Energy management and optimization of microgrid system using particle swarm optimization algorithm

Abstract

An optimization model is proposed to manage a day-ahead optimal energy management strategy for economic operation of Microgrids. The model is based on a using particle swarm optimization algorithm (PSO) for scheduling four energy sources (grid, PV system, wind system, energy storage system) with 24 hours' time step, considering forecasted electrical demands, weather, and renewable energy generations. In this paper, the objective function is to minimize the cost of electricity generation and to manage delivering power from hybrid sources to the demand. The results showed that scheduling and controlling of different energy sources in efficient way reduce the total cost of power generation and ensure sustainable power flow. It is important to enhance the usage of solar and wind sources, optimize the operation of storage systems.