Coordinated optimal bidding strategies methods of aggregated microgrids: A game theory-based demand side management under an electricity market environment

Hosein Saeian, Taher Niknam, Mohsen Zare and Jamshid Aghaei

Energy, 2022, vol. 245, issue C

Abstract: Due to substantial demand of expansion and application of distributed generations and energy storage systems (ESSs), the operation of microgrids (MGs) has become more flexible but more complicated with the role of active network loads. To deploying these potentials of MGs, in this paper, a novel demand side management (DSM) method based on the game theory with an effective payoff function is developed in a scrutinized manner. In order to be more compatible with reality, the interactions between some MGs are optimized in an electricity market environment using an evolutionary method. To implement this model, in the first step, each microgrid operator (MGO) tries to maximize its benefit considering the payoff function in an iterative process deploying the proposed game theory method. In this step, a new strategy is reconciled to DSM and its payoff function to reach the Nash equilibrium, effectively. The aggregated load demand of MGs will be participated in market mechanism by MGO through a Gray Wolf Algorithm (GWA) to maximize the MGO's profit. The results confirm the compatibility between DSM and game theory to find the Nash equilibrium point. Furthermore, the price-maker strategy makes more profit compared to price-taker one form the MGO point of view.

Keywords: Microgrid operation; Demand side management; Game theory method; Electricity market; Price maker player; Gray wolf algorithm (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:245:y:2022:i:c:s0360544222001086

DOI: 10.1016/j.energy.2022.123205

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