Multi-Objective Optimal Scheduling of the Microgrid with Electric Vehicles

Abstract

As the global attention to environmental protection continues to improve, the efficient use of renewable energy microgrids has been widely developed. At present, the intermittent nature of renewable energy and the uncertainty on the demand side will affect the stable operation of the microgrid. As an impact load, electric vehicles (EVs) will seriously affect the safe dispatch of the microgrid. To solve the above problems, this paper established a microgrid based on contains the electric vehicles, multi-objective optimization model, to achieve the available in full given raw energy and load-bearing, and these two goals better balance of economy and environmental protection, the linear weighting method based on the two-person zero-sum game as a whole these two goals, at the same time to get the optimal solution in the unit, the adaptive simulated annealing particle swarm optimization algorithm (ASAPSO) is used to solve the multi-objective optimization model. The simulation results show that the multi-objective weight method can reduce the influence of uncertainty factors, promote the full absorption of renewable energy and full load-bearing, the orderly charging and discharging mode of electric vehicles can reduce the operation cost and environmental protection cost of the microgrid, and the improved optimization algorithm can improve the economy and environmental protection of the microgrid.

Keywords: Microgrid; Electric Vehicles; Multi-Objective Optimization; Two-Person Zero-Sum Game; Adaptive Simulated Annealing Particle Swarm Optimization Algorithm