Game theoretic model of energy trading strategies at equilibrium in microgrids

This paper models and analyzes the consumption and trading patterns of electrical energy in islanded microgrids when the generation is restricted to renewable resources such as photovoltaic (PV) panels. With the producers and consumers of the grid represented as agents, the impact of the following two scenarios on the agents' utilities as well as the social welfare are investigated during the islanded period: (i) trading with fixed price; (ii) trading with variable price. In order to reflect real-world behavior, Nash equilibrium (NE) in user (agent) behavior is established by means of evolutionary optimization i.e. Genetic Algorithm (GA), such that each user maximizes its individual utility. The users' utilities consider both income from trade as well as the monetary equivalent of satisfaction derived from energy consumption. The latter is sufficiently generalized as it incorporates fixed loads whose utility curves are modeled as saturating nonlinearities, as well as discrete shiftable loads that can be scheduled over any time interval during the isolation period. Simulation results of this study are expected to have widespread ramifications in designing the future distribution systems.