An optimal control method of microgrid system with household load considering battery service life

Since the disorderly charging of a large number of electric vehicles is not conducive to the stability of the power grid, aiming at the storage function of power batteries for electric vehicles, an optimal control method for microgrid systems with household loads based on electric vehicle virtual energy storage is proposed in this paper. Taking the minimum of electricity cost, capacity attenuation of the battery and carbon dioxide emission as the objective functions, and fully considering the constraints of the charge and discharge power and the available capacity of electric vehicles, an optimal control model for microgrid systems with household load is established based on the multi-objective optimization. The optimal Pareto solution set of the model is obtained by the Non-dominated Sorting Genetic Algorithms III (NSGA-III) algorithm, and the optimal solution is solved by the technique for order preference by similarity to the ideal solution (TOPSIS) algorithm. The effectiveness and correctness of the proposed method are verified by the simulation examples from the actual operation data of the microgrid system containing a photovoltaic station and household load in China. The simulation results show that electric vehicles participating in virtual energy storage not only improve the stability of the power grid operation, but also bring some economic benefits to electric vehicle users. The electricity cost is reduced by 829.0USD, the total charging and discharging of the electric vehicle virtual energy storage system is 2703 kWh, the average service life of the battery is 7.3 years, and the carbon dioxide emission is reduced by 166.37 kg.

Automated summary

This paper proposes an optimal control method for microgrid systems with household loads based on electric vehicle virtual energy storage, aiming at the stability of the power grid. By considering multiple objective functions and using genetic algorithms, the charging and discharging of electric vehicles are optimized. Simulation results demonstrate that electric vehicles participating in virtual energy storage enhance the stability of the power grid and provide economic benefits to electric vehicle users.