A New Cooperative Game—Theoretic Approach for Customer-Owned Energy Storage

Maria O. Hanna, Mostafa F. Shaaban and Magdy M. A. Salama
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Maria O. Hanna: Electrical and Computer Engineering Department, University of Waterloo, Waterloo, ON N2L 3G1, Canada
Mostafa F. Shaaban: Electrical Engineering Department, American University of Sharjah, Sharjah 26666, United Arab Emirates
Magdy M. A. Salama: Electrical and Computer Engineering Department, University of Waterloo, Waterloo, ON N2L 3G1, Canada

Sustainability, 2022, vol. 14, issue 6, 1-14

Abstract: The increasing demand for energy storage systems (ESSs) alongside the continuous enhancements to storage technology have been of great positive impact on the electric grid. Their unceasing development has been driven by the need to accommodate increased penetration of renewable energy resources and defer capital investments, among other benefits. Moreover, ESSs have played a key role in the grid’s ability to cope with its ever-shifting load profiles, resulting in large economic gain for ESS owners. For this reason, this prospective study was designed to investigate privately-owned energy storage hubs (ESHs) and their interactions with potential customers as well as with the electric grid. This research examined two contrasting interaction approaches for customer-owned stationary energy storage hubs: a cooperative and a non-cooperative game-theoretic approach. The goal of the cooperative technique is to conduce to a correlated equilibrium increasing the social welfare of all players involved using a regret matching algorithm. On the other hand, in the non-cooperative approach, modeled as an ascending price-clinching auction, each player acts greedily, maximizing only their individual welfare. Implementing both case studies resulted in important insights into ESH players’ interactions and provided contrasting methods of modeling their behaviors. Finally, depending on the application at hand, the choice of one approach may be more realistic than the other.

Keywords: correlated equilibrium; regret matching algorithm; clinching auction; energy storage hub (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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