Optimizing Energy Management in Microgrids Based on Different Load Types in Smart Buildings

This paper presents an energy management strategy (EMS) based on the Stackelberg game theory for microgrid community. Three agents or layers are considered in proposed framework. The cluster (MGC) refers to agent that coordinates interactions between microgrids and utility grid. manages scheduling of its own consumers. third represents consumers inside microgrids. equilibrium point is solved different each layer will benefit most. First, algorithm performs demand response according load models smart buildings determines consumption consumer. Then, selling price amount required purchase from grid achieve maximum profit. Finally, balance be obtained by agent. Moreover, method uses various types at times real-life models. result shows considering these with increased profit user average 22%. implemented time use (TOU) model real-time pricing (RTP) microgrid.