Optimal operation of microgrid based on improved binary particle swarm optimization algorithm with double-structure coding

Due to energy crisis and environmental concern, distributed generations including renewable energy sources have become popular in the electric energy industry. Microgrid is an effective technical means of the integration and access of distributed generations. On the basic of the generating characteristics of various microsources, this paper establishes a multi-objective optimal operation model with multiple constraints, aiming at minimizing the generation cost, pollutant emission cost, compensation cost of load shedding and network loss of microgrid. Different weights are assigned to the four sub-objective functions to transform the multi-objective optimization problem into a single objective optimization problem. Binary particle swarm optimization (BPSO) algorithm is improved with double-structure coding. Its performance is tested by two test functions and comparison with the traditional BPSO algorithm is made. The improved algorithm is applied to a microgrid simulation example which is in the island mode. Simulation results demonstrate the correctness of the proposed optimization model and the effectiveness of the improved algorithm.