A Game-Theoretic Framework for Multiperiod-Multicompany Demand Response Management in the Smart Grid

By utilizing tools from the game theory, we develop a novel multiperiod-multicompany demand response framework considering the interactions between companies (sellers of energy) and their consumers (buyers of energy). We model the interactions in terms of a Stackelberg game, where companies set thei...

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Veröffentlicht in:	IEEE transactions on control systems technology Jg. 29; H. 3; S. 1019 - 1034
Hauptverfasser:	Alshehri, Khaled, Liu, Ji, Chen, Xudong, Basar, Tamer
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.05.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Closed form solutions Companies Consumers Demand side management Demand-side management (DSM) Distributed algorithms Energy consumption Energy management Equilibrium Exact solutions Game theory Games Incentives Load management power system economics Smart grid Smart grids Subdivisions Uniqueness Utilities
ISSN:	1063-6536, 1558-0865
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Abstract	By utilizing tools from the game theory, we develop a novel multiperiod-multicompany demand response framework considering the interactions between companies (sellers of energy) and their consumers (buyers of energy). We model the interactions in terms of a Stackelberg game, where companies set their prices and consumers respond by choosing their demands. We show that the underlying game has a unique equilibrium at which the companies maximize their revenues, while the consumers maximize their utilities subject to their local constraints. Closed-form expressions are provided for the optimal strategies of all players. Based on these solutions, a power-allocation game has been formulated, which is shown to admit a unique pure-strategy Nash equilibrium, for which closed-form expressions are also provided. This equilibrium is found under the assumption that companies can freely allocate their power across the time horizon, but we also demonstrate that it is possible to relax this assumption. We further provide a fast distributed algorithm for the computation of all optimal strategies using only local information. We also study the effect of variations in the number of periods (subdivisions of the time horizon) and the number of consumers. As a consequence, we are able to find an appropriate company-to-consumer ratio when the number of consumers participating in demand response exceeds some threshold. Furthermore, we show, both analytically and numerically, that the multiperiod scheme provides incentives for energy consumers to participate in demand response compared with the single-period framework studied by Maharjan et al. In our framework, we provide a condition for the minimum budget consumers need and carry out case studies using real-life data to demonstrate the benefits of the approach, which show potential savings of up to 30% and equilibrium prices that have low volatility.
AbstractList	By utilizing tools from the game theory, we develop a novel multiperiod-multicompany demand response framework considering the interactions between companies (sellers of energy) and their consumers (buyers of energy). We model the interactions in terms of a Stackelberg game, where companies set their prices and consumers respond by choosing their demands. We show that the underlying game has a unique equilibrium at which the companies maximize their revenues, while the consumers maximize their utilities subject to their local constraints. Closed-form expressions are provided for the optimal strategies of all players. Based on these solutions, a power-allocation game has been formulated, which is shown to admit a unique pure-strategy Nash equilibrium, for which closed-form expressions are also provided. This equilibrium is found under the assumption that companies can freely allocate their power across the time horizon, but we also demonstrate that it is possible to relax this assumption. We further provide a fast distributed algorithm for the computation of all optimal strategies using only local information. We also study the effect of variations in the number of periods (subdivisions of the time horizon) and the number of consumers. As a consequence, we are able to find an appropriate company-to-consumer ratio when the number of consumers participating in demand response exceeds some threshold. Furthermore, we show, both analytically and numerically, that the multiperiod scheme provides incentives for energy consumers to participate in demand response compared with the single-period framework studied by Maharjan et al. In our framework, we provide a condition for the minimum budget consumers need and carry out case studies using real-life data to demonstrate the benefits of the approach, which show potential savings of up to 30% and equilibrium prices that have low volatility.
Author	Liu, Ji Basar, Tamer Alshehri, Khaled Chen, Xudong
Author_xml	– sequence: 1 givenname: Khaled orcidid: 0000-0001-9761-0830 surname: Alshehri fullname: Alshehri, Khaled email: kalshehri@kfupm.edu.sa organization: Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia – sequence: 2 givenname: Ji orcidid: 0000-0003-2871-9888 surname: Liu fullname: Liu, Ji email: ji.liu@stonybrook.edu organization: Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA – sequence: 3 givenname: Xudong orcidid: 0000-0002-0135-0606 surname: Chen fullname: Chen, Xudong email: xudong.chen@colorado.edu organization: Department of Electrical, Computer, and Energy Engineering, University of Colorado Boulder, Boulder, CO, USA – sequence: 4 givenname: Tamer orcidid: 0000-0003-4406-7875 surname: Basar fullname: Basar, Tamer email: basar1@illinois.edu organization: Department of Electrical and Computer Engineering, University of Illinois at Urbana--Champaign, Urbana, IL, USA
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SubjectTerms	Algorithms Closed form solutions Companies Consumers Demand side management Demand-side management (DSM) Distributed algorithms Energy consumption Energy management Equilibrium Exact solutions Game theory Games Incentives Load management power system economics Smart grid Smart grids Subdivisions Uniqueness Utilities
Title	A Game-Theoretic Framework for Multiperiod-Multicompany Demand Response Management in the Smart Grid
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