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Impact of demand-response on the efficiency and prices in real-time electricity markets

Published: 11 June 2014 Publication History

Abstract

We study the effect of Demand-Response (DR) in dynamic real-time electricity markets. We use a two-stage market model that takes into account the dynamical aspects of generation, demand, and DR. We study the real-time market prices in two scenarios: in the former, consumers anticipate or delay their flexible loads in reaction to market prices; in the latter, the flexible loads are controlled by an independent aggregator. For both scenarios, we show that, when users are price-takers, any competitive equilibrium is efficient: the players' selfish responses to prices coincide with a socially optimal policy. Moreover, the price process is the same in all scenarios. For the numerical evaluation of the properties of the equilibrium, we develop a solution technique based on the Alternating Direction Method of Multipliers (ADMM) and trajectorial forecasts. The forecasts are computed using wind generation data from the UK. We challenge the assumption that all players have full information. If the assumption is verified, then, as expected, the social welfare increases with the amount of DR available, since DR relaxes the ramping constraints of generation. However, if the day-ahead market cannot observe how elastic loads are affected by DR, a large quantity of DR can be detrimental and leads to a decrease in the welfare. Furthermore, the DR operator has an incentive to under-dimension the quantity of available DR. Finally, we compare DR with an actual energy storage system. We find that storage has a faster response-time and thus performs better when only a limited amount is installed. However, storage suffers from charge-discharge inefficiency: with DR, prices do concentrate on marginal cost (for storage, they do not) and provide a better welfare.

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Cited By

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  • (2019)Model Predictive Power Dispatch and Control With Price-Elastic Load in Energy InternetIEEE Transactions on Industrial Informatics10.1109/TII.2018.286324115:3(1775-1787)Online publication date: Mar-2019
  • (2016)Mean-Field Limits Beyond Ordinary Differential EquationsAdvanced Lectures of the 16th International School on Formal Methods for the Quantitative Evaluation of Collective Adaptive Systems - Volume 970010.1007/978-3-319-34096-8_3(61-82)Online publication date: 20-Jun-2016
  • (2015)Distributed Multi-Period Optimal Power Flow for Demand Response in MicrogridsProceedings of the 2015 ACM Sixth International Conference on Future Energy Systems10.1145/2768510.2768534(17-26)Online publication date: 14-Jul-2015
  • Show More Cited By

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cover image ACM Conferences
e-Energy '14: Proceedings of the 5th international conference on Future energy systems
June 2014
326 pages
ISBN:9781450328197
DOI:10.1145/2602044
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publication History

Published: 11 June 2014

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Author Tags

  1. demand-response
  2. electricity pricing
  3. energy economics
  4. market efficiency

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e-Energy '14 Paper Acceptance Rate 23 of 112 submissions, 21%;
Overall Acceptance Rate 160 of 446 submissions, 36%

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Cited By

View all
  • (2019)Model Predictive Power Dispatch and Control With Price-Elastic Load in Energy InternetIEEE Transactions on Industrial Informatics10.1109/TII.2018.286324115:3(1775-1787)Online publication date: Mar-2019
  • (2016)Mean-Field Limits Beyond Ordinary Differential EquationsAdvanced Lectures of the 16th International School on Formal Methods for the Quantitative Evaluation of Collective Adaptive Systems - Volume 970010.1007/978-3-319-34096-8_3(61-82)Online publication date: 20-Jun-2016
  • (2015)Distributed Multi-Period Optimal Power Flow for Demand Response in MicrogridsProceedings of the 2015 ACM Sixth International Conference on Future Energy Systems10.1145/2768510.2768534(17-26)Online publication date: 14-Jul-2015
  • (undefined)American Call Options for Power System BalancingSSRN Electronic Journal10.2139/ssrn.2508258

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