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The proliferation of distributed generation and storage units is leading tothe development of local, small-scale distribution grids, known as microgrids(MGs). In this paper, the problem of optimizing the energy trading decisions ofMG operators (MGOs) is studied using game theory. In the formulated game, eachMGO chooses the amount of energy that must be sold immediately or stored forfuture emergencies, given the prospective market prices which are influenced byother MGOs' decisions. The problem is modeled using a Bayesian game to accountfor the incomplete information that MGOs have about each others' levels ofsurplus. The proposed game explicitly accounts for each MGO's subjectivedecision when faced with the uncertainty of its opponents' energy surplus. Inparticular, the so-called framing effect, from the framework of prospect theory(PT), is used to account for each MGO's valuation of its gains and losses withrespect to an individual utility reference point. The reference point istypically different for each individual and originates from its pastexperiences and future aspirations. A closed-form expression for the BayesianNash equilibrium is derived for the standard game formulation. Under PT, a bestresponse algorithm is proposed to find the equilibrium. Simulation results showthat, depending on their individual reference points, MGOs can tend to storemore or less energy under PT compared to classical game theory. In addition,the impact of the reference point is found to be more prominent as theemergency price set by the power company increases.

Prospect Theory for Enhanced Smart Grid Resilience Using Distributed Energy Storage