Game Theory Based Profit Maximization Model for Microgrid Aggregators With Presence of EDRP Using Information Gap Decision Theory

In the competitive electricity markets, each microgrid (MG) aggregator strives to maximize its own profit, whereas their coordination is a serious challenge for distribution system operator (DSO). In addition, indefiniteness of market clearing price and pungent alterations of renewable power generation are driving this issue toward a more complicated problem. To address this problem, we proposed an unprecedented game theoretic model by means of Stackelberg strategy to peruse the competition among MGs aggregators and DSO in order to attain the equilibrium point that can maximize the profit of all players who participate in retail market. Our design objective is to distinguish the optimal power exchanges between the MGs and market simultaneously considering emergency demand response program in order to hedge the risk of participation in retail market. Furthermore, information gap decision theory has been fulfilled to cope with drastic uncertainty of the problem. Finally, Benders decomposition (BD) associated with mathematical program with equilibrium constraints and strong duality theorem are accomplished to make the proposed model computationally tractable and subsequently replaced by its Karush-Kuhn-Tucker optimality conditions, which are in turn linearized. The executed detailed and extensive results indicate the sufficiency and competency of the proposed model.