Energy Management for a Microgrid Cluster Using Game Theory Approach and Variable Battery Cost

This document presents an energy management system (EMS) that implements a game theory approach, using Nash equilibrium as a solution method to minimize operating costs and enhance prosumer revenue within a microgrid cluster (MGC). Prosumer revenue is determined by reducing energy costs, which depend on grid energy absorption and battery usage, considering the depth of discharge and battery type. The proposed approach is applied to a cluster of two PV-based microgrids within a neighborhood in a Puerto Rican town, where each microgrid features unique load and generation profiles as well as different battery sizes.The model operates over a seven-day window with a one-hour time step and is structured into stages, which are solved using Python.