A game theory approach for maximum utilization of wind power by DR in residential consumers

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A4 Artikkeli konferenssijulkaisussa
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Date

2020-10-26

Department

Department of Electrical Engineering and Automation
Department of Economics

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Language

en

Pages

5

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Proceedings of 2020 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2020, pp. 111-115, IEEE PES Innovative Smart Grid Technologies Conference Europe

Abstract

This paper proposes an indirect load control demand response (DR) strategy for residential houses. A Stackelberg game theory is applied to account for the interaction between the aggregator in one side and the consumers on the other side. The aggregator, which owns a wind power plant, strives to maximize wind power utilization by consumers. Therefore, it motivates the consumers to adjust their load demand according to the forecasted wind power production by offering a bonus to them. On the other hand, consumers attempt to achieve the highest amount of reward by changing their load profile. It is assumed that each consumer has a critical load of which they have no control, and also a flexible load such as heat, ventilation and air conditioning (HVAC) system which can regulate its demand while keeping the temperature in a specified band. In this way, the consumers' comfort level is entirely maintained. In addition, for the sake of considering the uncertainty, several scenarios for wind and also consumers' demand are considered in this work.

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Keywords

Game theory, HVAC systems, Indirect load control, Stochastic programming

Other note

DOI

10.1109/ISGT-Europe47291.2020.9248820

Citation

Tavakkoli, M, Fattaheian-Dehkordi, S, Pourakbari-Kasmaei, M, Liski, M & Lehtonen, M 2020, A game theory approach for maximum utilization of wind power by DR in residential consumers. in Proceedings of 2020 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2020., 9248820, IEEE PES Innovative Smart Grid Technologies Conference Europe, IEEE, pp. 111-115, IEEE PES Europe Conference on Innovative Smart Grid Technologies, Virtual, Online, 26/10/2020. https://doi.org/10.1109/ISGT-Europe47291.2020.9248820

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https://urn.fi/URN:NBN:fi:aalto-202103222534

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[article-cris] Sähkötekniikan korkeakoulu / ELEC