints, debugging tools, dynamic type inference, heap visualization, physical subtyping

Marina Polishchuk; Ben Liblit; Chloë W. Schulze

2007-01-01T23:59:59.000Z

138

Program partitioning: a framework for combining static and dynamic analysis  

Science Conference Proceedings (OSTI)

For higher quality software, static analysis and dynamic analysis should be used in a complementary manner. In this work, we explore the concept of partitioning a program such that the partitions can be analyzed separately. With such partitioning, potentially ... Keywords: dynamic analysis, program partitioning, static analysis

Pankaj Jalote; Vipindeep Vangala; Taranbir Singh; Prateek Jain

2006-05-01T23:59:59.000Z

139

3 MICROSIMULATING AUTOMOBILE MARKETS: 4 EVOLUTION OF VEHICLE HOLDINGS AND VEHICLE-PRICING DYNAMICS  

E-Print Network (OSTI)

. This work combines an auction-style 33 microsimulation of vehicle prices and random-utility vehicles and the infrastructure they use, directly and peripherally. To understand and anticipate 46 travel to vehicle aging. This paper60 makes explicit the role of user preferences in vehicle price fluctuations

Kockelman, Kara M.

140

Green Power Network: Top Ten Utility Green Pricing Programs, December 2008  

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

8 8 Green Pricing Program Renewable Energy Sales (as of December 2008) Rank Utility Resources Used Sales (kWh/year) Sales (Avg. MW)a 1 Austin Energy Wind, landfill gas 723,824,901 82.6 2 Portland General Electricb Wind, biomass 681,943,576 77.9 3 PacifiCorpcde Wind, biomass, landfill gas, solar 492,892,222 56.3 4 Xcel Energyef Wind 362,040,082 41.3 5 Sacramento Municipal Utility Districte Wind, solar, biomass, landfill gas, hydro 325,275,628 37.1 6 Puget Sound Energye Wind, solar, biomass, landfill gas, hydro 291,166,600 33.2 7 Public Service Company of New Mexico Wind 176,497,697 20.1 8 We Energiese Wind, landfill gas, solar 176,242,630 20.1 9 National Gridgh Biomass, wind, small hydro, solar 174,612,444 19.9 10 PECOi Wind 172,782,490 19.7

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


141

Green Power Network: Top Ten Utility Green Pricing Programs, December 2002  

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

2 2 Green Pricing Program Renewable Energy Sales (as of December 2002) Rank Utility Resources Sales (kWh/year) Sales (Avg. MW)1 1 Austin Energy Wind, landfill gas, solar 251,520,000 28.7 2 Sacramento Municipal Utility District Landfill gas, wind, solar 104,344,0002 11.9 3 Xcel Energy Wind and solar 103,739,0003 11.8 4 Los Angeles Department of Power and Water Wind and landfill gas 66,666,0004 7.6 5 Portland General Electric5 Wind and geothermal 57,989,000 6.6 6 PacifiCorp5 Wind and geothermal 55,615,000 6.3 7 Tennessee Valley Authority Wind, biomass, landfill gas, solar 35,955,000 4.1 8 We Energies Landfill gas, wind, hydro 35,161,000 4.0 9 Puget Sound Energy Wind and solar 20,334,000 2.3 10 Madison Gas and Electric Wind 15,593,000 1.8

142

Prices and Price Setting.  

E-Print Network (OSTI)

??This thesis studies price data and tries to unravel the underlying economic processes of why firms have chosen these prices. It focuses on three aspects… (more)

Faber, R.P.

2010-01-01T23:59:59.000Z

143

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network (OSTI)

OASIS SDO. “Energy Market Information Exchange (eMIX)information are published: For each of these wholesale markets, wholesale prices for energy andInformation System (OASIS) [7]. We used the CAISO wholesale energy market

Ghatikar, Girish

2010-01-01T23:59:59.000Z

144

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network (OSTI)

existing TOU tariff and a peak energy charge ( $1.20/kWh) isWholesale Energy Market Prices PG&E’s PDP Tariff PG&E’s TOU

Ghatikar, Girish

2010-01-01T23:59:59.000Z

145

Socioeconophysics: Opinion Dynamics for number of transactions and price, a trader based model  

E-Print Network (OSTI)

Involving effects of media, opinion leader and other agents on the opinion of individuals of market society, a trader based model is developed and utilized to simulate price via supply and demand. Pronounced effects are considered with several weights and some personal differences between traders are taken into account. Resulting time series and probabilty distribution function involving a power law for price come out similar to the real ones.

Tuncay, C

2006-01-01T23:59:59.000Z

146

The Potential of Energy Management and Control Systems for Real-Time Electricity Pricing Programs  

E-Print Network (OSTI)

In implementing an integrated electric utility network, direct communication between the utility and customers is an important component. The rapid penetration of computer building control technology in larger commercial and industrial customers provides an opportunity for the utility to implement this network by linking directly with equipment already in place: customer-owned energy management and control systems (EMCS). This paper assesses the potential use of EMCSs in utility real-time pricing (RTP) efforts by discussing the procedures and technical requirements for transferring prices to the EMCS. The perspectives and objectives of the customer and the utility will also be discussed. We will discuss how price information can be used by the customer and the EMCS to implement demand-limiting strategies, both in currently available demand-management algorithms, and in potential price-responsive cost-management algorithms.

Akbari, H.; Heinemeier, K. E.

1990-01-01T23:59:59.000Z

147

A Branch-Price-and-Cut Algorithm for Single-Product Maritime Inventory Routing  

Science Conference Proceedings (OSTI)

A branch-price-and-cut algorithm is developed for a complex maritime inventory-routing problem with varying storage capacities and production/consumption rates at facilities. The resulting mixed-integer pricing problem is solved exactly and efficiently ... Keywords: column generation, dynamic programming, integer programming, maritime inventory routing

Faramroze G. Engineer; Kevin C. Furman; George L. Nemhauser; Martin W. P. Savelsbergh; Jin-Hwa Song

2012-01-01T23:59:59.000Z

148

A CMOS Current-Mode Dynamic Programming Circuit  

E-Print Network (OSTI)

Dynamic programming (DP) is a fundamental algorithm for complex optimization and decision-making in many engineering and biomedical systems. However, conventional DP computation based on digital implementation of the ...

Mak, Terrence

149

Performance of Dynamic Programming methods in airline Revenue Management  

E-Print Network (OSTI)

This thesis evaluates the performance of Dynamic Programming (DP) models as applied to airline Revenue Management (RM) compared to traditional Revenue Management models like EMSRb as DP models offer a theoretically attractive ...

Diwan, Sarvee

2010-01-01T23:59:59.000Z

150

Using Dynamic Tracing Sampling to Measure Long Running Programs  

Science Conference Proceedings (OSTI)

Detailed cache simulation can be useful to both system developers and application writers to understand an application's performance. However, measuring long running programs can be extremely slow. In this paper we present a technique to use dynamic ...

Jeffrey Odom; Jeffrey K. Hollingsworth; Luiz DeRose; Kattamuri Ekanadham; Simone Sbaraglia

2005-11-01T23:59:59.000Z

151

Improvement of an EVT-based HEV using dynamic programming  

E-Print Network (OSTI)

vehicle, dynamic programming, electrical variable transmission I. INTRODUCTION Hybrid Electric Vehicles for automotive hybridization [4], [6]. However other advanced SP-HEVs like the Electric Variable Transmission. Abstract- Automotive engineers and researchers have proposed different Series-Parallel Hybrid Electric

Recanati, Catherine

152

Approximate dynamic programming with applications in multi-agent systems  

E-Print Network (OSTI)

This thesis presents the development and implementation of approximate dynamic programming methods used to manage multi-agent systems. The purpose of this thesis is to develop an architectural framework and theoretical ...

Valenti, Mario J. (Mario James), 1976-

2007-01-01T23:59:59.000Z

153

An Approximate Dynamic Programming Approach to Benchmark Practice-based Heuristics for Natural Gas Storage Valuation  

E-Print Network (OSTI)

The valuation of the real option to store natural gas is a practically important problem that entails dynamic optimization of inventory trading decisions with capacity constraints in the face of uncertain natural gas price dynamics. Stochastic dynamic programming is a natural approach to this valuation problem, but it does not seem to be widely used in practice because it is at odds with the high-dimensional naturalgas price evolution models that are widespread among traders. According to the practice-based literature, practitioners typically value natural gas storage heuristically. The effectiveness of the heuristics discussed in this literature is currently unknown, because good upper bounds on the value of storage are not available. We develop a novel and tractable approximate dynamic programming method that coupled with Monte Carlo simulation computes lower and upper bounds on the value of storage, which we use to benchmark these heuristics on a set of realistic instances. We find that these heuristics are extremely fast but significantly suboptimal as compared to our upper bound, which appears to be fairly tight and much tighter than a simpler perfect information upper bound; our lower bound is slower to compute than these heuristics but substantially outperforms them in terms of valuation. Moreover, with periodic reoptimizations embedded in Monte Carlo simulation, the practice-based heuristics become nearly optimal, with one exception, at the expense of higher computational effort. Our lower bound with reoptimization is also nearly optimal, but exhibits a higher computational requirement than these heuristics. Besides natural gas storage, our results are potentially relevant for the valuation of the real option to store other commodities, such as metals, oil, and petroleum products. 1.

Guoming Lai; François Margot; Nicola Secom

2008-01-01T23:59:59.000Z

154

Free Space Computation Using Stochastic Occupancy Grids and Dynamic Programming  

E-Print Network (OSTI)

1 Free Space Computation Using Stochastic Occupancy Grids and Dynamic Programming Hern´an Badino1Chrysler AG, Stuttgart Abstract. The computation of free space available in an environment is an essential, which builds a stochastic occupancy grid to address the free space problem as a dynamic pro- gramming

Mester, Rudolf

155

Inventory Fluctuations and Price Discrimination: The Determinants of Price Variation in Car Retailing  

E-Print Network (OSTI)

Dynamic Pricing of Inventories with Stochastic Demand overStatistics † Obs Price Inventory DaysToTurn LocalInv LotFullTable 2: Price e?ects of inventory † Dep. Var. ln(price)

Zettelmeyer, Florian; Scott Morton, Fiona; Silva-Risso, Jorge

2005-01-01T23:59:59.000Z

156

INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization  

SciTech Connect

It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms we have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.

Groer, Christopher S [ORNL; Sullivan, Blair D [ORNL; Weerapurage, Dinesh P [ORNL

2012-10-01T23:59:59.000Z

157

Providing Dynamic Instructional Adaptation in Programming Learning  

Science Conference Proceedings (OSTI)

This paper describes an approach to create an Intelligent Tutoring System that provides dynamic personalization and learning activities sequencing adaptation by combining eLearning standards and Artificial Intelligent techniques. The work takes advantage ...

Francisco Jurado; Olga C. Santos; Miguel A. Redondo; Jesús G. Boticario; Manuel Ortega

2008-09-01T23:59:59.000Z

158

Dynamic analysis for reverse engineering and program understanding  

Science Conference Proceedings (OSTI)

The main focus of program understanding and reverse engineering research has been on modeling the structure of a program by examining its code. This has been the result of the nature of the systems investigated and the perceived goals of the reverse ... Keywords: dynamic analysis, reverse engineering

Eleni Stroulia; Tarja Systä

2002-04-01T23:59:59.000Z

159

Price strategies in dynamic duopolistic markets with deregulated electricity supplies using mixed strategies  

Science Conference Proceedings (OSTI)

While effective competition can force service providers to seek economically efficient methods to reduce costs, the deregulated electricity supply industry still allows some generators to exercise market power at particular locations, thereby preventing ... Keywords: deregulated electricity supplies, mixed strategies, price strategies

Jose B. Cruz, Jr.; Xiaohuan Tan

2005-10-01T23:59:59.000Z

160

Price strategies in dynamic duopolistic markets with deregulated electricity supplies using mixed strategies  

Science Conference Proceedings (OSTI)

While effective competition can force service providers to seek economically efficient methods to reduce costs, the deregulated electricity supply industry still allows some generators to exercise market power at particular locations, thereby preventing ... Keywords: Deregulated electricity supplies, Mixed strategies, Price strategies

Jose B. Cruz, Jr.; Xiaohuan Tan

2005-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Customer reponse to day-ahead wholesale market electricity prices: Case study of RTP program experience in New York  

E-Print Network (OSTI)

Response to Electricity Real-Time Prices: Short Run and LongElectricity Usage to Real Time Prices A-31 v List ofwere linked to real-time prices, most customers indicated

2004-01-01T23:59:59.000Z

162

Customer reponse to day-ahead wholesale market electricity prices: Case study of RTP program experience in New York  

E-Print Network (OSTI)

of the monthly electricity bill), (3) the pricing methodof the monthly SC-3A electricity bill (@ X%) Hedge PricePrice @ Cost (as % of electricity bill) Covered Hours: Hedge

2004-01-01T23:59:59.000Z

163

A Survey of Load Control Programs for Price and System Stability  

Science Conference Proceedings (OSTI)

Load control and demand side load management programs have been implemented in a large number of competitive power markets. These programs can provide enhanced system security and many benefits to participants. This paper reviews and compares existing economically driven programs.

Jazayeri, P.; Schellenberg, A.; Rosehart, W. D.; Doudna, J.; Widergren, Steven E.; Lawrence, D.; Mickey, J.; Jones, S.

2005-08-01T23:59:59.000Z

164

Extending Tcl for Dynamic Object-Oriented Programming  

E-Print Network (OSTI)

Object Tcl is an extension to the Tool Command Language (Tcl) for the management of complicated data types and dynamic object-oriented programming in general. We believe it is a worthy alternative to other object-oriented programming extensions (including [incr Tcl]) because it may be used dynamically, allows for per object specialization, has an economy of design and implementation, and provides a metaobject-based class system. Its design was driven by our VuSystem application needs to create a foundation with powerful abstraction and introspection capabilities, yet we sought to retain both the spirit and benefits of Tcl. This paper presents Object Tcl, emphasizing language design and implementation issues by comparing it with alternative systems. Keywords: object-oriented programming, Tcl, programming languages, [incr Tcl] 1 Introduction Object Tcl is an object-oriented extension to the Tool command Language (Tcl) [12] that we created to meet the programming needs...

David Wetherall; David Wetherall; Christopher J. Lindblad; Christopher J. Lindblad

1995-01-01T23:59:59.000Z

165

Electricity price impacts of alternative Greenhouse gas emission cap-and-trade programs  

SciTech Connect

Limits on greenhouse gas emissions would raise the prices of the goods and services that require such emissions for their production, including electricity. Looking at a variety of emission limit cases and scenarios for selling or allocating allowances to load-serving entities, the authors estimate how the burden of greenhouse gas limits are likely to be distributed among electricity consumers in different states. (author)

Edelston, Bruce; Armstrong, Dave; Kirsch, Laurence D.; Morey, Mathew J.

2009-07-15T23:59:59.000Z

166

Qualification of a computer program for drill string dynamics  

DOE Green Energy (OSTI)

A four point plan for the qualification of the GEODYN drill string dynamics computer program is described. The qualification plan investigates both modal response and transient response of a short drill string subjected to simulated cutting loads applied through a polycrystalline diamond compact (PDC) bit. The experimentally based qualification shows that the analytical techniques included in Phase 1 GEODYN correctly simulate the dynamic response of the bit-drill string system. 6 refs., 8 figs.

Stone, C.M.; Carne, T.G.; Caskey, B.C.

1985-01-01T23:59:59.000Z

167

Dynamical Theory of Price and Money in Volatile Markets. A Physicist's Reaction to Economics  

E-Print Network (OSTI)

The creation and annihilation of money and its economic effects are reviewed. Economic values appear "in the mind" of the market participants; e.g., by pretending, maintaining and achieving a particular price for a certain asset. Upon its creation by banks, this kind of "value phantasy" is converted into "real money" often in terms of buyer's debt accompanied by a simultaneous payment of fiat money to the seller. This money is then multiplied on the money market and is competing against other money supplies for the traded assets, goods and services, where it may cause dilution, inflation and reallocation of resources.

Svozil, Karl

2008-01-01T23:59:59.000Z

168

Gas Market Transition: Impacts of Power Generation on Gas Pricing Dynamics  

Science Conference Proceedings (OSTI)

The power sector is beginning to influence the natural gas market, affecting both total natural gas demand and aspects of natural gas price behavior. This report offers a single source that quantifies these influences. With the addition of new gas-fired generating capacity, the use of gas generation in the power sector has grown steadily. However, this progression was arrested after 2002 when the brunt of overbuilding was felt, and gas use in the power sector migrated to ever more efficient units. While ...

2005-03-16T23:59:59.000Z

169

Heuristic Reusable Dynamic Programming: Efficient Updates of Local Sequence Alignment  

Science Conference Proceedings (OSTI)

Recomputation of the previously evaluated similarity results between biological sequences becomes inevitable when researchers realize errors in their sequenced data or when the researchers have to compare nearly similar sequences, e.g., in a family of ... Keywords: Shortest path, minimum spanning tree, sensitivity analysis, dynamic programming, sequence alignment, string edit, suboptimal paths.

Changjin Hong; Ahmed H. Tewfik

2009-10-01T23:59:59.000Z

170

APPROXIMATE DYNAMIC PROGRAMMING METHODS FOR COOPERATIVE UAV SEARCH  

E-Print Network (OSTI)

APPROXIMATE DYNAMIC PROGRAMMING METHODS FOR COOPERATIVE UAV SEARCH Matthew Flint Emmanuel 01801 matt.flint@baesystems.com Dept. of Electrical and Computer Engineering and Computer Science by the authors of this paper e.g. (Flint et al., 2003b), (Flint et al., 2003a), (Flint et al., 2004); and others

Fernandez, Emmanuel

171

Utility-aware deferred load balancing in the cloud driven by dynamic pricing of electricity  

Science Conference Proceedings (OSTI)

Distributed computing resources in a cloud computing environment provides an opportunity to reduce energy and its cost by shifting loads in response to dynamically varying availability of energy. This variation in electrical power availability is represented ...

Muhammad Abdullah Adnan, Rajesh Gupta

2013-03-01T23:59:59.000Z

172

Abstract--A key component of the smart grid is the ability to enable dynamic residential pricing to incentivize the customer  

E-Print Network (OSTI)

Abstract-- A key component of the smart grid is the ability to enable dynamic residential pricing, Multiple Knapsack Problem (MKP), Optimization, Smart Grids. I. INTRODUCTION With ever challenge to the future electricity distribution systems. The smart grid has emerged as a solution

Sapatnekar, Sachin

173

Superstatistical fluctuations in time series: applications to share price dynamics and turbulence  

E-Print Network (OSTI)

We introduce a general technique to study whether a given experimental time series is superstatistical. Crucial for the applicability of the superstatistics concept is the existence of a parameter $\\beta$ that fluctuates on a large time scale as compared to the other time scales of the complex system under consideration. The proposed method extracts the main superstatistical parameters out of a given data set and checks the validity of the superstatistical model assumptions. We test the method thoroughly with surrogate data sets. Then the applicability of the superstatistical approach is illustrated using real experimental data. We study two examples, velocity time series measured in turbulent Taylor-Couette flows and time series of log-returns of the closing prices of some stock market indices.

Van der Straeten, Erik

2009-01-01T23:59:59.000Z

174

Natural Gas Citygate Price  

Gasoline and Diesel Fuel Update (EIA)

Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 1231 Reserves...

175

Beyond the Price Effect in Time-of-Use Programs: Results from a Municipal Utility Pilot, 2007-2008  

Science Conference Proceedings (OSTI)

This paper discusses results of a two-year collaborative research project between the authors and the Demand Response Research Center focused on behavioral response to a voluntary time-of-use pilot rate offered by the Sacramento Municipal Utilities District (SMUD) under the PowerChoice label. The project had two purposes: one was to assess the potential for increasing demand response through the introduction of enhanced information and real-time consumption feedback; the second was to better understand behavioral response to a TOU rate. Three successive waves of telephone surveys collected details about reasons for participation, actions taken, capacities and constraints to altering behavior, and a range of salient conditions, such as demographics and dwelling characteristics. Pre- and post-program interval meter data for participants and a comparison sample of households were also collected and analyzed to consider initial and season-change price effects of the rate and the effect of supplemental information treatments on response. Over half of surveyed participating households reported that they had made a great deal of effort to adjust their electricity consumption to the rate. Despite this, load data analysis revealed only minimal price effects; and, though households subjected to information treatments seemed to have learned from these treatments, load data analysis again detected only minimal effects on load. Given the currently high hopes for behavioral intervention and residential TOU rates, these unexpected results require explanation. We suggest a number of possibilities and discuss some implications for TOU programs, and for understanding demand response behavior and approaches to experiments with TOU rates.

Lutzenhiser, Susan; Peters, Jane; Moezzi, Mithra; Woods, James

2009-08-12T23:59:59.000Z

176

Optimal Control of Residential Energy Storage Under Price Fluctuations  

E-Print Network (OSTI)

Abstract—An increasing number of retail energy markets exhibit price fluctuations and provide home users the opportunity to buy energy at lower than average prices. However, such cost savings are hard to realize in practice because they require human users to observe the price fluctuations and shift their electricity demand to low price periods. We propose to temporarily store energy of low price periods in a home battery and use it later to satisfy user demand when energy prices are high. This enables home users to save on their electricity bill by exploiting price variability without changing their consumption habits. We formulate the problem of minimizing the cost of energy storage purchases subject to both user demands and prices as a Markov Decision Process and show that the optimal policy has a threshold structure. We also use a numerical example to show that this policy can lead to significant cost savings, and we offer various directions for future research. Index Terms—Battery storage, dynamic pricing, dynamic programming, energy storage, threshold policy. I.

Nidhi Hegde; Laurent Massoulié; Theodoros Salonidis

2011-01-01T23:59:59.000Z

177

Customer reponse to day-ahead wholesale market electricity prices: Case study of RTP program experience in New York  

E-Print Network (OSTI)

March. Neenan, B. (1992) “Electricity A La Carte” ElectricPrice Responsive? ” The Electricity Journal 15(3): 52-59.ahead Wholesale Market Electricity Prices: Case Study of RTP

2004-01-01T23:59:59.000Z

178

Beyond the Price Effect in Time-of-Use Programs: Results from a Municipal Utility Pilot, 2007-2008  

E-Print Network (OSTI)

Demand Response in Electricity Markets and RecommendationsJ. 1985. “The Residential Electricity Time-of-Use PricingJ. 1985. “The Residential Electricity Time-of-Use Pricing

Lutzenhiser, Susan

2010-01-01T23:59:59.000Z

179

Two-Settlement Electric Power Markets with Dynamic-Price Contracts  

E-Print Network (OSTI)

.g., consumer-owned photovoltaic (PV) panels #12;5 Principal IRW Project Research Topics Dynamic retail/wholesale reliability and efficiency implications of integrating demand response resources as realized thru Top-owned distributed energy resources, such as photovoltaic (PV) generation & plug-in electric vehicles (PEV

Tesfatsion, Leigh

180

Rethinking Real Time Electricity Pricing  

E-Print Network (OSTI)

Most US consumers are charged a near-constant retail price for electricity, despite substantial hourly variation in the wholesale market price. This paper evaluates the .rst program to expose residential consumers to hourly ...

Allcott, Hunt

Note: This page contains sample records for the topic "dynamic pricing programs" 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

On the Use of Multi-dimensional Dynamic Logic Programming to Represent Societal Agents' Viewpoints  

Science Conference Proceedings (OSTI)

This paper explores the applicability of the new paradigm of Multi-dimensional Dynamic Logic Programming to represent an agent's view of the combination of societal knowledge dynamics. The representation of a dynamic society of agents is the core of ...

Joăo Alexandre Leite; José Júlio Alferes; Luís Moniz Pereira

2001-12-01T23:59:59.000Z

182

The Minimum Price Contract  

E-Print Network (OSTI)

A minimum price contract is one of many tools a marketer may use to better manage price and production risk while trying to achieve financial goals and objectives. This publication discusses the advantages and disadvantages involved in this marketing program and the situations when it can be used.

Waller, Mark L.; Amosson, Stephen H.; Welch, Mark; Dhuyvetter, Kevin C.

2008-10-17T23:59:59.000Z

183

Phillip Price  

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

Phillip Price Phil Price Sustainable Energy Systems Group Demand Response Research Center (DRRC) Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R2002 Berkeley CA 94720...

184

Gasoline Prices  

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

and diesel price estimates from the Energy Information Administration Understanding Gas Prices Photo of gasoline receipt What determines the cost of gasoline? What's the...

185

Residential Heating Oil Prices  

Gasoline and Diesel Fuel Update (EIA)

This chart highlights residential heating oil prices for the current and This chart highlights residential heating oil prices for the current and past heating season. As you can see, prices have started the heating season, about 40 to 50 cents per gallon higher than last year at this time. The data presented are from EIA's State Heating Oil and Propane Program. We normally collect and publish this data twice a month, but given the low stocks and high prices, we started tracking the prices weekly. These data will also be used to determine the price trigger mechanism for the Northeast Heating Oil Reserve. The data are published at a State and regional level on our web site. The slide is to give you some perspective of what is happening in these markets, since you probably will get a number of calls from local residents about their heating fuels bills

186

Essays on the household-level effects of house price growth  

E-Print Network (OSTI)

Constructing measures of house price variance . . . . 2.4.4Flip That House? House Price Dynamics and Housing InvestmentHouse Price Data . . . . . . . . . . . . . . . . . . . . .

Sitgraves, Claudia Ayanna

2009-01-01T23:59:59.000Z

187

Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S.  

E-Print Network (OSTI)

local-level wholesale energy market price dynamics and localare included. Energy factor market prices, the shape of theare included. Energy factor market prices, the shape of the

Jaffee, Dwight M.; Stanton, Richard; Wallace, Nancy E.

2010-01-01T23:59:59.000Z

188

Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S.  

E-Print Network (OSTI)

local-level wholesale energy market price dynamics and localare included. Energy factor market prices, the shape of theare included. Energy factor market prices, the shape of the

Jaffee, Dwight; Stanton, Richard; Wallace, Nancy

2012-01-01T23:59:59.000Z

189

Green Power Network: Top Ten Utility Green Pricing Programs, December 2001  

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

December 2001 December 2001 Customer Participants (as of December 2001) Rank Utility Program # of Participants 1 Los Angeles Department of Water and Power Green Power for a Green L.A. 87,0001 2 Xcel Energy (Colorado) WindSource 18,600 3 Sacramento Municipal Utility District Greenergy - All Renewables 14,200 4 Xcel Energy (Colorado) Renewable Energy Trust 10,900 5 Wisconsin Electric Power Company Energy for Tomorrow 10,700 6 PacifiCorp Blue Sky 7,300 7 Austin Energy GreenChoice 6,600 8 Portland General Electric Company Salmon Friendly Clean Wind Power 5,700 9 Wisconsin Public Service SolarWise for Schools 5,200 10 Tennessee Valley Authority Green Power Switch 4,9002 Source: NREL Notes: 1 About half of the total are low-income customers that receive existing renewables at no extra cost.

190

GEOGYN - a geological formation/drill string dynamics computer program  

DOE Green Energy (OSTI)

This paper describes the initial development phase of a finite element computer program, GEODYN, capable of simulating the three-dimensional transient, dynamic response of a polycrystalline diamond compact (PDC) bit interacting with a non-uniform formation. The ability of GEODYN to simulate response variations attributable to hole size, hole bottom surface shapes, and formation material non-uniformities is demonstrated. Planned developmental phases will address the detailed response of a bottom-hole assembly (BHA), a drill ahead (rock penetration and removal) simulation, and ultimately, the response of the entire string.

Caskey, B.

1984-09-16T23:59:59.000Z

191

Green Power Network: Top Ten Utility Green Pricing Programs, December 2005  

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

5 5 Green Power Program Renewable Energy Sales (as of December 2005) Rank Utility Resources Used Sales (kWh/year) Sales (Avg. MWa) 1 Austin Energy Wind, landfill gas 435,140,739 49.7 2 Portland General Electricb Existing geothermal and hydro, wind 339,577,170 38.8 3 PacifiCorpcd Wind, biomass, solar 234,163,591 26.7 4 Florida Power & Light Biomass, wind, solar 224,574,530 25.6 5 Sacramento Municipal Utility Districte Wind, landfill gas, small hydro, solar 195,081,504 22.3 6 Xcel Energyef Wind 147,674,000 16.9 7 National Gridghi Biomass, wind, small hydro, solar 127,872,457 14.6 8 Basin Electric Power Cooperative Wind 113,957,000 13.0 9 Puget Sound Energy Wind, solar, biogas 71,341,000 8.1 10 OG&E Electric Services Wind 63,591,526 7.3

192

Green Power Network: Top Ten Utility Green Pricing Programs, December 2004  

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

4 4 Green Power Program Renewable Energy Sales (as of December 2004) Rank Utility Resources Used Sales (kWh/year) Sales (Avg. MWa) 1 Austin Energy Wind, landfill gas, small hydro 334,446,101 38.2 2 Portland General Electricb Existing geothermal, wind, small hydro 262,142,564 29.9 3 PacifiCorpcd Wind, biomass,solar 191,838,079 21.9 4 Sacramento Municipal Utility Districte Landfill gas, wind, small hydro, solar 176,774,804 20.2 5 Xcel Energy Wind 137,946,000 15.7 6 National Gridfgh Biomass, wind, small hydro, solar 88,204,988 10.1 7 Los Angeles Department of Power & Water Wind and landfill gas 75,528,746 8.6 8 OG&E Electric Services Wind 56,672,568 6.5 9 Puget Sound Energy Wind, solar, biogas 46,110,000 5.3 10 We Energiese Landfill gas, wind, small hydro 40,906,410 4.7

193

Green Power Network: Top Ten Utility Green Pricing Programs, December 2006  

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

6 6 Green Power Program Renewable Energy Sales (as of December 2006) Rank Utility Resources Used Sales (kWh/year) Sales (Avg. MWa) 1 Austin Energy Wind, landfill gas 580,580,401 66.3 2 Portland General Electricb Existing geothermal and hydro, wind 432,826,408 49.4 3 Florida Power & Light Landfill gas, biomass, wind, solar 302,792,000 34.6 4 PacifiCorpcd Wind, biomass, solar 299,862,690 34.2 5 Xcel Energyef Wind 236,505,718 27.0 6 Basin Electric Power Cooperative Wind 217,427,000 24.8 7 Sacramento Municipal Utility Districte Wind, landfill gas,small hydro 216,476,278 24.7 8 National Gridghi Biomass, wind,small hydro, solar 156,447,869 17.9 9 OG&E Electric Services Wind 134,553,920 15.4 10 Puget Sound Energy Wind, solar, biogas 131,742,000 15.0

194

Time Series Forecasting for Dynamic Environments: the DyFor Genetic Program Model  

E-Print Network (OSTI)

Time Series Forecasting for Dynamic Environments: the DyFor Genetic Program Model Neal Wagner programming (GP) to the task of forecasting with favorable results. However, these studies, like those "dynamic" GP model that is specifically tailored for forecasting in non-static environments. This Dynamic

Michalewicz, Zbigniew

195

Natural Gas Citygate Price  

Annual Energy Outlook 2012 (EIA)

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross...

196

Cheese Prices  

E-Print Network (OSTI)

Cheese prices are derived from the USDA Agricultural Marketing Service Market News, the National Agricultural Statistics Service, and the Chicago Mercantile Exchange. This publication explains the process of cheese pricing. It includes information on hauling rates and freight differentials

Schwart Jr., Robert B.; Anderson, David P.; Knutson, Ronald D.

2003-08-25T23:59:59.000Z

197

Sarah Price  

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

Sarah K Price Sarah Price Energy Efficiency Standards Group Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R4000 Berkeley CA 94720 Office Location: 90-4128B (510)...

198

Marisa Price  

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

Marisa Dawn Price Marisa Price Communications Office Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R3029B Berkeley CA 94720 Office Location: 90-2056B (510) 495-2713...

199

Approximate Dynamic Programming Solutions for Lean Burn Engine Aftertreatment  

E-Print Network (OSTI)

The competition to deliver fuel e#cient and environmentally friendly vehicles is driving the automotive industry to consider ever more complex powertrain systems. Adequate performance of these new highly interactive systems can no longer be obtained through traditional approaches, which are intensive in hardware use and #nal control software calibration. This paper explores the use of dynamic programming to make model-based design decisions for a lean burn, direct injection spark ignition engine, in combination with a three way catalyst and lean NOx trap aftertreatment system. The primary contribution is the development ofavery rapid method to evaluate the tradeo#s in fuel economy and emissions for this novel powertrain system, as a function of design parameters and controller structure, over a standard emission test cycle. 1 Introduction Designing a powertrain system to meet drivability, fuel economy and emissions performance requirements is a complicated task. There are many tradeo...

Jun-Mo Kang; Ilya Kolmanovsky; J.W. Grizzle

1999-01-01T23:59:59.000Z

200

Finding genes in DNA using decision trees and dynamic programming  

E-Print Network (OSTI)

{ salz berg,xchendhndrsn}:~cs.jhu.edu,kewf~gdb.org This study demonstrates the use of decision tree classifiers as the basis for a general gene-finding system. The system uses a dynamic programming algorithm that. finds the optimal segmentation of a DNA sequence into coding and noncoding regions (exons and introits).]’he optimality property is dependent oll a separate scoring function that takes a subsequence and assigns to it a score reflecting the probability that the sequence is an exon. In this study, the scoring functions were sets of decision trees and rules that were combined to give the probability estimate. Experimental results on a newly collected database of human DNA sequences are encouraging, and some new observations about the structure of classifiers for tile gene-finding problem have emerged from this study. We also provide descriptions of a new probability chain model that produces very accurate filters to find donor and acceptor sites.

Steven Salzberg; Xin Chen; John Henderson; Kenneth Fasman

1996-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Winter Residential Heating Oil Prices  

Gasoline and Diesel Fuel Update (EIA)

7 7 Notes: Residential heating oil prices reflect a similar pattern to that shown in spot prices. However, like other retail petroleum prices, they tend to lag changes in wholesale prices in both directions, with the result that they don't rise as rapidly or as much, but they take longer to recede. This chart shows the residential heating oil prices collected under the State Heating Oil and Propane Program (SHOPP), which only runs during the heating season, from October through March. The spike in New York Harbor spot prices last winter carried through to residential prices throughout New England and the Central Atlantic states. Though the spike actually lasted only a few weeks, residential prices ended the heating season well above where they had started.

202

Gas Prices  

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

Prices Gasoline Prices for U.S. Cities Click on the map to view gas prices for cities in your state. AK VT ME NH NH MA MA RI CT CT DC NJ DE DE NY WV VA NC SC FL GA AL MS TN KY IN...

203

Need-based Communication for Smart Grid: When to Inquire Power Price?  

E-Print Network (OSTI)

In smart grid, a home appliance can adjust its power consumption level according to the realtime power price obtained from communication channels. Most studies on smart grid do not consider the cost of communications which cannot be ignored in many situations. Therefore, the total cost in smart grid should be jointly optimized with the communication cost. In this paper, a probabilistic mechanism of locational margin price (LMP) is applied and a model for the stochastic evolution of the underlying load which determines the power price is proposed. Based on this framework of power price, the problem of determining when to inquire the power price is formulated as a Markov decision process and the corresponding elements, namely the action space, system state and reward function, are defined. Dynamic programming is then applied to obtain the optimal strategy. A simpler myopic approach is proposed by comparing the cost of communications and the penalty incurred by using the old value of power price. Numerical resul...

Li, Husheng

2010-01-01T23:59:59.000Z

204

Dynamic Line Rating Oncor Electric Delivery Smart Grid Program  

Science Conference Proceedings (OSTI)

Electric transmission lines are the lifeline of the electric utility industry, delivering its product from source to consumer. This critical infrastructure is often constrained such that there is inadequate capacity on existing transmission lines to efficiently deliver the power to meet demand in certain areas or to transport energy from high-generation areas to high-consumption regions. When this happens, the cost of the energy rises; more costly sources of power are used to meet the demand or the system operates less reliably. These economic impacts are known as congestion, and they can amount to substantial dollars for any time frame of reference: hour, day or year. There are several solutions to the transmission constraint problem, including: construction of new generation, construction of new transmission facilities, rebuilding and reconductoring of existing transmission assets, and Dynamic Line Rating (DLR). All of these options except DLR are capital intensive, have long lead times and often experience strong public and regulatory opposition. The Smart Grid Demonstration Program (SGDP) project co-funded by the Department of Energy (DOE) and Oncor Electric Delivery Company developed and deployed the most extensive and advanced DLR installation to demonstrate that DLR technology is capable of resolving many transmission capacity constraint problems with a system that is reliable, safe and very cost competitive. The SGDP DLR deployment is the first application of DLR technology to feed transmission line real-time dynamic ratings directly into the system operation’s State Estimator and load dispatch program, which optimizes the matching of generation with load demand on a security, reliability and economic basis. The integrated Dynamic Line Rating (iDLR)1 collects transmission line parameters at remote locations on the lines, calculates the real-time line rating based on the equivalent conductor temperature, ambient temperature and influence of wind and solar radiation on the stringing section, transmits the data to the Transmission Energy Management System, validates its integrity and passes it on to Oncor and ERCOT (Electric Reliability Council of Texas) respective system operations. The iDLR system is automatic and transparent to ERCOT System Operations, i.e., it operates in parallel with all other system status telemetry collected through Supervisory Control and Data Acquisition (SCADA) employed across the company.

Johnson, Justin; Smith, Cale; Young, Mike; Donohoo, Ken; Owen, Ross; Clark, Eddit; Espejo, Raul; Aivaliotis, Sandy; Stelmak, Ron; Mohr, Ron; Barba, Cristian; Gonzalez, Guillermo; Malkin, Stuart; Dimitrova, Vessela; Ragsdale, Gary; Mitchem, Sean; Jeirath, Nakul; Loomis, Joe; Trevino, Gerardo; Syracuse, Steve; Hurst, Neil; Mereness, Matt; Johnson, Chad; Bivens, Carrie

2013-05-04T23:59:59.000Z

205

On the global economic potentials and marginal costs of non-renewable resources and the price dynamics of energy commodities  

E-Print Network (OSTI)

A model is presented in this work for simulating endogenously the evolution of the marginal costs of production of energy carriers from non-renewable resources, their consumption, depletion pathways and timescales. Such marginal costs can be used to simulate the long term average price formation of energy commodities. Drawing on previous work where a global database of energy resource economic potentials was constructed, this work uses cost distributions of non-renewable resources in order to evaluate global flows of energy commodities. A mathematical framework is given to calculate endogenous flows of energy resources given an exogenous commodity price path. This framework can be used in reverse in order to calculate an exogenous marginal cost of production of energy carriers given an exogenous carrier demand. Using rigid price inelastic assumptions independent of the economy, these two approaches generate limiting scenarios that depict extreme use of natural resources. This is useful to characterise the cur...

Mercure, Jean-Francois

2013-01-01T23:59:59.000Z

206

Plutonium Certified Reference Materials Price List | U.S. DOE...  

Office of Science (SC) Website

Plutonium Certified Reference Materials Price List New Brunswick Laboratory (NBL) NBL Home About Programs Certified Reference Materials Prices and Certificates Ordering Information...

207

When the price is right: enabling time-dependent pricing of broadband data  

Science Conference Proceedings (OSTI)

In an era of 108% annual growth in demand for mobile data and $10/GB overage fees, Internet Service Providers (ISPs) are experiencing severe congestion and in turn are hurting consumers with aggressive pricing measures. But smarter practices, such as ... Keywords: broadband access pricing, dynamic pricing, economics, mobile application interface, time- and usage-based pricing

Soumya Sen, Carlee Joe-Wong, Sangtae Ha, Jasika Bawa, Mung Chiang

2013-04-01T23:59:59.000Z

208

Price Elasticity of Demand for Electricity: A Primer and Synthesis  

Science Conference Proceedings (OSTI)

The results of recent real-time pricing (RTP) and critical peak pricing (CPP) pilots demonstrate resoundingly that consumers can and will adjust electricity usage in response to price changes. Nonetheless, dynamic pricing plans are still novelties, in part because policy makers and pricing plan designers are equally skeptical of the impact of large-scale implementation. There is no consensus on the degree to which consumers will respond to price changes and as a result no concurrence on which pricing pla...

2008-01-17T23:59:59.000Z

209

The Cross-Section of Output and Inflation in a Dynamic Stochastic General Equilibrium Model with Sticky Prices  

E-Print Network (OSTI)

?cant Di¤erences to Economic Equilibria, American Economic Review, Vol. 75, pp 708-721. [2] Ball, L. Mankiw, N. G. (1994) Asymmetric Price Adjustment and Economic Fluc- tuations", The Economic Journal, Vol. 104, No. 423, March, pages 247-261. [3] Ball, L...

Döpke, J; Funke, M.; Holly, Sean; Weber, S

210

Applications of flexible pricing in business-to-business electronic commerce  

Science Conference Proceedings (OSTI)

The increasingly dynamic nature of business-to-business electronic commerce has produced a recent shift away from fixed pricing and toward flexible pricing. Flexible pricing, as defined here, includes both differential pricing, in which different buyers ...

M. Bichler; J. Kalagnanam; K. Katircioglu; A. J. King; R. D. Lawrence; H. S. Lee; G. Y. Lin; Y. Lu

2002-04-01T23:59:59.000Z

211

A Threshold Autoregressive Model for Wholesale Electricity Prices  

E-Print Network (OSTI)

A Threshold Autoregressive Model for Wholesale Electricity Prices B. Ricky Rambharat Carnegie model; electricity prices; spikes; Markov chain Monte Carlo. 1. Introduction The dynamics of electricity of electricity price dynamics is essential for pricing and hedging financial futures and options on power

212

Lynn Price  

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

Lynn Price Lynn Price China Energy Group Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R2002 Berkeley CA 94720 Office Location: 90-2108 (510) 486-6519 LKPrice@lbl.gov Lynn Price is a Staff Scientist and Leader of the China Energy Group of the Energy Analysis and Environmental Impacts Department, Environmental Energy Technologies Division, of Lawrence Berkeley National Laboratory. Ms. Price has a MS in Environmental Science from the University of Wisconsin-Madison and has worked at LBNL since 1990. Ms. Price has been a member of the Intergovernmental Panel on Climate Change, which won the Nobel Peace Prize in 2007, since 1994 and was an author on the industrial sector chapter of IPCC's Fourth Assessment Report on Mitigation of Climate Change. Since 1999, Ms. Price has provided technical assistance to the Energy

213

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

214

Stephanie Price  

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

Stephanie Price is a communicator at the National Renewable Energy Laboratory, which assists EERE in providing technical content for many of its websites.

215

PRICE SPECULATION  

E-Print Network (OSTI)

The price of crude oil in the U.S. had never exceeded $40 per barrel until mid-2004. By 2006 it reached $70 per barrel, and in July 2008 it reached a peak of $145. By the end of 2008 it had plummeted to about $30 before increasing again, reaching about $110 in 2011. Are “speculators ” to blame for at least part of the volatility and sharp run-ups in price? We clarify the potential and actual effects of speculators, and investors in general, on commodity prices. We focus on crude oil, but our approach can be applied to other commodities. We first address the question of what is meant by “oil price speculation, ” and how it relates to investments in oil reserves, oil inventories, or oil price derivatives (such as futures contracts). Next we outline the ways in which one could speculate on oil prices. Finally, we turn to the data, and calculate counterfactual prices that would have occurred from 1999 to 2012 in the absence of speculation. Our framework is based on a simple and transparent model of supply and demand in the cash and storage markets for a commodity. It lets us determine whether speculation as the driver of price changes is consistent with the data on production, consumption, inventory changes, and changes in convenience yields given reasonable elasticity assumptions. We show speculation had little, if any, effect on prices and volatility.

Christopher R. Knittel; Robert S. Pindyck; Christopher R. Knittel; Robert S. Pindyck

2013-01-01T23:59:59.000Z

216

Snuller Price  

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

Snuller Price Energy and Environmental Economics NOTICE Due to the current lapse of federal funding, Berkeley Lab websites are accessible, but may not be updated until Congress...

217

Geological formation - drill string dynamic interaction finite-element program (GEODYN). Phase 1. Theoretical description  

DOE Green Energy (OSTI)

The Theoretical Description for the GEODYN interactive finite-element computer program is presented. The program is capable of performing the analysis of the three-dimensional transient dynamic response of a Polycrystalline Diamond Compact Bit-Bit Sub arising from the intermittent contact of the bit with the downhole rock formations. The program accommodates nonlinear, time-dependent, loading and boundary conditions.

Baird, J.A.; Apostal, M.C.; Rotelli, R.L. Jr.; Tinianow, M.A.; Wormley, D.N.

1984-06-01T23:59:59.000Z

218

Phase 1 user instruction manual. A geological formation - drill string dynamic interaction finite element program (GEODYN)  

DOE Green Energy (OSTI)

User instructions for the GEODYN Interactive Finite Element Computer Program are presented. The program is capable of performing the analysis of the three-dimensional transient dynamic response of a Polycrystalline Diamond Compact Bit - Bit Sub arising from the intermittent contact of the bit with the downhole rock formations. The program accommodates non-linear, time dependent, loading and boundary conditions.

Tinianow, M.A.; Rotelli, R.L. Jr.; Baird, J.A.

1984-06-01T23:59:59.000Z

219

Essays on Three Price Judgments: Price Fairness, Price Magnitude, and Price Expectation.  

E-Print Network (OSTI)

??This dissertation addresses three important price judgments: price fairness, price magnitude, and price expectation. Developed over three chapters, the main objective of this research is… (more)

Bhowmick, Sandeep

2010-01-01T23:59:59.000Z

220

Green Power Network: Green Pricing  

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

Table of Utility Programs by State Table of Utility Programs by State List of Utilities Offering Green Power Top Ten Utility Green Power Programs Green Power Marketing Green Certificates Carbon Offsets State Policies Green Pricing Green pricing is an optional utility service that allows customers an opportunity to support a greater level of utility company investment in renewable energy technologies. Participating customers pay a premium on their electric bills to cover the incremental cost of the additional renewable energy. To date, more than 860 utilities, including investor-owned, municipal utilities, and cooperatives, offer a green pricing option. Table of Utility Programs by State List of Utilities Offering Green Power Top Ten Utility Green Power Programs National Green Pricing Map

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Price Server System for Automated Critical Peak Pricing  

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

Price Server System for Automated Critical Peak Pricing Price Server System for Automated Critical Peak Pricing Speaker(s): David S. Watson Date: June 3, 2005 - 12:00pm Location: 90-3148 Overview of current California Energy Commission (CEC)/Demand Response Research Center (DRRC) Auto-CPP project: This summer, some select commercial CPP customers of PG&E will have the option of joining the Automated Critical Peak Pricing pilot. The pilot will have the same tariffs as standard CPP programs, but will include an added feature: automated shedding of electric loads. Through use of the Price Server System, day-ahead CPP event signals initiated by PG&E will ultimately cause electric loads to be automatically curtailed on commercial customer sites. These optional predetermined shed strategies will occur without

222

A sniffer technique for an efficient deduction of model dynamical equations using genetic programming  

Science Conference Proceedings (OSTI)

A novel heuristic technique that enhances the search facility of the standard genetic programming (GP) algorithm is presented. The method provides a dynamic sniffing facility to optimize the local search in the vicinity of the current best chromosomes ...

Dilip P. Ahalpara; Abhijit Sen

2011-04-01T23:59:59.000Z

223

Lynn Price  

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

Lynn Price China Energy Group Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R2002 Berkeley CA 94720 Office Location: 90-2108 (510) 486-6519 LKPrice@lbl.gov NOTICE Due...

224

Snuller Price  

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

Snuller Price Energy and Environmental Economics This speaker was a visiting speaker who delivered a talk or talks on the date(s) shown at the links below. This speaker is not...

225

PRICE GOUGING  

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

home heating costs? How will those be affected? With an overall increase in the price of heating oil and natural gas, we expect that there may be an increase in home heating costs...

226

Phillip Price  

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

90-2006 (510) 486-7875 PNPrice@lbl.gov Dr. Phillip Price has a Ph.D. in physics from the University of Kentucky, and has worked in the Indoor Environment Department since 1992. In...

227

Customer reponse to day-ahead wholesale market electricity prices: Case study of RTP program experience in New York  

E-Print Network (OSTI)

Statewide Participation in NYISO Demand Response Programs:SC-3A Peak Period Demand Response: Shifting Only andDemand Response .

2004-01-01T23:59:59.000Z

228

Improving the Performance of Stochastic Dual Dynamic Programming  

E-Print Network (OSTI)

Jul 10, 2012 ... This gives an order of magnitude decrease in computation time with little change in solution quality. Keywords: stochastic programming ...

229

Estimating Large-Customer Demand Response Market Potential: Integrating Price and Customer Behavior  

E-Print Network (OSTI)

and 2006) ISO-NE Real-Time Price Response (RTPR) ProgramResponse to Real Time Electricity Prices”, December,real-time energy market) Short-notice emergency program Price-

Goldman, Charles; Hopper, Nicole; Bharvirkar, Ranjit; Neenan, Bernie; Cappers, Peter

2007-01-01T23:59:59.000Z

230

SF 6432-LA Fixed Price Latin America  

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

CORPORATION SF 6432-LA (072013) SECTION II STANDARD TERMS AND CONDITIONS FOR FIXED PRICE CONTRACTS RENEWABLE ENERGY PROGRAMS IN LATIN AMERICAN COUNTRIES THE FOLLOWING CLAUSES...

231

Real-time Pricing Demand Response in Operations  

Science Conference Proceedings (OSTI)

Abstract—Dynamic pricing schemes have been implemented in commercial and industrial application settings, and recently they are getting attention for application to residential customers. Time-of-use and critical-peak-pricing rates are in place in various regions and are being piloted in many more. These programs are proving themselves useful for balancing energy during peak periods; however, real-time (5 minute) pricing signals combined with automation in end-use systems have the potential to deliver even more benefits to operators and consumers. Besides system peak shaving, a real-time pricing system can contribute demand response based on the locational marginal price of electricity, reduce load in response to a generator outage, and respond to local distribution system capacity limiting situations. The US Department of Energy (DOE) is teaming with a mid-west electricity service provider to run a distribution feeder-based retail electricity market that negotiates with residential automation equipment and clears every 5 minutes, thus providing a signal for lowering or raising electric consumption based on operational objectives of economic efficiency and reliability. This paper outlines the capability of the real-time pricing system and the operational scenarios being tested as the system is rolled-out starting in the first half of 2012.

Widergren, Steven E.; Marinovici, Maria C.; Berliner, Teri; Graves, Alan

2012-07-26T23:59:59.000Z

232

October 2009Rethinking Real Time Electricity Pricing  

E-Print Network (OSTI)

Most US consumers are charged a near-constant retail price for electricity, despite substantial hourly variation in the wholesale market price. This paper evaluates the …rst program to expose residential consumers to hourly real time pricing (RTP). I …nd that enrolled households are statistically signi…cantly price elastic and that consumers responded by conserving energy during peak hours, but remarkably did not increase average consumption during o¤-peak times. Welfare analysis suggests that program households were not su ˘ ciently price elastic to generate e ˘ ciency gains that substantially outweigh the estimated costs of the advanced electricity meters required to observe hourly consumption. Although in electricity pricing, congestion pricing, and many other settings, economists’intuition is that prices should be aligned with marginal costs, residential RTP may provide an important real-world example of a situation where this is not currently welfare-enhancing given contracting or information costs.

Hunt Allcott; Hunt Allcott; Bill Hogan; Erich Muehlegger; Larry Katz; Erin Mansur; Sendhil Mullainathan; Paul Niehaus; Chris Nosko; Ariel Pakes; Dave Rapson; Rob Stavins; Frank Wolak

2009-01-01T23:59:59.000Z

233

SF 6432-LA Standard Terms and Conditions for Fixed Price Contracts Established Under the Renewable Energy Programs in Latin American Countries  

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

SF 6432-LA (04-95) SECTION II STANDARD TERMS AND CONDITIONS FOR FIXED PRICE CONTRACTS ESTABLISHED UNDER THE RENEWABLE ENERGY PROGRAMS IN LATIN AMERICAN COUNTRIES INDEX OF CLAUSES THE FOLLOWING CLAUSES APPLY TO REQUESTS FOR QUOTATION AND CONTRACTS AS INDICATED UNLESS SPECIFICALLY DELETED, OR EXCEPT TO THE EXTENT THEY AERE SPECIFICALLY SUPPLEMENTED OR AMENDED IN WRITING IN THE SIGNATURE PAGE OR SECTION I. No. Title Page "A" Clauses apply to Requests for Quotation and Contracts at any value for work performed A10 Definitions 2 A11 Unclassified Contract 2 A12 Assignment 2 *A13 Releases Void 2 *A14 Notice of Labor Disputes 2 A17 Delegated Representatives 2 A19 Terms and Conditions 2 *A20 Permits 2 *A23 Applicable Law 2 *A26 Officials Not to Benefit (FAR 52.203-1

234

Dynamic programming for constrained optimal control of discrete-time linear hybrid systems  

Science Conference Proceedings (OSTI)

In this paper we study the solution to optimal control problems for constrained discrete-time linear hybrid systems based on quadratic or linear performance criteria. The aim of the paper is twofold. First, we give basic theoretical results on the structure ... Keywords: Dynamic programming, Hybrid systems, Multiparametric programming, Optimal control, Piecewise affine systems

Francesco Borrelli; Mato Baoti?; Alberto Bemporad; Manfred Morari

2005-10-01T23:59:59.000Z

235

A NONGAUSSIAN ORNSTEINUHLENBECK PROCESS FOR ELECTRICITY SPOT PRICE MODELING AND  

E-Print Network (OSTI)

A NON­GAUSSIAN ORNSTEIN­UHLENBECK PROCESS FOR ELECTRICITY SPOT PRICE MODELING AND DERIVATIVES for analytical pricing of electricity forward and futures contracts. Electricity forward and futures contracts to capture the observed dynamics of electricity spot prices. We also discuss the pricing of European call

Kallsen, Jan

236

Crude Oil Affects Gasoline Prices  

U.S. Energy Information Administration (EIA)

Crude Oil Affects Gasoline Prices. WTI Crude Oil Price. Retail Gasoline Price. Source: Energy Information Administration

237

Dynamic Decision-Making in Logic Programming and Game Theory  

Science Conference Proceedings (OSTI)

We present a framework for decision making with circumstance-dependent preferences and decisions. This formalism, called Ordered Choice Logic Programming, allows decisions that comprise multiple alternatives, which become available only when a choice ...

Marina De Vos; Dirk Vermeir

2002-12-01T23:59:59.000Z

238

Aspects of Poincaré's Program for Dynamical Systems and Mathematical Physics  

Science Conference Proceedings (OSTI)

This article is mainly historical, except for the discussion of integrability and characteristic exponents in Sect. 2. After summarising the achievements of Henri Poincaré, we discuss his theory of critical exponents. The theory is applied to the ... Keywords: Characteristic exponents, Dynamical systems, Henri Poincaré, Relativity, Rotating fluids

Ferdinand Verhulst

2012-08-01T23:59:59.000Z

239

SRM Pricing Policy  

Science Conference Proceedings (OSTI)

... rates are used to calculate the price for each ... Therefore, prices for new lots and renewal issues of ... changed, all SRMs may be re-priced taking into ...

2012-11-16T23:59:59.000Z

240

Pennsylvania Gasoline Price Data  

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

- GasBuddy.com Pennsylvania Gas Prices (selected cities) - GasBuddy.com Pennsylvania Gas Prices (organized by county) - Automotive.com Gas Prices of the United States:...

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Demand Reductions from the Application of Advanced Metering Infrastructure, Pricing Programs, and Customer-Based Systems - Intial Results  

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

U.S. Department of Energy | December 2012 Table of Contents Executive Summary ................................................................................................................. ii 1. Introduction ..................................................................................................................... 1 1.1 Purpose and Scope.................................................................................................... 1 1.2 Organization of this Report....................................................................................... 3 2. Overview of Demand-Side Devices, Systems, Programs, and Expected Benefits ............... 4 2.1 Communications Networks Associated with AMI .................................................... 4

242

Prices & Trends  

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

The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment. Learn about EIA and Energy Department organizations that track energy prices and trends.

243

A Time Series Analysis of Food Price and Its Input Prices  

E-Print Network (OSTI)

Rapid increases in consumer food price beginning in 2007 generated interest in identifying the main factors influencing these increases. In subsequent years, food prices have fluctuated, but generally have continued their ascent. The effects of crude oil, gasoline, corn, and ethanol prices, as well as, the relative foreign exchange rate of the U.S. dollar and producer price indexes for food manufacturing and fuel products on domestic food prices are examined. Because the data series are non-stationary and cointegrated, a vector error correction model is estimated. Weak exogeneity and exclusion tests in the cointegration space are performed. Directed acyclical graphs are used to specify contemporaneous causal relationships. Dynamic interactions among the series are given by impulse response functions and forecast error variance decompositions. Weak exogeneity tests indicate all eight series work to bring the system back into equilibrium following a shock to the system. Further, exclusion tests suggest crude oil, gasoline, food CPI, ethanol, and food PPI variables are not in the long-run relationships. Dynamic analyses suggest the following relationships. Ethanol price is not a major factor in domestic food prices, suggesting that food prices are largely unaffected by the recent increased use of corn-based ethanol for fuel. Crude oil prices, corn prices, and the relative foreign exchange rate of the U.S. dollar, however, do influence domestic food prices with corn price contributing the most to food price variability. Innovation accounting inferences are robust to potential different contemporaneous causal specifications.

Routh, Kari 1988-

2012-12-01T23:59:59.000Z

244

Understanding Crude Oil Prices  

E-Print Network (OSTI)

2004. “OPEC’s Optimal Crude Oil Price,” Energy Policy 32(2),percent change in real oil price. Figure 3. Price of crude023 Understanding Crude Oil Prices James D. Hamilton June

Hamilton, James Douglas

2008-01-01T23:59:59.000Z

245

On the stability of wholesale electricity markets under real-time pricing  

E-Print Network (OSTI)

The paper proposes a mathematical model for the dynamic evolution of supply, demand, and clearing prices under a class of real-time pricing mechanisms characterized by passing on the real-time wholesale prices to the end ...

Roozbehani, Mardavij

246

Average Commercial Price  

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

Residential Price Average Commercial Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes...

247

International Price List | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

International Price List New Brunswick Laboratory (NBL) NBL Home About Programs Certified Reference Materials Prices and Certificates Ordering Information Training New Brunswick...

248

Domestic Price List | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

Domestic Price List New Brunswick Laboratory (NBL) NBL Home About Programs Certified Reference Materials Prices and Certificates Ordering Information Training New Brunswick...

249

Uranium Certified Reference Materials Price List | U.S. DOE Office...  

Office of Science (SC) Website

Certified Reference Materials Price List New Brunswick Laboratory (NBL) NBL Home About Programs Certified Reference Materials Prices and Certificates Ordering Information Training...

250

Uranium and Thorium Ores Price List | U.S. DOE Office of Science...  

Office of Science (SC) Website

and Thorium Ores Price List New Brunswick Laboratory (NBL) NBL Home About Programs Certified Reference Materials Prices and Certificates Ordering Information Training New Brunswick...

251

Research on water level optimal control of boiler drum based on dual heuristic dynamic programming  

Science Conference Proceedings (OSTI)

Boiler drum system is an important component of a thermal power plant or industrial production, and the water level is a critical parameter of boiler drum control system. Because of non-linear, strong coupling and large disturbance, it is difficult to ... Keywords: BP neural network, boiler drum level, dual heuristic dynamic programming, optimal control

Qingbao Huang; Shaojian Song; Xiaofeng Lin; Kui Peng

2011-05-01T23:59:59.000Z

252

Solving the job-shop scheduling problem optimally by dynamic programming  

Science Conference Proceedings (OSTI)

Scheduling problems received substantial attention during the last decennia. The job-shop problem is a very important scheduling problem, which is NP-hard in the strong sense and with well-known benchmark instances of relatively small size which attest ... Keywords: Complexity analysis, Dynamic programming, Job-shop scheduling

Joaquim A. S. Gromicho; Jelke J. Van Hoorn; Francisco Saldanha-Da-Gama; Gerrit T. Timmer

2012-12-01T23:59:59.000Z

253

The optimization of the stocks within coal power stations using the dynamic programming method  

Science Conference Proceedings (OSTI)

The purpose of this paper is to devise an economic and mathematical model for forecasting and optimizing the need of coal, for determining the current stock size and optimizing the supply-storage costs within a coal-fired power plant. The conditions ... Keywords: continuous flow production, dynamic programming method, energetic resources, optimization of the safety stock, power plants, stock analysis

Rascolean Ilie; Isac Claudia; Dura Codruta

2009-12-01T23:59:59.000Z

254

An Approximate Dynamic Programming Algorithm for Large-Scale Fleet Management: A Case Application  

Science Conference Proceedings (OSTI)

We addressed the problem of developing a model to simulate at a high level of detail the movements of over 6,000 drivers for Schneider National, the largest truckload motor carrier in the United States. The goal of the model was not to obtain a better ... Keywords: approximate dynamic programming, driver management, fleet management, truckload trucking

Hugo P. Simăo; Jeff Day; Abraham P. George; Ted Gifford; John Nienow; Warren B. Powell

2009-05-01T23:59:59.000Z

255

A simulation-and-regression approach for stochastic dynamic programs with endogenous state variables  

Science Conference Proceedings (OSTI)

We investigate the optimum control of a stochastic system, in the presence of both exogenous (control-independent) stochastic state variables and endogenous (control-dependent) state variables. Our solution approach relies on simulations and regressions ... Keywords: Approximate dynamic programming, Hydropower management, Least-squares Monte Carlo, Simulation and regression, Stochastic control

Michel Denault, Jean-Guy Simonato, Lars Stentoft

2013-11-01T23:59:59.000Z

256

Essays on pricing under uncertainty  

E-Print Network (OSTI)

This dissertation analyzes pricing under uncertainty focusing on the U.S. airline industry. It sets to test theories of price dispersion driven by uncertainty in the demand by taking advantage of very detailed information about the dynamics of airline prices and inventory levels as the flight date approaches. Such detailed information about inventories at a ticket level to analyze airline pricing has been used previously by the author to show the importance of capacity constraints in airline pricing. This dissertation proposes and implements many new ideas to analyze airline pricing. Among the most important are: (1) It uses information about inventories at a ticket level. (2) It is the first to note that fare changes can be explained by adding dummy variables representing ticket characteristics. Therefore, the load factor at a ticket level will lose its explanatory power on fares if all ticket characteristics are included in a pricing equation. (3) It is the first to propose and implement a measure of Expected Load Factor as a tool to identify which flights are peak and which ones are not. (4) It introduces a novel idea of comparing actual sales with average sales at various points prior departure. Using these deviations of actual sales from sales under average conditions, it presents is the first study to show empirical evidence of peak load pricing in airlines. (5) It controls for potential endogeneity of sales using dynamic panels. The first essay tests the empirical importance of theories that explain price dispersion under costly capacity and demand uncertainty. The essay calculates a measure of an Expected Load Factor, that is used to calibrate the distribution of demand uncertainty and to identify which flights are peak and which ones are off-peak. It shows that different prices can be explained by the different selling probabilities. The second essay is the first study to provide formal evidence of stochastic peak-load pricing in airlines. It shows that airlines learn about the demand and respond to early sales setting higher prices when expected demand is high and more likely to exceed capacity.

Escobari Urday, Diego Alfonso

2008-05-01T23:59:59.000Z

257

WORKING PAPER SERIESFEDERAL RESERVE BANK of ATLANTA WORKING PAPER SERIES Crude Substitution: The Cyclical Dynamics of Oil Prices and the Skill Premium  

E-Print Network (OSTI)

Abstract: Higher oil-price shocks benefit unskilled workers relative to skilled workers: At the businesscycle frequency, energy prices and the skill premia display a strong, negative correlation. We assess the robustness of this negative correlation using several methods and data sources, including sector-level data. We find that the negative correlation is robust to different de-trending procedures, and the wages of unskilled workers in energy-intensive industries have a larger positive correlation with oil prices. We also estimate the parameters of an aggregate technology, which uses, among other inputs, energy and heterogeneous skills. We find that both capital-skill and capital-energy complementarity are responsible for this correlation pattern. As energy prices rise, the use of capital decreases and the demand for unskilled labor relative to skilled labor increases, resulting in lower skill premia. JEL classification: E24, E32, J24 Key words: skill heterogeneity, energy prices, business cycles, capital-skill complementarity

Linnea Polgreen; Pedro Silos; Linnea Polgreen; Pedro Silos; Nir Jaimovich; Karsten Jeske; Jim Nason; B. Ravikumar; Víctor Ríos-rull; Ellis Tallman; Robert Tamura

2008-01-01T23:59:59.000Z

258

OIL PRICES AND LONG-RUN RISK  

E-Print Network (OSTI)

I show that relative levels of aggregate consumption and personal oil consumption provide an excellent proxy for oil prices, and that high oil prices predict low future aggregate consumption growth. Motivated by these facts, I add an oil consumption good to the long-run risk model of Bansal and Yaron [2004] to study the asset pricing implications of observed changes in the dynamic interaction of consumption and oil prices. Empirically I observe that, compared to the first half of my 1987- 2010 sample, oil consumption growth in the last 10 years is unresponsive to levels of oil prices, creating an decrease in the mean-reversion of oil prices, and an increase in the persistence of oil price shocks. The model implies that the change in the dynamics of oil consumption generates increased systematic risk from oil price shocks due to their increased persistence. However, persistent oil prices also act as a counterweight for shocks to expected consumption growth, with high expected growth creating high expectations of future oil prices which in turn slow down growth. The combined effect is to reduce overall consumption risk and lower the equity premium. The model also predicts that these changes affect the riskiness of of oil futures contracts, and combine to create a hump shaped

Robert Ready; Robert Clayton Ready; Robert Clayton Ready; Amir Yaron

2011-01-01T23:59:59.000Z

259

Solar Pilot Plant, Phase I. Preliminary design report. Volume II, Book 3. Dynamic simulation model and computer program descriptions. CDRL item 2. [SPP dynamics simulation program  

DOE Green Energy (OSTI)

The mathematical models and computer program comprising the SPP Dynamic Simulation are described. The SPP Dynamic Simulation is a computerized model representing the time-varying performance characteristics of the SPP. The model incorporates all the principal components of the pilot plant. Time-dependent direct normal solar insulation, as corrupted by simulated cloud passages, is transformed into absorbed radiant power by actions of the heliostat field and enclosed receiver cavity. The absorbed power then drives the steam generator model to produce superheated steam for the turbine and/or thermal storage subsystems. The thermal storage subsystem can, in turn, also produce steam for the turbine. The turbine using the steam flow energy produces the mechanical shaft power necessary for the generator to convert it to electrical power. This electrical power is subsequently transmitted to a transmission grid system. Exhaust steam from the turbine is condensed, reheated, deaerated, and pressurized by pumps for return as feedwater to the thermal storage and/or steam generator. A master control/instrumentation system is utilized to coordinate the various plant operations. The master controller reacts to plant operator demands and control settings to effect the desired output response. The SPP Dynamic Simulation Computer program is written in FORTRAN language. Various input options (e.g., insolation values, load demands, initial pressures/temperatures/flows) are permitted. Plant performance may be monitored via computer printout or computer generated plots. The remainder of this document describes the detailed pilot plant dynamic model, the basis for this simulation, and the utilization of this simulation to obtain analytical plant performance results.

None

1977-05-01T23:59:59.000Z

260

Price controls and international petroleum product prices  

SciTech Connect

The effects of Federal refined-product price controls upon the price of motor gasoline in the United States through 1977 are examined. A comparison of domestic and foreign gasoline prices is made, based on the prices of products actually moving in international trade. There is also an effort to ascribe US/foreign market price differentials to identifiable cost factors. Primary emphasis is on price comparisons at the wholesale level, although some retail comparisons are presented. The study also examines the extent to which product price controls are binding, and attempts to estimate what the price of motor gasoline would have been in the absence of controls. The time period under consideration is from 1969 through 1977, with primary focus on price relationships in 1970-1971 (just before US controls) and 1976-1977. The foreign-domestic comparisons are made with respect to four major US cities, namely, Boston, New York, New Orleans, and Los Angeles. 20 figures, 14 tables.

Deacon, R.T.; Mead, W.J.; Agarwal, V.B.

1980-02-01T23:59:59.000Z

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Natural Gas Wellhead Price  

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

Pipeline and Distribution Use Price City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Vehicle Fuel Price Electric Power Price Period: Monthly Annual Pipeline and Distribution Use Price City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Vehicle Fuel Price Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2007 2008 2009 2010 2011 2012 View History U.S. 6.25 7.97 3.67 4.48 3.95 2.66 1922-2012 Alabama 7.44 9.65 4.32 4.46 1967-2010 Alaska 5.63 7.39 2.93 3.17 1967-2010 Arizona 5.98 7.09 3.19 4.11 1967-2010 Arkansas

262

GETTING THE PRICES RIGHT: AN EVALUATION OF PRICING PARKING BY DEMAND IN SAN FRANCISCO  

E-Print Network (OSTI)

Underpriced and overcrowded curb parking creates problems for everyone except a few lucky drivers who find a cheap space; all the other drivers who cruise to find an open space waste time and fuel, congest traffic, and pollute the air. Overpriced and underoccupied parking also creates problems; when curb spaces remain empty, nearby merchants lose potential customers, workers lose jobs, and cities lose tax revenue. To address these problems, San Francisco has established SFpark, a program that adjusts parking prices to achieve a target parking availability of one or two open spaces on each block. To measure how parking prices affected parking occupancy in San Francisco we calculated the price elasticity of demand for onstreet parking revealed by 5,294 individual price and occupancy changes during the program’s first year. Price elasticity varies greatly by time of day, location, and several other factors, with an average value of –0.4. The average meter price fell 1 percent during the first year, so SFpark adjusted prices up and down according to local demand without increasing prices overall. The city can improve the program by making drivers more aware of the variable prices, reducing the abuse of disabled parking placards, and introducing seasonal adjustments for parking prices.

Gregory Pierce; Donald Shoup

2013-01-01T23:59:59.000Z

263

PRICE GOUGING | Department of Energy  

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

PRICE GOUGING PRICE GOUGING PRICE GOUGING More Documents & Publications PRICE GOUGING Department of Energy Response to Hurricane Katrina Fact Sheet Department of Energy Response to...

264

Why are gasoline prices sticky? A test of alternative models of price adjustment  

E-Print Network (OSTI)

Several macroeconomic models of business cycles rely on the assumption that …rms adjust prices infrequently to generate the short-run non-neutrality of money documented by the literature on monetary transmission. These models posit di¤erent mechanisms to generate price stickiness, with correspondingly di¤erent implications for in‡ation dynamics. While empirical implications regarding the response to macro shocks are indistinguishable on a time series of daily price changes, the models have distinct predictions on the dynamic patterns of price adjustment. In this paper, we use daily data on wholesale gasoline prices to test three explanations for price stickiness: menu-costs, information processing, and strategic interactions. Using an autoregressive conditional binomial (ACB) model, we show that both the past distribution of price changes and the lagged gap have signi…cant explanatory power for the probability of a price change over and above the current price-cost gap. Our results have important implications regarding which of the three explanations (menu-costs, information processing, or strategic interactions) best …ts the observed wholesale gasoline data. First, the signi…cant e¤ect of the historic distribution of price changes leads us to reject menu-costs as an explanation for price

Christopher Douglas; Ana María Herrera

2009-01-01T23:59:59.000Z

265

Converter Program: PSADD Dictionary for Dynamics Model, Version 2.0  

Science Conference Proceedings (OSTI)

This manual contains a listing of the PSADD dictionary for PSS/E dynamics models. The format of this dictionary is the same as that used for the "main" PSADD. Wherever possible, dictionary names and data types are the same as those used in the "main" PSADD. Please note that not all of the PSS/E dynamics models have been included in this dictionary and are convertible by the CONVERTER program. EPRI advisors and PTI engineers selected the models for inclusion based on the perceived "usefulness" of the mode...

2000-07-13T23:59:59.000Z

266

Diesel prices decrease  

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

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 4.05 a gallon on Monday. That's down 4.1 cents from a week ago, based on the weekly price...

267

Diesel prices flat  

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

Diesel prices flat The U.S. average retail price for on-highway diesel fuel saw no movement from last week. Prices remained flat at 3.89 a gallon on Monday, based on the weekly...

268

Overshooting of agricultural prices  

E-Print Network (OSTI)

Rotenberg, Julio J. , "Sticky Prices in the United States,"Monetary Policy on United States Agriculture. A Fix-Price,Flex-Price Approach," Unpublished Ph.D. Disser- tation,

Stamoulis, Kostas G.; Rausser, Gordon C.

1987-01-01T23:59:59.000Z

269

Diesel prices decrease  

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

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.88 a gallon on Monday. That's down a penny from a week ago, based on the weekly price...

270

Diesel prices decrease  

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

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.85 a gallon on Monday. That's down 2 cents from a week ago, based on the weekly price...

271

Diesel prices decrease  

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

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.82 a gallon on Monday. That's down 2.1 cents from a week ago, based on the weekly price...

272

Diesel prices flat nationally  

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

Diesel prices flat nationally The U.S. average retail price for on-highway diesel fuel remained the same from a week ago at 3.98 a gallon on Monday, based on the weekly price...

273

Diesel prices decrease  

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

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.87 a gallon on Monday. That's down 1.6 cents from a week ago, based on the weekly price...

274

Diesel prices increase  

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

Diesel prices increase The U.S. average retail price for on-highway diesel fuel rose to 3.84 a gallon on Monday. That's up 2.2 cents from a week ago, based on the weekly price...

275

Georgia Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices ... History; Imports Price: 6.79: 9.71: 3.73: 4.39: 4.20: 2.78: 1999-2012: Pipeline and Distribution Use Price : 1967-2005: ...

276

Michigan Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Wellhead Price: NA: 5.63: 3.92: 3.79 : 1967-2010: Imports Price: ...

277

House Price Booms and the Current Account  

E-Print Network (OSTI)

A simple open economy asset pricing model can account for the house price and current account dynamics in the G7 over the years 2001-2008. The model features rational households, but assumes that households entertain subjective beliefs about price behavior and update these using Bayes ’ rule. The resulting beliefs dynamics considerably propagate economic shocks and crucially contribute to replicating the empirical evidence. Belief dynamics can temporarily delink house prices from fundamentals, so that low interest rates can fuel a house price boom. House price booms, however, are not necessarily synchronized across countries and the model correctly predicts the heterogeneous response of house prices across the G7, following the fall in real interest rates at the beginning of the millennium. The response to interest rates depends sensitively on agents ’ beliefs at the time of the interest rate reduction, which are a function of the prior history of disturbances hitting the economy. According to the model, the US house price boom could have been largely avoided, if real interest rates had decreased by less after the year 2000.

Klaus Adam; Pei Kuang; Albert Marcet Abstract

2011-01-01T23:59:59.000Z

278

A Threshold Autoregressive Model for Wholesale Electricity Prices  

E-Print Network (OSTI)

A Threshold Autoregressive Model for Wholesale Electricity Prices B. Ricky Rambharat, Department, 2003 Abstract We introduce a discrete-time model for electricity prices, which accounts for both spikes Introduction The study of electricity price dynamics has attracted significant attention from researchers

279

RWP 10-18The Roles of Price Points and Menu Costs in Price Rigidity  

E-Print Network (OSTI)

Macroeconomic models often generate nominal price rigidity via menu costs. This paper provides empirical evidence that treating menu costs as a structural explanation for sticky prices may be spurious. Using supermarket scanner data, I note two empirical facts: (1) price points, embodied in nine-ending prices, account for more than 60 percent of prices; (2) at the conclusion of sales, post-sale prices return to their pre-sale levels nearly 90 percent of the time. I construct a model that nests roles for menu costs and price points and estimate model variants via simulated method of moments. Excluding the two facts yields a statistically and economically significant role for menu costs in generating price rigidity. Incorporating the two facts yields an incentive to set nine-ending prices two orders of magnitude larger than the menu costs in this model. In this setting, the price point model can match the two stylized facts, but menu costs are effectively irrelevant as a source of price rigidity. The choice of a mechanism for price rigidity matters for aggregate dynamics.

Edward S. Knotek Ii; Edward S. Knotek Ii

2010-01-01T23:59:59.000Z

280

The Roles of Price Points and Menu Costs in Price Rigidity *  

E-Print Network (OSTI)

Macroeconomic models often generate nominal price rigidity via menu costs. This paper provides empirical evidence that treating menu costs as a structural explanation for sticky prices may be spurious. Using supermarket scanner data, I note two empirical facts: (1) price points, embodied in nine-ending prices, account for more than 60 percent of prices; (2) at the conclusion of sales, post-sale prices return to their pre-sale levels nearly 90 percent of the time. I construct a model that nests roles for menu costs and price points and estimate model variants via simulated method of moments. Excluding the two facts yields a statistically and economically significant role for menu costs in generating price rigidity. Incorporating the two facts yields an incentive to set nine-ending prices two orders of magnitude larger than the menu costs in this model. In this setting, the price point model can match the two stylized facts, but menu costs are effectively irrelevant as a source of price rigidity. The choice of a mechanism for price rigidity matters for aggregate dynamics.

Edward S. Knotek Ii

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Retail Price Changes Lag Spot Prices  

Gasoline and Diesel Fuel Update (EIA)

1 1 Notes: While EIA cannot claim to explain all of the factors that drive retail gasoline prices, we have had a fair amount of success in exploring the relationship between wholesale and retail prices. In particular, we have looked closely at the "pass-through" of changes in spot prices to the retail market. This graph shows a weighted national average of spot prices for regular gasoline -both conventional and reformulated (shown in red), and EIA's weekly survey price for retail regular (again both conventional and reformulated). As you can see, spot prices tend to be more volatile (and would be even more so on a daily basis), while these changes are smoother by the time they reach the retail pump. Furthermore, by looking at the peaks, you can see the retail prices seem to lag the spot price changes

282

Residential Heating Oil Prices  

U.S. Energy Information Administration (EIA)

We normally collect and publish this data twice a month, but given the low stocks and high prices, we started tracking the prices weekly.

283

Natural Gas Wellhead Price  

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

included in Prices Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes...

284

Primer on Gasoline Prices  

Reports and Publications (EIA)

This brochure answers, in laymen's terms, questions such as "What are the components of the retail price of gasoline? Why do gasoline prices fluctuate?

Information Center

2009-07-15T23:59:59.000Z

285

Natural Gas Wellhead Prices  

U.S. Energy Information Administration (EIA)

Slide 19 of 27. Price: Wellhead. Natural gas wellhead prices are projected to move up 5 percent this winter, averaging about $2.28 per Mcf during this ...

286

Crude Oil Price Forecast  

U.S. Energy Information Administration (EIA)

We believe crude oil prices will strengthen somewhat, but prices will rise much more slowly than they fell, and they are expected to remain lower in ...

287

Price Liquefied Sabine Pass, LA Natural Gas Exports Price ...  

U.S. Energy Information Administration (EIA)

Price Liquefied Sabine Pass, LA Natural Gas Exports Price to Brazil (Dollars per Thousand Cubic Feet)

288

What Is Price Volatility  

Gasoline and Diesel Fuel Update (EIA)

What Is Price Volatility? What Is Price Volatility? The term "price volatility" is used to describe price fluctuations of a commodity. Volatility is measured by the day-to-day percentage difference in the price of the commodity. The degree of variation, not the level of prices, defines a volatile market. Since price is a function of supply and demand, it follows that volatility is a result of the underlying supply and demand characteristics of the market. Therefore, high levels of volatility reflect extraordinary characteristics of supply and/or demand. Prices of basic energy (natural gas, electricity, heating oil) are generally more volatile than prices of other commodities. One reason that energy prices are so volatile is that many consumers are extremely limited in their ability to substitute other fuels when the price, of natural gas

289

Summary of work completed under the Environmental and Dynamic Equipment Qualification research program (EDQP)  

Science Conference Proceedings (OSTI)

This report documents the results of the main projects undertaken under the Environmental and Dynamic Equipment Qualification Research Program (EDQP) sponsored by the U.S. Nuclear Regulatory Commission (NRC) under FIN A6322. Lasting from fiscal year 1983 to 1987, the program dealt with environmental and dynamic (including seismic) equipment qualification issues for mechanical and electromechanical components and systems used in nuclear power plants. The research results have since been used by both the NRC and industry. The program included seven major research projects that addressed the following issues: (a) containment purge and vent valves performing under design basis loss of coolant accident loads, (b) containment piping penetrations and isolation valves performing under seismic loadings and design basis and severe accident containment wall displacements, (c) shaft seals for primary coolant pumps performing under station blackout conditions, (d) electrical cabinet internals responding to in-structure generated motion (rattling), and (e) in situ piping and valves responding to seismic loadings. Another project investigating whether certain containment isolation valves will close under design basis conditions was also started under this program. This report includes eight main section, each of which provides a brief description of one of the projects, a summary of the findings, and an overview of the application of the results. A bibliography lists the journal articles, papers, and reports that document the research.

Steele, R. Jr.; Bramwell, D.L.; Watkins, J.C.; DeWall, K.G. [EG and G Idaho, Inc., Idaho Falls, ID (United States)

1994-02-01T23:59:59.000Z

290

Natural Gas Price Uncertainty: Establishing Price Floors  

Science Conference Proceedings (OSTI)

This report presents the results of comprehensive calculations of ceiling and floor prices for natural gas. Ceiling prices are set by the price levels at which it is more economic to switch from natural gas to residual fuel oil in steam units and to distillate in combined cycle units. Switching to distillate is very rare, whereas switching to fuel oil is quite common, varying between winter and summer and increasing when natural gas prices are high or oil prices low. Monthly fuel use was examined for 89 ...

2007-01-11T23:59:59.000Z

291

Genetic Programming for Evolving a Heterogenous Multi-agent System in a Dynamic Environment  

E-Print Network (OSTI)

The Robocup Rescue Simulation System (RCRSS) is dynamic system of of multi-agent interaction, simulating a large-scale urban disaster scenario. Teams of rescue agents are charged with the tasks of minimizing civilian casualties and infrastructure damage while competing against limitations on time, communication, and awareness. There have been numerous approaches to solving the problems of the RCRSS, but as of yet, no attempts to use Genetic Programming (GP) have been reported. GP is a popular form of automatic programming which utilizes the evolutionary mechanism of Genetic Algorithms (GA) to evolve a potentially complex program from simplistic primitives. This is the approach that will be used in this thesis to evolve the behaviours of a heterogenous set of cooperating agents for the RCRSS. Specifically, this thesis will study GP’s ability to evolve individual behaviours such as appropriate action selection, cooperation amongst homogenous and heterogenous teams of agents, and task assignment. 1 1

Andrew Runka; Dr. Vladimir Wojcik

2009-01-01T23:59:59.000Z

292

GEODYN2: a bottom hole assembly. Geological formation dynamic interaction computer program  

DOE Green Energy (OSTI)

This paper describes the current development of a three-dimensional transient dynamic finite element computer program, GEODYN2, capable of simulating the behavior of a rotating bottom hole assembly (BHA) interacting with a non-uniform formation. The GEODYN2 Program facilitates a very detailed analysis/simulation of the behavior of a BHA with a polycrystalline diamond compact (PDC) bit and various stabilizer designs. The basic drill string mechanics implemented within the program, the overall algorithm, and the more pertinent modeling features which permit this level of analysis are briefly outlined. The implementation of these features and how they allow calculation of the response behavior of a bottom hole assembly are demonstrated. Although the development and enhancement of modeling capabilities within GEODYN2 is ongoing, it is anticipated that the preliminary verification results thus far generated will further the understanding of the response behavior of BHAs. 9 refs., 16 figs.

Baird, J.A.; Caskey, B.C.; Wormley, D.N.; Stone, C.M.

1985-01-01T23:59:59.000Z

293

Do Producer Prices Lead Consumer Prices?  

E-Print Network (OSTI)

increased rapidly. Excluding food and energy, prices of crude materials and intermediate goods rose at annual rates of 7.2 and 16.7 percent, respectively. At the same time, however, prices of consumer goods and services excluding food and energy increased a more modest 2.9 percent. Many analysts are concerned that recent increases in the prices of crude and intermediate goods may be passed through to consumers, resulting in a higher rate of inflation in consumer prices later this year and perhaps in 1996. This article examines whether price increases at the early stages of production should be expected to move through the production chain, leading to increases in consumer prices. In the first section, a review of basic economic theory suggests there should be a pass-through effect—that is, producer prices should lead and thereby help predict consumer prices. A more sophisticated analysis, though, suggests the pass-through effect may be weak. In the second section, an examination of the empirical evidence indicates that producer prices are not always good predictors of consumer prices. The article Todd E. Clark is an economist at the Federal Reserve Bank of Kansas City. Mangal Goswami, a research associate at the bank, helped prepare the article. concludes that the recent increases in some producer prices do not necessarily signal higher inflation.

E. Clark

1994-01-01T23:59:59.000Z

294

Simulating Price Responsive Distributed Resources  

SciTech Connect

Distributed energy resources (DER) include distributed generation, storage, and responsive demand. The integration of DER into the power system control framework is part of the evolutinary advances that allow these resources to actively particpate in the energy balance equation. Price can provide a powerful signal for independent decision-making in distributed control strategies. To study the impact of price responsive DER on the electric power system requires generation and load models that can capture the dynamic coupling between the energy market and the physical operation of the power system in appropriate time frames. This paper presents modeling approaches for simulating electricity market price responsive DER, and introduces a statistical mechanics approach to modeling the aggregated response of a transformed electric system of pervasive, transacting DER.

Lu, Ning; Chassin, David P.; Widergren, Steven E.

2004-10-15T23:59:59.000Z

295

State heating oil and propane program: Final report. Survey of No.2 heating oil and propane prices at the retail level, October 1997 through March 1998  

SciTech Connect

The Energy Efficiency Division of the Vermont Department of Public Service (DPS) monitored the price and inventory of residential heating oil and propane during the 1997--98 heating season under a grant from the US Department of Energy`s Energy Information Administration (EIA). DPS staff collected data biweekly between October 5, 1997 and March 16, 1998 on the retail price of {number_sign}2 home heating oil and propane by telephone survey. Propane price quoted was based on the rate for a residential home heating customer using 1,000+ per year. The survey included a sample of fuel dealers selected by the EIA, plus additional dealers and fuels selected by the DPS. The EIA weighted, analyzed, and reported the data collected from their sample.

1998-11-01T23:59:59.000Z

296

Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming  

Science Conference Proceedings (OSTI)

This work presents a new algorithm for solving the explicit/multi-parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The ... Keywords: Dynamic programming, Explicit Model Predictive Control, Model Predictive Control, Multi-parametric control, Multi-parametric programming

K. I. Kouramas; N. P. Faísca; C. Panos; E. N. Pistikopoulos

2011-08-01T23:59:59.000Z

297

Real Time Pricing as a Default or Optional Service for C&I Customers: A Comparative Analysis of Eight Case Studies  

E-Print Network (OSTI)

Response Program, ISO-NE Real-Time Price Response Program,rather than real time market prices) is more compatible withare correlated to real-time market prices, customers may be

Barbose, Galen; Goldman, Charles; Bharvirkar, Ranjit; Hopper, Nicole; Ting, Michael; Neenan, Bernie

2005-01-01T23:59:59.000Z

298

Sustainably Priced Energy Enterprise Development (SPEED) Goals | Department  

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

Sustainably Priced Energy Enterprise Development (SPEED) Goals Sustainably Priced Energy Enterprise Development (SPEED) Goals Sustainably Priced Energy Enterprise Development (SPEED) Goals < Back Eligibility Investor-Owned Utility Municipal Utility Rural Electric Cooperative Savings Category Bioenergy Alternative Fuel Vehicles Hydrogen & Fuel Cells Buying & Making Electricity Water Solar Heating & Cooling Water Heating Wind Program Info State Vermont Program Type Renewables Portfolio Standard Provider Vermont Public Service Board Vermont's Sustainably Priced Energy Enterprise Development (SPEED) Program was created by legislation in 2005 to promote renewable energy development. The SPEED program itself is not a renewable portfolio goal or standard. However, if the Vermont Public Service Board (PSB) determines that the

299

Geothermal Power: Meeting the Challenge of Electric Price Stabilizatio...  

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

Office EETD Safety Program Development Contact Us Department Contacts Media Contacts Geothermal Power: Meeting the Challenge of Electric Price Stabilization in the West Speaker(s):...

300

Ethane prices trail other natural gas liquids - Today in Energy ...  

U.S. Energy Information Administration (EIA)

... shift their drilling programs to the more liquids-rich portions of natural gas fields to take advantage of considerable price premiums over dry natural gas. ...

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Enforcement Guidance Supplement 00-02, Price-Anderson Amendment...  

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

OFFICE OF ENFORCEMENT AND INVESTIGATION SUBJECT: Enforcement Guidance Supplement 00-02: Price-Anderson Amendment Act (PAAA) Program Reviews Section 1.3 of the Operational...

302

The welfare effects of raising household energy prices in Poland  

Science Conference Proceedings (OSTI)

We examine the welfare effects from increasing household energy prices in Poland. Subsidizing household energy prices, common in the transition economies, is shown to be highly regressive. The wealthy spend a larger portion of their income on energy and consume more energy in absolute terms. We therefore rule out the oft-used social welfare argument for delaying household energy price increases. Raising prices, while targeting relief to the poor through a social assistance program is the first-best response. However, if governments want to ease the adjustment, several options are open, including: in-kind transfers to the poor, vouchers, in-cash transfers, and lifeline pricing for electricity. Our simulations show that if raising prices to efficient levels is not politically feasible at present and social assistance targeting is sufficiently weak, it may be socially better to use lifeline pricing and a large price increase than an overall, but smaller, price increase.

Freund, C.L. [Columbia Univ., New York, NY (United States); Wallich, C.I. [World Bank, Washington, DC (United States)

1996-06-01T23:59:59.000Z

303

How regulators should use natural gas price forecasts  

Science Conference Proceedings (OSTI)

Natural gas prices are critical to a range of regulatory decisions covering both electric and gas utilities. Natural gas prices are often a crucial variable in electric generation capacity planning and in the benefit-cost relationship for energy-efficiency programs. High natural gas prices can make coal generation the most economical new source, while low prices can make natural gas generation the most economical. (author)

Costello, Ken

2010-08-15T23:59:59.000Z

304

Price Responsive Demand in New York Wholesale Electricity Market using  

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

Price Responsive Demand in New York Wholesale Electricity Market using Price Responsive Demand in New York Wholesale Electricity Market using OpenADR Title Price Responsive Demand in New York Wholesale Electricity Market using OpenADR Publication Type Report LBNL Report Number LBNL-5557E Year of Publication 2012 Authors Kim, Joyce Jihyun, and Sila Kiliccote Date Published 06/2012 Publisher LBNL/NYSERDA Keywords commercial, demand response, dynamic pricing, mandatory hourly pricing, open automated demand response, openadr, pilot studies & implementation, price responsive demand Abstract In New York State, the default electricity pricing for large customers is Mandatory Hourly Pricing (MHP), which is charged based on zonal day-ahead market price for energy. With MHP, retail customers can adjust their building load to an economically optimal level according to hourly electricity prices. Yet, many customers seek alternative pricing options such as fixed rates through retail access for their electricity supply. Open Automated Demand Response (OpenADR) is an XML (eXtensible Markup Language) based information exchange model that communicates price and reliability information. It allows customers to evaluate hourly prices and provide demand response in an automated fashion to minimize electricity costs. This document shows how OpenADR can support MHP and facilitate price responsive demand for large commercial customers in New York City.

305

MTBE Prices Responded to Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: On top of the usual factors impacting gasoline prices, natural gas has had some influence recently. MTBE is an oxygenate used in most of the RFG consumed in the U.S. Generally, it follows gasoline prices and its own supply/demand balance factors. But this winter, we saw it respond strongly to natural gas prices. MTBE is made from methanol and isobutylene, which in turn come from methane and butane. Both methane and butane come from natural gas streams. Until this year, the price of natural gas has been so low that it had little effect. But the surge that occurred in December and January pulled MTBE up . Keep in mind that about 11% MTBE is used in a gallon of RFG, so a 30 cent increase in MTBE is only about a 3 cent increase in the price of RFG. While we look ahead at this summer, natural gas prices should be

306

Appendix A: Fuel Price Forecast Introduction..................................................................................................................................... 1  

E-Print Network (OSTI)

Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts............................................................................................................................... 12 Oil Price Forecast Range

307

MTBE Prices Responded to Natural Gas Prices  

U.S. Energy Information Administration (EIA)

On top of the usual factors impacting gasoline prices, natural gas has had some influence recently. ... Both methane and butane come from natural gas streams.

308

Maximum entropy distribution of stock price fluctuations  

E-Print Network (OSTI)

The principle of absence of arbitrage opportunities allows obtaining the distribution of stock price fluctuations by maximizing its information entropy. This leads to a physical description of the underlying dynamics as a random walk characterized by a stochastic diffusion coefficient and constrained to a given value of the expected volatility, taking in this way into account the information provided by the existence of an option market. This model is validated by a comprehensive comparison with observed distributions of both price return and diffusion coefficient. Expected volatility is the only parameter in the model and can be obtained by analysing option prices. We give an analytic formulation of the probability density function for price returns which can be used to extract expected volatility from stock option data. This distribution is of high practical interest since it should be preferred to a Gaussian when dealing with the problem of pricing derivative financial contracts.

Bartiromo, Rosario

2011-01-01T23:59:59.000Z

309

Maryland Gasoline Price Data  

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

Maryland Maryland Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Baltimore BaltimoreGasPrices.com Automotive.com MapQuest.com Bethesda BethesdaGasPrices.com Automotive.com MapQuest.com Bowie BowieGasPrices.com Automotive.com MapQuest.com Frederick FrederickGasPrices.com Automotive.com MapQuest.com Gaithersburg GaithersburgGasPrices.com Automotive.com MapQuest.com Other Maryland Cities MarylandGasPrices.com (search by city or ZIP code) - GasBuddy.com Maryland Gas Prices (selected cities) - GasBuddy.com Maryland Gas Prices (organized by county) - Automotive.com Gas Prices of the United States: Maryland Cities - MapQuest

310

Massachusetts Gasoline Price Data  

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

Massachusetts Massachusetts Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Boston BostonGasPrices.com Automotive.com MapQuest.com Brockton BrocktonGasPrices.com Automotive.com MapQuest.com Cambridge CambridgeGasPrices.com Automotive.com MapQuest.com Fall River FallRiverGasPrices.com Automotive.com MapQuest.com Haverhill HaverhillGasPrices.com Automotive.com MapQuest.com Lawrence LawrenceGasPrices.com Automotive.com MapQuest.com Lowell LowellGasPrices.com Automotive.com MapQuest.com New Bedford NewBedfordGasPrices.com Automotive.com Mapquest.com Taunton TauntonGasPrices.com Automotive.com MapQuest.com

311

Ohio Gasoline Price Data  

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

Ohio Ohio Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Akron AkronGasPrices.com Automotive.com Mapquest.com Cincinnati CincinnatiGasPrices.com Automotive.com Mapquest.com Cleveland ClevelandGasPrices.com Automotive.com Mapquest.com Columbus ColumbusGasPrices.com Automotive.com Mapquest.com Dayton DaytonGasPrices.com Automotive.com Mapquest.com Toledo ToledoGasPrices.com Automotive.com Mapquest.com Other Ohio Cities OhioGasPrices.com (search by city or ZIP code) - GasBuddy.com Ohio Gas Prices (selected cities) - GasBuddy.com Ohio Gas Prices (organized by county) - Automotive.com

312

Regional Retail Gasoline Prices  

Gasoline and Diesel Fuel Update (EIA)

7 7 Notes: Retail gasoline prices, like those for distillate fuels, have hit record prices nationally and in several regions this year. The national average regular gasoline price peaked at $1.68 per gallon in mid-June, but quickly declined, and now stands at $1.45, 17 cents higher than a year ago. Two regions, in particular, experienced sharp gasoline price runups this year. California, which often has some of the highest prices in the nation, saw prices peak near $1.85 in mid-September, while the Midwest had average prices over $1.87 in mid-June. Local prices at some stations in both areas hit levels well over $2.00 per gallon. The reasons for the regional price runups differed significantly. In the Midwest, the introduction of Phase 2 RFG was hampered by low stocks,

313

Virginia Gasoline Price Data  

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

Virginia Virginia Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Alexandria AlexandriaGasPrices.com Automotive.com Mapquest.com Arlington ArlingtonGasPrices.com Automotive.com Mapquest.com Chesapeake ChesapeakeGasPrices.com Automotive.com Mapquest.com Hampton HamptonGasPrices.com Automotive.com Mapquest.com Newport News NewportNewsGasPrices.com Automotive.com Mapquest.com Norfolk NorfolkGasPrices.com Automotive.com Mapquest.com Portsmouth PortsmouthGasPrices.com Automotive.com Mapquest.com Richmond RichmondGasPrices.com Automotive.com Mapquest.com Virginia Beach VirginiaBeachGasPrices.com Automotive.com Mapquest.com

314

Illinois Gasoline Price Data  

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

Illinois Illinois Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Arlington Heights ArlingtonHeightsGasPrices.com Automotive.com MapQuest.com Aurora AuroraGasPrices.com Automotive.com MapQuest.com Bloomington BloomingtonGasPrices.com Automotive.com MapQuest.com Champaign ChampaignGasPrices.com Automotive.com MapQuest.com Chicago ChicagoGasPrices.com Automotive.com MapQuest.com Decatur DecaturGasPrices.com Automotive.com Mapquest.com Elgin ElginGasPrices.com Automotive.com MapQuest.com Joliet JolietGasPrices.com Automotive.com MapQuest.com Naperville NapervilleGasPrices.com Automotive.com MapQuest.com

315

Oklahoma Gasoline Price Data  

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

Oklahoma Oklahoma Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Lawton LawtonGasPrices.com Automotive.com Mapquest.com Norman NormanGasPrices.com Automotive.com Mapquest.com Oklahoma City OklahomaCityGasPrices.com Automotive.com Mapquest.com Tulsa TulsaGasPrices.com Automotive.com Mapquest.com Other Oklahoma Cities OklahomaGasPrices.com (search by city or ZIP code) - GasBuddy.com Oklahoma Gas Prices (selected cities) - GasBuddy.com Oklahoma Gas Prices (organized by county) - Automotive.com Gas Prices of the United States: Oklahoma Cities - MapQuest Oklahoma Gas Prices (organized by county, search by ZIP code) -

316

Tennessee Gasoline Price Data  

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

Tennessee Tennessee Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Chattanooga ChattanoogaGasPrices.com Automotive.com Mapquest.com Clarksville ClarksvilleGasPrices.com Automotive.com Mapquest.com Knoxville KnoxvilleGasPrices.com Automotive.com Mapquest.com Memphis MemphisGasPrices.com Automotive.com Mapquest.com Murfreesboro MurfreesboroGasPrices.com Automotive.com Mapquest.com Nashville NashvilleGasPrices.com Automotive.com Mapquest.com Other Tennessee Cities TennesseeGasPrices.com (search by city or ZIP code) - GasBuddy.com Tennessee Gas Prices (selected cities) - GasBuddy.com Tennessee Gas Prices (organized by county) - Automotive.com

317

Wisconsin Gasoline Price Data  

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

Wisconsin Wisconsin Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Appleton AppletonGasPrices.com Automotive.com Mapquest.com Eau Claire EauClaireGasPrices.com Automotive.com Mapquest.com Green Bay GreenBayGasPrices.com Automotive.com Mapquest.com Kenosha KenoshaGasPrices.com Automotive.com Mapquest.com Madison MadisonGasPrices.com Automotive.com Mapquest.com Milwaukee MilwaukeeGasPrices.com Automotive.com Mapquest.com Other Wisconsin Cities WisconsinGasPrices.com (search by city or ZIP code) - GasBuddy.com Wisconsin Gas Prices (selected cities) - GasBuddy.com Wisconsin Gas Prices (organized by county) - Automotive.com

318

PRICE & AVAILABILITY UPDATES  

E-Print Network (OSTI)

4.3 Price & Availability Updates File when titles transferred to new supplier..................... 5 4.4 Format of the ‘Day ’ element in Availability Dates......................................................... 5 5 Example of Price & Availability Updates transmission....................................................... 5 6 Price & Availability Updates file header............................................................................. 7 Example of a complete Price & Availability Updates file header....................................... 12 7 Price & Availability Updates “message level ” content...................................................... 13 8 Price & Availability Updates “line level ” content............................................................... 14 Example showing Order "line level " segments NOI to DNC.............................................. 21 9 Price & Availability Updates message trailer.................................................................... 21 10 Price & Availability Updates file trailer............................................................................ 22 NOTE: The TRADACOMS Price & Availability Updates message is not recommended for new implementations. The recommended formats for the communication of book product information are the ONIX for Books Product Information message and Supply Update message.

unknown authors

2010-01-01T23:59:59.000Z

319

Higher Prices from Entry: Pricing of Brand-Name Drugs  

E-Print Network (OSTI)

with Distance Figure 6 Cumulative Unexpected Price Effectsand Paul J. Seguin, "Price Volatility, Trading Volume andGoods in Pharmaceutical Price In- dexes," American Economic

Perloff, Jeffrey M.; Suslow, Valerie Y.; Seguin, Paul J.

1995-01-01T23:59:59.000Z

320

Higher Prices from Entry: Pricing of Brand-Name Drugs  

E-Print Network (OSTI)

4 Bertrand and Cartel Prices Vary with z 7T, CS L Figure 5Distance Cumulative Abnormal Price Changes (%) Dissimilarof New Drug Figure 6 Cumulative Unexpected Price Effects

Perloff, Jeffrey M.; Suslow, Valerie Y.; Seguin, Paul J.

1995-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "dynamic pricing programs" 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

State Volume Price Volume Price Volume Price Volume Price Volume Price  

Gasoline and Diesel Fuel Update (EIA)

7 7 2000 2001 2002 2003 2004 State Volume Price Volume Price Volume Price Volume Price Volume Price Pipeline (Canada) Eastport, ID..................... 830,351 3.79 802,182 4.71 759,647 2.83 R 623,652 4.72 707,885 5.30 Calais, ME ...................... 123,521 4.50 152,486 4.47 124,991 3.49 R 115,301 R 5.85 102,292 6.44 Detroit, MI ....................... 6,171 3.82 405 9.34 1,948 3.56 2,514 5.96 1,117 6.27 Marysville, MI.................. 0 -- 0 -- 74 3.95 0 -- 303 7.80 St. Clair, MI..................... 17,198 4.45 21,747 4.54 28,441 3.19 5,202 5.84 22,853 6.50 International Falls, MN .... 3,022 2.77 617 4.85 602 3.01 0 -- 0 -- Noyes, MN...................... 469,361 3.75 448,898 4.19 402,621 3.09 R 359,801 5.04 399,298 5.77 Warroad, MN .................. 4,576 3.95 5,318 4.52

322

Examination Procedure for Price Verification  

Science Conference Proceedings (OSTI)

... advertised or displayed at the same price that was ... to permit 2 % of products to be inaccurately priced? ... overall quality of a store's pricing practices. ...

2013-06-28T23:59:59.000Z

323

C. Uniform Unit Pricing Regulation  

Science Conference Proceedings (OSTI)

... to permit retail stores that voluntarily provide unit pricing to present prices using various ... with requirements that specify that the unit price is to be ...

2013-10-25T23:59:59.000Z

324

All Price Tables.vp  

Annual Energy Outlook 2012 (EIA)

8. Coal and Retail Electricity Prices and Expenditures, Ranked by State, 2011 Rank Coal Retail Electricity Prices Expenditures Prices Expenditures State Dollars per Million Btu...

325

South Carolina Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Pipeline and Distribution Use Price : 1967-2005: Citygate Price: ...

326

Spot Distillate & Crude Oil Prices  

U.S. Energy Information Administration (EIA)

Retail distillate prices follow the spot distillate markets, and crude oil prices have been the main driver behind distillate spot price increases until recently.

327

Natural Gas Spot Prices:  

Gasoline and Diesel Fuel Update (EIA)

4 of 26 4 of 26 Notes: Spot wellhead prices last summer averaged well over $4.00 per thousand cubic feet during a normally low-price season. During the fall, these prices stayed above $5.00 per thousand cubic feet, more than double the year-ago average price. In January, the spot wellhead price averaged a record $8.98 per thousand cubic feet. Spot prices at the wellhead have never been this high for such a prolonged period. The chief reason for these sustained high gas prices was, and still is, uneasiness about the supply situation. Concern about the adequacy of winter supplies loomed throughout most of the summer and fall as storage levels remained significantly depressed. Last December, the most severe assumptions about low storage levels became real, when the spot price

328

Understanding Crude Oil Prices  

E-Print Network (OSTI)

2004. “OPEC’s Optimal Crude Oil Price,” Energy Policy 32(2),Figure 3. Price of crude oil contract maturing December ofbarrels per day. Monthly crude oil production Iran Iraq

Hamilton, James Douglas

2008-01-01T23:59:59.000Z

329

Diesel prices decrease slightly  

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

Diesel prices decrease slightly The U.S. average retail price for on-highway diesel fuel fell slightly to 3.84 a gallon on Monday. That's down 3-tenths of a penny from a week ago,...

330

Diesel prices rise slightly  

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

Diesel prices rise slightly The U.S. average retail price for on-highway diesel fuel rose slightly to 4.16 a gallon on Monday. That's up 2-tenths of a penny from a week ago, based...

331

Diesel prices slightly decrease  

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

3, 2013 Diesel prices slightly decrease The U.S. average retail price for on-highway diesel fuel fell to 3.87 a gallon on Monday. That's down 1.1 cents from a week ago, based on...

332

Diesel prices slightly decrease  

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

Diesel prices slightly decrease The U.S. average retail price for on-highway diesel fuel fell slightly to 3.84 a gallon on Monday. That's down 8-tenths of a penny from a week ago,...

333

Diesel prices increase nationally  

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

Diesel prices increase nationally The U.S. average retail price for on-highway diesel fuel rose to 3.91 a gallon on Monday. That's up 1.3 cents from a week ago, based on the...

334

Florida Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Citygate Price: 4.79: 4.68: 4.54: 4.47: 4.26: 4.33: 1989-2013: ...

335

Michigan Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) Area: ... History; Citygate Price: 4.74: 4.99: 4.52: 4.48: 4.13: NA: ...

336

Maine Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Citygate Price: 6.72: 8.18: 11.03: NA: NA: 7.19: 1989-2013: ...

337

Pennsylvania Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Citygate Price: 6.14: 7.58: 8.34: 7.51: 7.39: 6.16: 1989-2013: ...

338

Alabama Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) Area: ... History; Citygate Price: 4.81: 5.12: 5.31: 4.92: 4.64: NA: ...

339

Career Services Pricing Information  

Science Conference Proceedings (OSTI)

Job/Resume Posting and Prices Career Services Pricing Information Career Services Career Services chemistry jobs classifieds employment fats global help wanted job Jobs member membership network oils science jobs ...

340

Diesel prices decrease  

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

to 3.88 a gallon on Monday. That's down 0.4 cents from a week ago, based on the weekly price survey by the U.S. Energy Information Administration. Diesel prices were highest in...

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Retail Propane Prices  

Gasoline and Diesel Fuel Update (EIA)

6 Notes: Consistent with spot prices, residential propane prices have been higher all winter than during the past several years. The recent surge is mainly the result of the surge...

342

Edgeworth Price Cycles, Cost-based Pricing and Sticky Pricing in Retail Gasoline Markets  

E-Print Network (OSTI)

Asymmetrically to Crude Oil Price Changes? ”, QuarterlyS. , A. Shepard. “Sticky Prices, Inventories, and MarketGas Wars: Retail Gasoline Price Fluctua- tions”, Review of

Noel, Michael

2004-01-01T23:59:59.000Z

343

Asymmetric Wholesale Pricing: Theory and Evidence  

Science Conference Proceedings (OSTI)

Asymmetric pricing or asymmetric price adjustment is the phenomenon where prices rise more readily than they fall. We offer and provide empirical support for a new theory of asymmetric pricing in wholesale prices. Wholesale prices may adjust asymmetrically ... Keywords: asymmetric price adjustment, asymmetric pricing, channel of distribution, channel pricing, cost of price adjustment, economic model, menu cost, retailing, scanner data, wholesale price

Sourav Ray; Haipeng (Allan) Chen; Mark E. Bergen; Daniel Levy

2006-03-01T23:59:59.000Z

344

Price Sound Laboratory  

Science Conference Proceedings (OSTI)

Price Sound Laboratory. NVLAP Lab Code: 200874-0. Address and Contact Information: 638 RALEIGH STREET WINNIPEG ...

2013-10-31T23:59:59.000Z

345

EIA Energy Prices  

U.S. Energy Information Administration (EIA)

This publication includes total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, ...

346

EIA Oil price timeline  

U.S. Energy Information Administration (EIA)

Crude oil, gasoline, heating oil, diesel, propane, ... Sales, revenue and prices, power plants, fuel use, stocks, generation, trade, demand & emissions.

347

Real-time pricing -- supplanted by Price-risk derivatives?  

Science Conference Proceedings (OSTI)

Future trends in pricing options for wholesale electrical generation are discussed. Specifically, the effect of price derivatives on electricity consumption are examined. Economic analyses are presented for customer demand in real-time pricing scenarios with and without a price derivative hedge. It is determined that consumption will be curtailed even when price caps have been purchased. Consumption behavior is also analyzed to determine the effect of different price caps; regardless of price, consumption is curtailed in response to price.

O`Sheasy, M.

1997-03-01T23:59:59.000Z

348

Price-responsive demand management for a smart grid world  

Science Conference Proceedings (OSTI)

Price-responsive demand is essential for the success of a smart grid. However, existing demand-response programs run the risk of causing inefficient price formation. This problem can be solved if each retail customer could establish a contract-based baseline through demand subscription before joining a demand-response program. (author)

Chao, Hung-po

2010-01-15T23:59:59.000Z

349

Wisconsin Natural Gas Prices  

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

Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.04 8.71 6.70 6.14 5.65 4.88 1984-2012 Residential Price 12.02 12.81 10.76 10.34 9.77 9.23 1967-2012 Percentage of...

350

Analysis of alternative-fuel price trajectories  

Science Conference Proceedings (OSTI)

Findings are presented from a study to (1) acquire, analyze, and report alternative published price projections including both oil- and coal-price trajectories, and to (2) apply the fixed-annuity formula to the updated primary source projections (Energy Information Administration; Data Resources, Inc.; and Wharton Econometric Forecasting Associates, Inc.) and to the newly acquired price projections. This report also encompasses: comparisons of key assumptions underlying the price projections, and a discussion of the applicability of the fixed-annuity formula as used in the alternative-cost calculation. Section II contains graphic presentations of all updated and newly acquired coal and oil price forecasts and the corresponding calculated annuity equivalents, tabulated presentations and discussions of each forecast and underlying assumptions, and a description of how each forecast price series was transformed into input for the present-value formulas. Section III presents the fixed-annuity formula employed and discusses its appropriateness for this application. Section IV discusses the applicability of the net present value approach for comparing alternate-fuel price trajectories. Appendix A contains a listing of contacts as potential sources of price forecasts. Appendix B contains the raw forecast data from each forecast source and the coal and oil price series derived from the raw data which were actually input into the cost calculation procedure. Appendix C contains a description and listing of the computer program developed to implement the cost calculation procedure. Finally, Appendix D contains tabulations and discussions of other alternative world crude price forecasts that were identified, but for which no corresponding coal-price projections were available. (MCW)

Not Available

1980-12-31T23:59:59.000Z

351

Rethinking Real-Time Electricity Pricing  

E-Print Network (OSTI)

Most US consumers are charged a near-constant retail price for electricity, despite substantial hourly variation in the wholesale market price. This paper evaluates the …rst program to expose residential consumers to hourly real-time pricing (RTP). I …nd that enrolled households are statistically signi…cantly price elastic and that consumers responded by conserving energy during peak hours, but remarkably did not increase average consumption during o¤-peak times. The program increased consumer surplus by $10 per household per year. While this is only one to two percent of electricity costs, it illustrates a potential additional bene…t from investment in retail Smart Grid applications, including the advanced electricity meters required to observe a household’s hourly consumption.

Hunt Allcott; Bill Hogan; Erich Muehlegger; Larry Katz; Erin Mansur; Sendhil Mullainathan; Paul Niehaus; Chris Nosko; Ariel Pakes; Dave Rapson; Rob Stavins; Frank Wolak

2010-01-01T23:59:59.000Z

352

Utility spot pricing study : Wisconsin  

E-Print Network (OSTI)

Spot pricing covers a range of electric utility pricing structures which relate the marginal costs of electric generation to the prices seen by utility customers. At the shortest time frames prices change every five ...

Caramanis, Michael C.

1982-01-01T23:59:59.000Z

353

Intraclass Price Elasticity & Electric Rate Design  

E-Print Network (OSTI)

Electric rate design relies on cost incurrance for pricing and pricing structures. However, as utilities move into a marketing mode, rate design needs to respond more to customer reactions to pricing changes. Intraclass price elasticities aid rate designers by estimating customer behavior to change. Intraclass price elasticities vary with customer usage. The more energy used by a customer, the greater the amount of elasticity. For an industrial customer, this means that all energy consumed up to the amount necessary for base operations is relatively inelastic. All energy consumption beyond this becomes more elastic as usage increases. In the book "Innovative Electric Rates," John Chamberlin and Charles Dickson utilize an economic model to test conservation programs. This model utilizes intraclass price elasticities and has a direct use in current electric rate design. The model is a strong indicator of how best a company's electric prices and pricing structures manage demand-side growth, increase energy sales consumption, and aide in non-discriminatory economic development.

Gresham, K. E.

1987-09-01T23:59:59.000Z

354

A statistical analysis of the natural gas futures market : the interplay of sentiment, volatility and prices  

E-Print Network (OSTI)

This paper attempts to understand the price dynamics of the North American natural gas market through a statistical survey that includes an analysis of the variables influencing the price and volatility of this energy ...

Fazzio, Thomas J. (Thomas Joseph)

2010-01-01T23:59:59.000Z

355

Average Residential Price  

Gasoline and Diesel Fuel Update (EIA)

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

356

Average Residential Price  

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

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

357

Average Commercial Price  

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

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

358

Average Commercial Price  

Gasoline and Diesel Fuel Update (EIA)

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

359

Natural Gas Industrial Price  

Gasoline and Diesel Fuel Update (EIA)

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

360

Montana Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.72 7.50 3.16 3.64 1967-2010 Imports Price 6.66 8.22 3.88 4.13 3.75 2.45 1989-2012 Exports Price 6.16 8.14 3.63 4.05 3.82 2.40 1989-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.42 7.71 5.63 5.17 5.11 4.23 1984-2012 Residential Price 9.91 11.45 9.50 8.64 8.80 8.06 1967-2012 Percentage of Total Residential Deliveries included in Prices 99.9 99.9 99.8 99.8 99.8 99.8 1989-2012 Commercial Price 9.76 11.32 9.41 8.54 8.66 7.98 1967-2012 Percentage of Total Commercial Deliveries included in Prices 78.5 79.6 49.2 54.6 53.3 52.9 1990-2012 Industrial Price 9.75 11.04 9.06 8.07 8.13 7.54 1997-2012 Percentage of Total Industrial Deliveries included in Prices

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Louisiana Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 7.02 8.73 3.82 4.23 1967-2010 Imports Price 6.98 9.76 3.89 4.84 7.57 7.98 1989-2012 Exports Price -- -- -- 7.07 9.63 11.80 2007-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.22 9.58 5.96 5.43 5.67 3.48 1984-2012 Residential Price 14.20 15.49 13.15 11.73 11.37 11.54 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 11.83 13.52 10.46 9.88 9.36 8.44 1967-2012 Percentage of Total Commercial Deliveries included in Prices 98.0 98.4 92.0 85.9 83.6 78.0 1990-2012 Industrial Price 7.08 9.32 4.31 4.68 4.25 2.96 1997-2012 Percentage of Total Industrial Deliveries included in Prices

362

Nebraska Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 4.86 6.22 2.97 3.98 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.67 8.12 5.87 5.62 5.11 4.31 1984-2012 Residential Price 11.15 11.11 9.34 8.95 8.84 8.68 1967-2012 Percentage of Total Residential Deliveries included in Prices 85.7 87.1 87.8 87.4 87.3 85.8 1989-2012 Commercial Price 9.16 9.62 7.44 7.08 6.69 6.19 1967-2012 Percentage of Total Commercial Deliveries included in Prices 63.9 57.5 61.3 60.6 60.6 55.8 1990-2012 Industrial Price 7.97 9.12 6.02 5.85 5.61 4.34 1997-2012 Percentage of Total Industrial Deliveries included in Prices 9.7 10.2 8.9 8.2 7.6 6.8 1997-2012 Vehicle Fuel Price 15.10 15.29 1994-2012 Electric Power Price

363

Average Residential Price  

Gasoline and Diesel Fuel Update (EIA)

Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production Natural Gas Processed NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals LNG Storage Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

364

Average Commercial Price  

Gasoline and Diesel Fuel Update (EIA)

Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production Natural Gas Processed NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals LNG Storage Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

365

Consumer Prices During  

Gasoline and Diesel Fuel Update (EIA)

City Gate City Gate City gate prices represent the total cost paid by gas distribu- tion companies for gas received at the point where the gas is physically transferred from a pipeline company or trans- mission system. This price is intended to reflect all charges for the acquisition, storage, and transportation of gas as well as other charges associated with the LDC's obtaining the gas for sale to consumers. Prices paid at the city gate by local distribution companies rose substantially between 1995 and 1996, climbing from $2.78 per thousand cubic feet to $3.27, an increase of 18 percent. Residential Residential consumers pay the highest price for natural gas. It increased to $6.34 per thousand cubic feet from the 1995 price of $6.06 per thousand cubic feet. However, the 1996 price was 1 percent lower than the 1994 price. In recent years, only modest changes in constant dollars have been

366

Connecticut Gasoline Price Data  

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

Connecticut Connecticut Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Bridgeport BridgeportGasPrices.com Automotive.com MapQuest.com Hartford HartfordGasPrices.com Automotive.com MapQuest.com New Haven NewHavenGasPrices.com Automotive.com MapQuest.com Stamford Automotive.com MapQuest.com Waterbury Automotive.com MapQuest.com West Hartford Automotive.com MapQuest.com Other Connecticut Cities ConnecticutGasPrices.com (search by city or ZIP code) - GasBuddy.com Connecticut Gas Prices (selected cities) - GasBuddy.com Connecticut Gas Prices (organized by county) - Automotive.com Gas Prices of the United States: Connecticut Cities - MapQuest

367

Average Residential Price  

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

Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production Natural Gas Processed NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals LNG Storage Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

368

Fundamentals Explain High Prices  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: One can use a simple model to deal with price/fundamental relationships. This one predicts monthly average WTI price as a function of OECD total petroleum stock deviations from the normal levels . The graph shows the model as it begins predicting prices in 1992. It shows how well the model has predicted not only the direction, but the magnitude of prices over this 8+ year period. While the model is simple and not perfect, it does predict the overall trends and, in particular, the recent rise in prices. It also shows that prices may have over-shot the fundamental balance for a while -- at least partially due to speculative concerns over Mideast tensions, winter supply adequacy, and Iraq's export policies. Prices now seem to be correcting, and may even undershoot briefly

369

Energy prices, production  

E-Print Network (OSTI)

on 0 1 2 3 4 5 6 7 8 9 price U K P ./kW h CHP adoption electyricity price to gas price ratio Figure 3. Energy price and CHP annual adoption (UK). Source: DTI (2002b) -5.00% 0.00% 5.00% 10.00% 15.00% 20... .00% 199119921993199419951996199719981999200020012002 an nu al g ro w th r at e in C H P a do pt io n 0 0.2 0.4 0.6 0.8 1 1.2 1.4 price U K P ./kW h CHP adoption Gas price 10 Gas prices leveled off from 1996 onwards and then increased considerably growing by 33% during 1999-2002. In recent...

Bonilla, David

370

Statistics of voltage drop in radial distribution circuits: a dynamic programming approach  

E-Print Network (OSTI)

We analyze a power distribution line with high penetration of distributed generation and strong variations of power consumption and generation levels. In the presence of uncertainty the statistical description of the system is required to assess the risks of power outages. In order to find the probability of exceeding the constraints for voltage levels we introduce the probability distribution of maximal voltage drop and propose an algorithm for finding this distribution. The algorithm is based on the assumption of random but statistically independent distribution of loads on buses. Linear complexity in the number of buses is achieved through the dynamic programming technique. We illustrate the performance of the algorithm by analyzing a simple 4-bus system with high variations of load levels.

Turitsyn, Konstantin S

2010-01-01T23:59:59.000Z

371

Missouri Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 1967-1997 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.53 8.03 7.06 6.17 5.85 5.27 1984-2012 Residential Price 13.42 13.36 12.61 11.66 12.02 12.25 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 11.82 12.02 10.81 10.28 9.99 9.54 1967-2012 Percentage of Total Commercial Deliveries included in Prices 76.9 77.5 76.7 76.5 73.1 69.2 1990-2012 Industrial Price 10.84 11.32 9.55 8.70 8.54 7.93 1997-2012 Percentage of Total Industrial Deliveries included in Prices 12.8 13.9 13.2 13.1 13.4 12.5 1997-2012 Vehicle Fuel Price 8.44 8.66 7.86 6.34 6.11 5.64 1994-2012

372

Arkansas Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 6.61 8.72 3.43 3.84 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.55 8.88 7.86 6.76 6.27 5.36 1984-2012 Residential Price 13.08 14.09 13.39 11.53 11.46 11.82 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 10.07 11.32 10.72 8.89 8.90 7.99 1967-2012 Percentage of Total Commercial Deliveries included in Prices 70.4 64.5 59.4 55.6 51.5 40.2 1990-2012 Industrial Price 9.51 10.56 8.44 7.28 7.44 6.38 1997-2012 Percentage of Total Industrial Deliveries included in Prices 4.2 3.9 3.7 2.8 2.1 1.9 1997-2012 Vehicle Fuel Price 8.39 -- -- -- -- 9.04 1994-2012

373

Iowa Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.80 8.28 5.62 5.69 5.27 4.84 1984-2012 Residential Price 11.76 11.91 9.83 9.57 9.54 9.46 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 9.97 10.25 7.88 7.81 7.55 7.13 1967-2012 Percentage of Total Commercial Deliveries included in Prices 77.7 75.8 72.5 72.0 72.1 72.3 1990-2012 Industrial Price 8.56 9.32 6.23 6.10 5.78 4.70 1997-2012 Percentage of Total Industrial Deliveries included in Prices 6.5 6.6 6.4 5.8 5.5 5.2 1997-2012 Vehicle Fuel Price 11.68 -- -- -- -- -- 1990-2012 Electric Power Price 7.73 W W W W 3.84 1997-2012

374

Maine Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Imports Price 7.57 9.77 4.48 4.94 4.40 3.45 1999-2012 Exports Price -- -- 5.62 4.53 4.46 4.30 2007-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 10.46 13.47 8.64 8.19 8.14 7.73 1984-2012 Residential Price 16.90 17.47 16.43 14.14 14.20 15.94 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 99.9 100.0 100.0 1989-2012 Commercial Price 14.82 15.87 13.94 11.71 11.69 12.22 1967-2012 Percentage of Total Commercial Deliveries included in Prices 46.2 45.0 51.0 45.0 45.8 42.1 1990-2012 Industrial Price 13.40 14.89 9.12 11.23 10.89 10.35 1997-2012 Percentage of Total Industrial Deliveries included in Prices 0.8 0.8 1.2 0.6 0.5 0.4 1997-2012

375

Idaho Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Imports Price 6.31 7.88 3.86 4.19 3.90 2.59 1989-2012 Exports Price -- 7.43 4.49 5.85 4.74 -- 1999-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.68 7.48 5.63 4.82 4.65 4.07 1984-2012 Residential Price 11.47 11.07 10.54 8.95 8.80 8.26 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 10.67 10.28 9.77 8.21 8.09 7.35 1967-2012 Percentage of Total Commercial Deliveries included in Prices 84.8 86.0 83.7 82.0 80.8 77.0 1990-2012 Industrial Price 9.39 9.18 8.53 6.39 6.36 5.73 1997-2012 Percentage of Total Industrial Deliveries included in Prices 2.0 1.9 1.7 1.8 2.0 1.9 1997-2012

376

Maryland Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price NA NA NA NA 1967-2010 Imports Price 7.25 9.09 4.05 5.37 5.30 13.82 1999-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 9.24 10.23 8.02 6.49 6.26 5.67 1984-2012 Residential Price 15.17 16.07 13.73 12.44 12.10 12.17 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 79.3 77.0 1989-2012 Commercial Price 12.30 13.12 10.87 9.87 10.29 10.00 1967-2012 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 27.3 24.7 1990-2012 Industrial Price 11.59 13.46 10.70 9.05 8.61 8.01 1997-2012 Percentage of Total Industrial Deliveries included in Prices 7.8 6.3 5.3 5.3 5.5 5.1 1997-2012

377

Alabama Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 7.44 9.65 4.32 4.46 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.78 9.84 7.61 6.46 5.80 5.18 1984-2012 Residential Price 18.14 18.30 18.12 15.79 15.08 16.20 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 15.06 15.58 14.94 13.34 12.36 12.55 1967-2012 Percentage of Total Commercial Deliveries included in Prices 79.8 80.2 78.8 79.3 78.9 76.2 1990-2012 Industrial Price 8.70 10.57 6.48 6.64 5.57 4.35 1997-2012 Percentage of Total Industrial Deliveries included in Prices 24.0 27.2 27.9 23.7 23.5 22.1 1997-2012 Vehicle Fuel Price -- 17.32 19.17 16.24 11.45 17.99 1990-2012

378

Massachusetts Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Imports Price 7.32 10.34 5.90 4.86 4.77 3.69 1989-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 9.34 10.29 8.29 7.74 7.04 6.03 1984-2012 Residential Price 16.99 17.18 14.85 14.53 13.81 13.22 1967-2012 Percentage of Total Residential Deliveries included in Prices 99.9 85.0 85.6 85.4 89.3 87.8 1989-2012 Commercial Price 15.08 15.25 12.85 12.00 11.68 10.68 1967-2012 Percentage of Total Commercial Deliveries included in Prices 65.3 57.9 56.9 52.1 50.0 48.6 1990-2012 Industrial Price 14.83 15.23 12.07 10.41 10.14 9.82 1997-2012 Percentage of Total Industrial Deliveries included in Prices 29.9 20.6 21.1 19.4 20.6 17.7 1997-2012 Vehicle Fuel Price 12.84 13.80 12.99 12.48 4.28 14.81 1990-2012

379

Vermont Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Imports Price 8.51 9.74 6.34 6.54 5.81 4.90 1989-2012 Pipeline and Distribution Use Price 1982-2005 Citygate Price 10.03 10.66 9.33 8.29 7.98 6.63 1984-2012 Residential Price 15.99 18.31 17.29 16.14 16.17 16.73 1980-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 12.79 14.31 12.96 11.82 11.90 12.09 1980-2012 Percentage of Total Commercial Deliveries included in Prices 100 100 100 100 100 100 1990-2012 Industrial Price 9.08 9.60 7.93 6.57 6.09 4.89 1997-2012 Percentage of Total Industrial Deliveries included in Prices 78.0 79.6 77.9 77.1 80.9 100.0 1997-2012 Electric Power Price 7.72 9.14 5.66 5.73 5.26 4.14 1997-2012

380

Pennsylvania Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price NA NA NA NA 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 9.35 10.39 7.81 7.04 6.28 5.52 1984-2012 Residential Price 14.66 16.22 14.74 12.90 12.46 11.99 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 91.2 88.6 1989-2012 Commercial Price 12.77 14.29 11.83 10.47 10.42 10.24 1967-2012 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 48.5 42.1 1990-2012 Industrial Price 10.64 12.09 9.19 8.23 9.86 9.58 1997-2012 Percentage of Total Industrial Deliveries included in Prices 5.4 5.7 4.5 3.8 2.0 1.3 1997-2012 Vehicle Fuel Price 10.83 8.30 5.15 3.76 3.40 7.96 1990-2012

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Indiana Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.78 7.58 4.05 4.13 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.83 8.94 5.59 5.52 4.97 4.23 1984-2012 Residential Price 11.29 12.65 10.81 8.63 9.46 8.94 1967-2012 Percentage of Total Residential Deliveries included in Prices 96.2 95.0 93.6 94.1 94.6 94.5 1989-2012 Commercial Price 10.20 11.14 9.18 7.55 8.04 7.68 1967-2012 Percentage of Total Commercial Deliveries included in Prices 78.1 77.9 73.9 72.5 70.2 67.5 1990-2012 Industrial Price 8.45 10.48 6.91 5.65 6.53 6.19 1997-2012 Percentage of Total Industrial Deliveries included in Prices 7.4 6.7 7.0 5.6 3.5 1.9 1997-2012 Vehicle Fuel Price 6.09 7.94 4.08 5.19 13.24 12.29 1990-2012

382

Florida Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price NA NA NA NA 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.97 9.73 5.76 5.49 5.07 3.93 1984-2012 Residential Price 20.61 21.07 20.18 17.89 18.16 18.31 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 98.0 97.7 1989-2012 Commercial Price 13.07 14.45 11.09 10.60 11.14 10.41 1967-2012 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 38.5 37.0 1990-2012 Industrial Price 10.56 11.72 9.41 8.33 8.07 6.96 1997-2012 Percentage of Total Industrial Deliveries included in Prices 3.1 3.0 3.2 3.0 3.0 2.7 1997-2012 Vehicle Fuel Price 12.82 15.56 13.16 17.98 5.56 9.83 1989-2012

383

Utah Gasoline Price Data  

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

Utah Utah Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Layton LaytonGasPrices.com Automotive.com MapQuest.com Ogden OgdenGasPrices.com Automotive.com MapQuest.com Orem OremGasPrices.com Automotive.com MapQuest.com Provo ProvoGasPrices.com Automotive.com MapQuest.com Salt Lake City SaltLakeCityGasPrices.com Automotive.com MapQuest.com Sandy SandyGasPrices.com Automotive.com MapQuest.com West Jordan WestJordanGasPrices.com Automotive.com MapQuest.com West Valley City WestValleyCityGasPrices.com Other Utah Cities UtahGasPrices.com (search by city or ZIP code) - GasBuddy.com Utah Gas Prices (selected cities) - GasBuddy.com

384

Connecticut Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.67 10.24 6.81 6.58 5.92 5.12 1984-2012 Residential Price 16.39 17.85 14.81 14.93 13.83 14.17 1967-2012 Percentage of Total Residential Deliveries included in Prices 98.2 97.7 97.5 97.3 96.8 96.7 1989-2012 Commercial Price 12.61 13.81 9.92 9.55 8.48 8.40 1967-2012 Percentage of Total Commercial Deliveries included in Prices 71.5 70.7 69.0 65.4 65.4 65.1 1990-2012 Industrial Price 10.54 12.63 8.44 9.60 9.16 8.83 1997-2012 Percentage of Total Industrial Deliveries included in Prices 50.0 47.3 37.5 31.1 31.0 32.3 1997-2012 Vehicle Fuel Price 20.57 24.04 15.26 16.31 18.59 13.70 1992-2012 Electric Power Price 7.81 10.48 4.89 5.70 5.09 3.99 1997-2012

385

Oregon Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.27 5.33 4.00 4.92 1979-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.14 8.82 7.79 6.78 5.84 5.21 1984-2012 Residential Price 14.65 13.89 14.52 12.49 11.76 11.22 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 12.36 11.57 11.86 10.10 9.60 8.91 1967-2012 Percentage of Total Commercial Deliveries included in Prices 98.5 98.5 98.4 97.4 97.4 96.9 1990-2012 Industrial Price 9.30 9.07 9.70 7.05 6.84 5.87 1997-2012 Percentage of Total Industrial Deliveries included in Prices 21.8 20.1 18.9 17.1 17.1 16.7 1997-2012 Vehicle Fuel Price 6.59 8.03 7.11 5.61 4.23 4.57 1992-2012

386

Arizona Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.98 7.09 3.19 4.11 1967-2010 Exports Price 6.94 8.09 3.79 4.57 4.28 3.07 1989-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.25 8.49 7.21 6.59 5.91 4.68 1984-2012 Residential Price 17.21 17.60 17.65 15.87 15.04 15.75 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 12.84 13.01 12.15 10.72 9.99 9.35 1967-2012 Percentage of Total Commercial Deliveries included in Prices 93.4 93.1 88.0 88.7 87.8 86.6 1990-2012 Industrial Price 10.49 10.47 8.19 7.54 6.86 5.78 1997-2012 Percentage of Total Industrial Deliveries included in Prices 31.3 29.6 29.1 25.5 24.2 21.4 1997-2012

387

Colorado Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 4.57 6.94 3.21 3.96 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.23 6.98 5.09 5.26 4.94 4.26 1984-2012 Residential Price 8.84 9.77 8.80 8.13 8.25 8.31 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 8.10 9.01 7.56 7.58 7.84 7.58 1967-2012 Percentage of Total Commercial Deliveries included in Prices 95.7 95.2 94.8 94.6 93.8 92.2 1990-2012 Industrial Price 7.21 8.76 6.57 5.84 6.42 5.79 1997-2012 Percentage of Total Industrial Deliveries included in Prices 0.5 0.6 0.5 5.2 7.5 6.8 1997-2012 Vehicle Fuel Price 8.72 13.57 9.12 10.79 9.56 11.65 1990-2012

388

Alaska Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.63 7.39 2.93 3.17 1967-2010 Exports Price 6.21 7.69 8.59 12.19 12.88 15.71 1989-2012 Pipeline and Distribution Use Price 1970-2005 Citygate Price 6.75 6.74 8.22 6.67 6.53 6.14 1988-2012 Residential Price 8.68 8.72 10.23 8.89 8.77 8.47 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 7.57 8.66 9.51 8.78 8.09 8.09 1967-2012 Percentage of Total Commercial Deliveries included in Prices 76.0 74.9 85.3 87.7 88.6 94.9 1990-2012 Industrial Price 4.67 5.49 4.02 4.23 3.84 5.11 1997-2012 Percentage of Total Industrial Deliveries included in Prices 70.0 78.2 72.5 70.5 60.8 100.0 1997-2012

389

Kansas Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.69 6.85 3.16 4.23 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.27 8.85 6.12 6.08 5.53 4.74 1984-2012 Residential Price 12.97 13.00 11.10 10.61 9.93 10.13 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 12.04 12.24 10.01 9.65 8.89 8.82 1967-2012 Percentage of Total Commercial Deliveries included in Prices 64.8 64.9 65.7 66.0 62.6 59.7 1990-2012 Industrial Price 7.17 9.42 4.59 5.49 5.28 3.95 1997-2012 Percentage of Total Industrial Deliveries included in Prices 5.9 7.8 6.7 7.0 9.5 8.8 1997-2012 Vehicle Fuel Price -- -- -- -- 9.87 9.00 1994-2012

390

Automatic generation of dynamic virtual fences as part of BIM-based prevention program for construction safety  

Science Conference Proceedings (OSTI)

The present research aims to investigate a new method for the automatic generation of Dynamic Virtual Fences (DVFs) as part of a BIM-based prevention program for construction safety following the Safety Code of Quebec Provence in Canada. First, the Safety ...

Amin Hammad; Shayan Setayeshgar; Cheng Zhang; Yoosef Asen

2012-12-01T23:59:59.000Z

391

prices | OpenEI  

Open Energy Info (EERE)

prices prices Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is Table 12, and contains only the reference case. The dataset uses 2009 dollars per gallon. The data is broken down into crude oil prices, residential, commercial, industrial, transportation, electric power and refined petroleum product prices. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Petroleum prices Data application/vnd.ms-excel icon AEO2011: Petroleum Product Prices- Reference Case (xls, 129.9 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period 2008-2035

392

Retail Motor Gasoline Prices*  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: Gasoline pump prices have backed down from the high prices experienced last summer and fall. The retail price for regular motor gasoline fell 11 cents per gallon from September to December. However, with crude oil prices rebounding somewhat from their December lows combined with lower than normal stock levels, we project that prices at the pump will rise modestly as the 2001 driving season begins this spring. For the summer of 2001, we expect only a little difference from the average price of $1.50 per gallon seen during the previous driving season, as motor gasoline stocks going into the driving season are projected to be slightly less than they were last year. The situation of relatively low inventories for gasoline could set the stage for some regional imbalances in supply that could once again

393

Using Environmental Emissions Permit Prices to Raise Electricity Prices: Evidence from the California Electricity Market  

E-Print Network (OSTI)

Permit Prices to Raise Electricity Prices: Evidence from thePermit Prices to Raise Electricity Prices: Evidence from thehigher wholesale electricity prices, during the third and

Kolstad, Jonathan; Wolak, Frank

2003-01-01T23:59:59.000Z

394

The long-run evolution of energy prices  

E-Print Network (OSTI)

I examine the long-run behavior of oil, coal, and natural gas prices, using up to 127 years of data, and address the following questions: What does over a century of data tell us about the stochastic dynamics of price ...

Pindyck, Robert S.

1999-01-01T23:59:59.000Z

395

Transmission Price Risk Management  

Science Conference Proceedings (OSTI)

This report is concerned with the financial risks that arise from the uncertain price of transmission service in restructured or competitive electricity markets. These risks are most severe in markets with locational pricing (LMP), but they also exist in more traditionally organized electricity markets. This report has two main purposes. The first is to review the existing mathematical models of electricity price formation in spot and forward markets that may be helpful as the foundations for developing ...

2006-12-04T23:59:59.000Z

396

Iowa Gasoline Price Data  

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

Iowa Iowa Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Ames AmesGasPrices.com Automotive.com MapQuest.com Cedar Rapids CedarRapidsGasPrices.com Automotive.com MapQuest.com Council Bluffs CouncilBluffsGasPrices.com Automotive.com MapQuest.com Des Moines DesMoinesGasPrices.com Automotive.com MapQuest.com Dubuque DubuqueGasPrices.com Automotive.com MapQuest.com Iowa City IowaCityGasPrices.com Automotive.com MapQuest.com Quad Cities QuadCitiesGasPrices.com Sioux City SiouxCityGasPrices.com Automotive.com MapQuest.com Waterloo WaterlooGasPrices.com Automotive.com MapQuest.com Other Iowa Cities

397

Louisiana Gasoline Price Data  

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

Louisiana Louisiana Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Baton Rouge BatonRougeGasPrices.com Automotive.com MapQuest.com Lafayette LafayetteGasPrices.com Automotive.com MapQuest.com Lake Charles LakeCharlesGasPrices.com Automotive.com MapQuest.com Metairie MetairieGasPrices.com Automotive.com MapQuest.com Monroe MonroeGasPrices.com Automotive.com MapQuest.com New Orleans NewOrleansGasPrices.com Automotive.com Mapquest.com Shreveport ShreveportGasPrices.com Automotive.com MapQuest.com Other Louisiana Cities LouisianaGasPrices.com (search by city or ZIP code) - GasBuddy.com Louisiana Gas Prices (selected cities) - GasBuddy.com

398

Utah Natural Gas Prices  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Prices are in ...

399

California Gasoline Price Data  

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

California California Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Bakersfield BakersfieldGasPrices.com Automotive.com MapQuest.com Fresno FresnoGasPrices.com Automotive.com MapQuest.com Los Angeles LosAngelesGasPrices.com Automotive.com MapQuest.com Modesto ModestoGasPrices.com Automotive.com MapQuest.com Oakland OaklandGasPrices.com Automotive.com MapQuest.com Orange County OrangeCountyGasPrices.com Automotive.com MapQuest.com Riverside RiversideGasPrices.com Automotive.com MapQuest.com San Bernardino SanBernardinoGasPrices.com Automotive.com MapQuest.com San Diego SanDiegoGasPrices.com Automotive.com MapQuest.com

400

Michigan Gasoline Price Data  

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

Michigan Michigan Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Ann Arbor AnnArborGasPrices.com Automotive.com MapQuest.com Battle Creek BattleCreekGasPrices.com Automotive.com MapQuest.com Detroit DetroitGasPrices.com Automotive.com MapQuest.com Flint FlintGasPrices.com Automotive.com MapQuest.com Grand Rapids GrandRapidsGasPrices.com Automotive.com MapQuest.com Kalamazoo KalamazooGasPrices.com Automotive.com MapQuest.com Lansing LansingGasPrices.com Automotive.com MapQuest.com Sterling Heights SterlingHeightsGasPrices.com Automotive.com MapQuest.com Other Michigan Cities MichiganGasPrices.com (search by city or ZIP code) - GasBuddy.com

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Natural Gas Exports Price  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Prices are in ...

402

Natural Gas Wellhead Price  

Annual Energy Outlook 2012 (EIA)

Wellhead Price Marketed Production Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By:...

403

,"Wisconsin Natural Gas Prices"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Wisconsin Natural Gas Prices",8,"Monthly","72013","1151989" ,"Release Date:","9302013"...

404

,"Texas Natural Gas Prices"  

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

,"Workbook Contents" ,"Texas Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

405

Residential Price - Marketers  

U.S. Energy Information Administration (EIA)

Average Price of Natural Gas Delivered to Residential and Commercial Consumers by Local Distribution and Marketers in Selected States (Dollars per Thousand Cubic Feet ...

406

Crude Oil Prices  

Annual Energy Outlook 2012 (EIA)

Information AdministrationPetroleum Marketing Annual 1999 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

407

Crude Oil Prices  

Annual Energy Outlook 2012 (EIA)

Information AdministrationPetroleum Marketing Annual 2000 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

408

Crude Oil Prices  

Annual Energy Outlook 2012 (EIA)

Information AdministrationPetroleum Marketing Annual 1998 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

409

Crude Oil Prices  

Gasoline and Diesel Fuel Update (EIA)

Information AdministrationPetroleum Marketing Annual 2001 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

410

Price-Anderson Act  

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

The Price-Anderson Act (PAA) provides a system of indemnification for legal liability resulting from a nuclear incident in connection with contractual activity for DOE.

411

,"Pennsylvania Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Prices",8,"Monthly","72013","1151989" ,"Release Date:","9302013" ,"Next Release...

412

Idaho Natural Gas Prices  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Prices are in ...

413

,"Idaho Natural Gas Prices"  

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

,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Idaho Natural Gas Prices",8,"Monthly","102013","1151989" ,"Release Date:","172014"...

414

Natural Gas Citygate Price  

U.S. Energy Information Administration (EIA)

... electric power price data are for regulated electric ... Gas volumes delivered for vehicle fuel are included in the State monthly totals from January ...

415

Crude Price & Differential  

U.S. Energy Information Administration (EIA)

... , making it more competitive with other boiler fuels, and the price of residual fuel relative to crude oil increases. Thus, both the light ...

416

Colorado Natural Gas Prices  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Prices are in ...

417

Retail Propane Prices  

Gasoline and Diesel Fuel Update (EIA)

19 Notes: Residential propane prices rose fairly strongly during the 1999-2000 heating season, gaining nearly 25 cents per gallon between October and March. Unfortunately,...

418

CA Following World Prices  

U.S. Energy Information Administration (EIA)

Light-heavy crude differentials fell and stayed down until the later part of 1997. Crude prices continued to weaken, but the light heavy difference ...

419

,"Wyoming Natural Gas Prices"  

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

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

420

,"Iowa Natural Gas Prices"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Iowa Natural Gas Prices",10,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

Note: This page contains sample records for the topic "dynamic pricing programs" 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

,"Nebraska Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Nebraska Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

422

,"Vermont Natural Gas Prices"  

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

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Vermont Natural Gas Prices",10,"Annual",2012,"6301980" ,"Release Date:","10312013" ,"Next Release...

423

,"Ohio Natural Gas Prices"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

424

,"California Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Prices",13,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

425

,"Wisconsin Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Wisconsin Natural Gas Prices",10,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

426

,"Maryland Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Maryland Natural Gas Prices",12,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

427

,"Michigan Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Prices",13,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

428

,"Illinois Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

429

,"Kansas Natural Gas Prices"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

430

,"Arkansas Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Arkansas Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

431

,"Texas Natural Gas Prices"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Prices",13,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

432

,"Arizona Natural Gas Prices"  

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

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Arizona Natural Gas Prices",12,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

433

,"Minnesota Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Minnesota Natural Gas Prices",12,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

434

,"Florida Natural Gas Prices"  

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

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

435

,"Tennessee Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Tennessee Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

436

,"Colorado Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

437

,"Virginia Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Virginia Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

438

,"Oklahoma Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

439

,"Washington Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Washington Natural Gas Prices",12,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

440

,"Maine Natural Gas Prices"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Maine Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

Note: This page contains sample records for the topic "dynamic pricing programs" 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

,"Louisiana Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Prices",13,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

442

,"Utah Natural Gas Prices"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

443

,"Oregon Natural Gas Prices"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oregon Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

444

,"Mississippi Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi Natural Gas Prices",12,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

445

,"Massachusetts Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Massachusetts Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

446

,"Nevada Natural Gas Prices"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Nevada Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

447

,"Delaware Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Delaware Natural Gas Prices",10,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

448

,"Pennsylvania Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

449

,"Kentucky Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

450

,"Montana Natural Gas Prices"  

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

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Prices",13,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

451

,"Idaho Natural Gas Prices"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Idaho Natural Gas Prices",12,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

452

,"Missouri Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Missouri Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

453

,"Georgia Natural Gas Prices"  

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

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Georgia Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

454

,"Indiana Natural Gas Prices"  

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

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Indiana Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

455

,"Alabama Natural Gas Prices"  

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

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Alabama Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

456

,"Connecticut Natural Gas Prices"  

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

Of Series","Frequency","Latest Data for" ,"Data 1","Connecticut Natural Gas Prices",10,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

457

,"Alaska Natural Gas Prices"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Alaska Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

458

,"Hawaii Natural Gas Prices"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Hawaii Natural Gas Prices",8,"Annual",2012,"6301980" ,"Release Date:","10312013" ,"Next Release...

459

,"Iowa Natural Gas Prices"  

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

,"Workbook Contents" ,"Iowa Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data...

460

,"Alabama Natural Gas Prices"  

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

,"Workbook Contents" ,"Alabama Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

Note: This page contains sample records for the topic "dynamic pricing programs" 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

,"Georgia Natural Gas Prices"  

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

,"Workbook Contents" ,"Georgia Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

462

,"Connecticut Natural Gas Prices"  

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

,"Workbook Contents" ,"Connecticut Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

463

,"Colorado Natural Gas Prices"  

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

,"Workbook Contents" ,"Colorado Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

464

,"California Natural Gas Prices"  

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

,"Workbook Contents" ,"California Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

465

,"Florida Natural Gas Prices"  

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

,"Workbook Contents" ,"Florida Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

466

,"Arkansas Natural Gas Prices"  

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

,"Workbook Contents" ,"Arkansas Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

467

,"Arizona Natural Gas Prices"  

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

,"Workbook Contents" ,"Arizona Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

468

,"Alaska Natural Gas Prices"  

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

,"Workbook Contents" ,"Alaska Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

469

,"Delaware Natural Gas Prices"  

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

,"Workbook Contents" ,"Delaware Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

470

,"Hawaii Natural Gas Prices"  

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

,"Workbook Contents" ,"Hawaii Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

471

Extending Tcl for Dynamic ObjectOriented Programming \\Lambda Proceedings of the Tcl/Tk Workshop 95, Toronto, Ontario, July 1995, modified for OTcl 0.95  

E-Print Network (OSTI)

Extending Tcl for Dynamic Object­Oriented Programming \\Lambda Proceedings of the Tcl/Tk Workshop 95 Abstract Object Tcl is an extension to the Tool Command Language (Tcl) for the management of complicated to other object­oriented programming extensions (in­ cluding [incr Tcl]) because it may be used dynam

Wetherall, David

472

Information-Based Asset Pricing  

E-Print Network (OSTI)

A new framework for asset price dynamics is introduced in which the concept of noisy information about future cash flows is used to derive the price processes. In this framework an asset is defined by its cash-flow structure. Each cash flow is modelled by a random variable that can be expressed as a function of a collection of independent random variables called market factors. With each such "X-factor" we associate a market information process, the values of which are accessible to market agents. Each information process is a sum of two terms; one contains true information about the value of the market factor; the other represents "noise". The noise term is modelled by an independent Brownian bridge. The market filtration is assumed to be that generated by the aggregate of the independent information processes. The price of an asset is given by the expectation of the discounted cash flows in the risk-neutral measure, conditional on the information provided by the market filtration. When the cash flows are th...

Brody, Dorje C; Macrina, Andrea

2007-01-01T23:59:59.000Z

473

Retrospective Evaluation of Appliance Price Trends  

E-Print Network (OSTI)

the higher the product cost and retail price. Table 3.change and appliance price Room air conditioners Small (price data to clarify price

Dale, Larry

2010-01-01T23:59:59.000Z

474

Retrospective Evaluation of Appliance Price Trends  

E-Print Network (OSTI)

analyses to generate price trends more accurately. 8.Evaluation of Appliance Price Trends Larry Dale, Camillewith regard to overall price trends and relative price of

Dale, Larry

2010-01-01T23:59:59.000Z

475

The Long-Run Evolution of Energy Prices  

E-Print Network (OSTI)

Abstract: I examine the long-run behavior of oil, coal, and natural gas prices, using up to 127 years of data, and address the following questions: What does over a century of data tell us about the stochastic dynamics of price evolution, and how it should be modeled? Can models of reversion to stochastically fluctuating trend lines help us forecast prices over horizons of 20 years or more? And what do the answers to these questions tell us about investment decisions that are dependent on prices and their stochastic evolution?

Robert S. Pindyck

1999-01-01T23:59:59.000Z

476

Price discovery and information linkages in the emission allowance and energy markets .  

E-Print Network (OSTI)

??We provide the first evidence on the catalysts for price discovery in the European Union Emissions Trading System. Short-run return dynamics are analysed using a… (more)

Swieringa, John Edward

2013-01-01T23:59:59.000Z

477

Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S.  

E-Print Network (OSTI)

contractual, energy and market-related characteristics. Afunction of local energy-market and weather characteristicslocal-level wholesale energy market price dynamics and local

Jaffee, Dwight; Stanton, Richard; Wallace, Nancy

2012-01-01T23:59:59.000Z

478

Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S.  

E-Print Network (OSTI)

contractual, energy and market-related characteristics. Alocal-level wholesale energy market price dynamics and localexpenses, and energy factor market inputs. In a companion

Jaffee, Dwight M.; Stanton, Richard; Wallace, Nancy E.

2010-01-01T23:59:59.000Z

479

A statistical analysis of the natural gas futures market : the interplay of sentiment, volatility and prices.  

E-Print Network (OSTI)

??This paper attempts to understand the price dynamics of the North American natural gas market through a statistical survey that includes an analysis of the… (more)

Fazzio, Thomas J. (Thomas Joseph)

2010-01-01T23:59:59.000Z

480

Minnesota Natural Gas Prices  

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

4.43 4.50 4.68 1989-2013 Residential Price 7.52 7.29 7.42 7.50 8.15 NA 1989-2013 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0...

Note: This page contains sample records for the topic "dynamic pricing programs" 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

Tennessee Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

5.23 4.35 1984-2012 Residential Price 13.42 14.20 12.15 10.46 10.21 9.98 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0...

482

Delaware Natural Gas Prices  

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

6.56 8.19 1989-2013 Residential Price 12.80 12.32 12.19 12.38 13.12 16.23 1989-2013 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0...

483

Mississippi Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

4.14 4.73 4.83 1989-2013 Residential Price 8.72 8.06 8.20 7.83 8.65 10.14 1989-2013 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0...

484

Washington Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

4.76 5.86 1989-2013 Residential Price 10.58 10.47 10.67 10.90 11.20 13.02 1989-2013 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0...

485

Oklahoma Natural Gas Prices  

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

5.67 5.00 1984-2012 Residential Price 12.06 12.32 11.39 11.12 10.32 11.14 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0...

486

Alabama Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

4.80 5.11 1989-2013 Residential Price 15.39 14.44 14.29 NA 15.40 18.40 1989-2013 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0...

487

Oklahoma Natural Gas Prices  

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

4.65 4.73 5.23 1989-2013 Residential Price 9.20 7.65 8.36 8.01 9.27 11.81 1989-2013 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0...

488

Maryland Natural Gas Prices  

Annual Energy Outlook 2012 (EIA)

6.17 7.02 1989-2013 Residential Price NA 10.78 10.30 10.42 12.70 15.65 1989-2013 Percentage of Total Residential Deliveries included in Prices NA 76.5 75.4 75.2 72.9 70.8...

489

Louisiana Natural Gas Prices  

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

4.60 4.62 1989-2013 Residential Price 10.19 8.87 9.52 9.06 10.68 12.47 1989-2013 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0...

490

Missouri Natural Gas Prices  

Annual Energy Outlook 2012 (EIA)

4.34 5.72 6.25 1989-2013 Residential Price 9.95 8.72 9.05 9.12 10.74 12.84 1989-2013 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0...

491

California Natural Gas Prices  

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

9.43 9.92 9.93 9.22 1967-2012 Percentage of Total Residential Deliveries included in Prices 99.5 99.3 98.9 98.5 98.3 97.4 1989-2012 Commercial Price 10.20 11.75 7.75 8.30 8.28...

492

Michigan Natural Gas Prices  

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

11.32 10.47 9.96 1967-2012 Percentage of Total Residential Deliveries included in Prices 94.5 94.0 93.7 91.9 92.1 NA 1989-2012 Commercial Price 10.02 10.66 9.38 8.95 9.14 8.34...

493

Utility spot pricing, California  

E-Print Network (OSTI)

The objective of the present spot pricing study carried out for SCE and PG&E is to develop the concepts which wculd lead to an experimental design for spot pricing in the two utilities. The report suggests a set of experiments ...

Schweppe, Fred C.

1982-01-01T23:59:59.000Z

494

High Electricity Prices  

E-Print Network (OSTI)

Generators supplying electricity markets are subject to volatile input and output prices and uncertain fuel availability. Price-risk may be hedged to a considerable extent but fuel-risk — water flows in the case of hydro and gas availability in the case of thermal plants — may not be. We show that a price-taking generator will only generate when the output price exceeds its marginal cost by an amount that reflects the value of the option to delay the use of stored fuel. The corresponding offer price is different from the theorized offer prices of static uniform auctions and more akin to pay-as-bid auction prices. We argue that the option value of delaying fuel use, which is an increasing function of spot price volatility and the uncertainty about fuel availability, must be considered when evaluating whether market power is present in electricity markets. The engineering approach to simulating an electricity supply curve, which has been used in market power evaluations to date, may lead to supply curves that are quite different from those that recognize possible fuel availability limitations, even in the complete absence of market power.

Kevin Counsell; Graeme Guthrie; Steen Videbeck

2006-01-01T23:59:59.000Z

495

Connecticut Natural Gas Prices  

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

15.45 18.00 18.88 1989-2013 Percentage of Total Residential Deliveries included in Prices 97.3 96.9 96.3 96.3 96.6 96.4 2002-2013 Commercial Price 8.24 7.71 8.57 8.59 8.19 8.51...

496

Utah Natural Gas Prices  

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

8.95 8.22 8.44 NA 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 8.03 7.74 7.57 6.83...

497

Colorado Natural Gas Prices  

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

8.80 8.13 8.25 8.26 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 8.10 9.01 7.56 7.58...

498

Illinois Natural Gas Prices  

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

14.56 15.62 15.52 1989-2013 Percentage of Total Residential Deliveries included in Prices 87.5 84.9 83.4 84.8 86.6 86.7 2002-2013 Commercial Price 7.04 8.26 NA 12.27 12.69...

499

Hawaii Natural Gas Prices  

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

44.50 55.28 52.86 1980-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 28.31 39.01 30.00 36.55...

500

Hawaii Natural Gas Prices  

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

46.54 48.35 47.10 1989-2013 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2013 Commercial Price 47.66 44.78 42.04 39.71...