Optimal Sizing and Energy Management of a Microgrid Using Single and Multi-Objective Particle Swarm Optimization under Autonomous and Grid Connected Mode 2019-28-0158
The conventional energy sources are getting depleted while at the same time the energy demand keeps growing. Hence, it is important to consider non-conventional energy sources to meet future energy demands. The renewable energy based microgrid system is one of the promising solutions to meet this increasing energy demand. The major parameters under consideration in a micro-grid system are cost-effectiveness, quality of service and energy management. This work concentrates on the energy management of the Photovoltaic/Wind based microgrid system connected to the fuel cell, microturbine and battery under Islanding (or) Autonomous mode and Grid-Connected Mode. The current model of PV, Wind and Battery systems are employed. The Wind, PV and Battery types are chosen from i-HOGA. The optimal combination of these sources with the aim of minimizing the operating cost, pollutant treatment cost and maximizing reliability using both single and multi-objective particle swarm optimization (PSO) has been considered. This microgrid has also been analyzed under three different strategies for both grids connected and islanded mode and the best energy management strategy is obtained after analysis. In addition to this, the type and number of PV, Wind, and Battery to meet the forecasted demand are determined under islanding mode using Multi-Objective Particle Swarm Optimization (MOPSO). A solitary best-accepted solution is attained from Fuzzy membership function. The algorithm proposed decides the optimal number of units and types of units selected to achieve the optimal cost. The simulation has been performed in MATLAB environment.
Citation: Dayalan, S., Rathinam, R., and Valliappan, S., "Optimal Sizing and Energy Management of a Microgrid Using Single and Multi-Objective Particle Swarm Optimization under Autonomous and Grid Connected Mode," SAE Technical Paper 2019-28-0158, 2019, https://doi.org/10.4271/2019-28-0158. Download Citation