Hybrid AC/DC microgrid energy management based on renewable energy sources forecasting

Energy management is the core of economical and efficient operation for hybrid AC/DC microgrid. In this paper, renewable energy sources are forecast by using BP neural network based on modified particle swarm optimization (MPSO-BP). Compared with traditional algorithm, the modified algorithm performs better in both search ability and speed. After forecasting, with the objectives of minimum total cost and minimum power loss, the optimal model is built. The output is optimized through coordinating all kinds of DGs. The simulation results verified the effectiveness of the proposed model in multi-objective optimization of hybrid microgrid. Through the energy management dispatch, the hybrid microgrid could realize the optimized operation level.