Demand Elasticity in the California Power Exchange Day-Ahead Market

Earle, Robert

doi:10.1016/s1040-6190(00)00145-7

Cited by 19 publications

(10 citation statements)

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“…Electricity price for low demand and peak demand scenarios [3] Fig. 5. The mechanism which leads to price spikes in the markets due to insufficient electricity generation [3] Now let's see what happens if a part of demand-side has the ability to response to the price variations.…”

Section: Consumers Behavior In the Smart Grid Environmentmentioning

confidence: 99%

Demand-side behavior in the smart grid environment

Moshari

Yousefi

Ebrahimi

et al. 2010

2010 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

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Recent developments in traditional power systems which involve emerging smart technologies and widely employing of communication will convert the present electricity grids into the smart grids. The future smart and efficient power systems will treat completely different compare with the existing power systems. This paper discusses the effect of emerging smart grids on the consumer's behavior. It investigates the responses of different types of consumers to the spot electricity price and the price elasticity of demand in the smart grid environment. Smart technologies could bring all of the consumers with any level of demand to the market actively, and results in increasing the efficiency of the market in a fully competitive electricity market. This paper also describes the effect of Demand Response (DR) on some electricity market issues like short-term load and price forecasting, generation expansion, and imperfect competition, in the smart grid environment. The qualitative discussions show that by emerging the smart grids the market efficiency, costumer's benefits, and Demand Response of the power system are improved and the ability of strategic players to exert market power will be reduced. Index Terms-Advanced Metering Infrastructure (AMI), Demand Response (

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Section: Consumers Behavior In the Smart Grid Environmentmentioning

confidence: 99%

Demand-side behavior in the smart grid environment

Moshari

Yousefi

Ebrahimi

et al. 2010

2010 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

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“…Mathematically (1) where and are, respectively, the consumer gross surplus and the system operating cost at period , and is the number of periods in the optimization horizon. If the generators or the consumers do not bid at their respective marginal costs or benefits, the objective function is not the social welfare but the "perceived" social welfare [11].…”

Section: A Objective Functionmentioning

confidence: 99%

“…While there are some good practical reasons for this difference, it is widely acknowledged that a more active participation in the market by the demand side could have significant benefits. In particular [1]- [6]:…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Effect of Demand Response on Electricity Markets

Kirschen

2009

IEEE Trans. Power Syst.

395

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It is widely agreed that an increased participation of the demand side in the electricity markets would produce benefits not only for the individual consumers but also for the market as a whole. This paper proposes a method for quantifying rigorously the effect that such an increase would have on the various categories of market participants. A new centralized complex-bid market-clearing mechanism has been devised to take into consideration the load shifting behavior of consumers who do submit price-sensitive bids. The effects of the proportion of demand response on the market are illustrated using a test system with ten generating units scheduled over 24 periods.

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“…Demand bidding can be considered as a subcategory from market-based programs category of demand response [5]. A wide range of literature has focused either on the measurement of load elasticity [6][7][8][9] or on the impacts of price responsiveness of loads on electricity prices in power markets [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of price‐sensitive loads’ impacts on transmission network congestion using an analytical approach

Sadr

Mashhadi

2015

IET Generation, Transmission & Distribution

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An analytical approach is presented to evaluate the impacts of price-sensitive loads on congestion in transmission network. To achieve this aim, the Lagrange multipliers (LMs) of transmission lines' power flow constraints are calculated from independent system operator's social welfare maximisation in which demand-side bidding is considered. It is shown that the LM of each congested line can be decomposed into five components. The first part is a constant value for the specified line, while the next two components are associated to generating units and the last two constitutive parts are related to load service entities (LSEs). The proposed decomposition obtains considerable information regarding the impacts of price-sensitive loads on congestion in transmission network. First, the sensitivity of congestion degree of each congested line to the bidding strategies and maximum price-sensitive demand of LSEs are indicated by weighting coefficients of the last two terms in the decomposed LM. Furthermore, the decomposition of LM to the constitutive components reveals the contribution of each generating unit and LSE to the congestion of corresponding line. The simulation results on a test system confirm the efficiency of the proposed approach.

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Demand Elasticity in the California Power Exchange Day-Ahead Market

Cited by 19 publications

References 0 publications

Demand-side behavior in the smart grid environment

Demand-side behavior in the smart grid environment

Quantifying the Effect of Demand Response on Electricity Markets

Evaluation of price‐sensitive loads’ impacts on transmission network congestion using an analytical approach

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