Optimal energy management strategy for an isolated industrial microgrid using a Modified Particle Swarm Optimization

In this research paper, a 24-hour ahead optimal energy management system (EMS) for an isolated industrial microgrid containing wind, PV solar, diesel generator, microturbine and energy storage is developed and analyzed. The main goal of the microgrid EMS optimization model is to minimize the cost of energy production, maximize the economical benefit of the energy storage and ensure the renewable energy utilization to the maximum possible extent. The Modified Particle Swarm Optimization (MPSO) technique is proposed to solve the optimization model. The model takes into account the fluctuations of renewable energy resources and load demands within the microgrid and uses appropriate forecasting to overcome these fluctuations. The proposed MPSO-based EMS has been tested on a real microgrid in stand-alone mode (Goldwind Smart Microgrid System, Beijing, China). Simulation results have revealed that the proposed MPSO-based EMS can solve the day-ahead optimization model in acceptable fast computation time efficiently. To validate the performances of the proposed strategy, simulation results were also obtained using Genetic Algorithm (GA). Comparison of simulation results show the robustness of the proposed MPSObased EMS in achieving a possible reduced total energy production cost within a reasonably short computation time.