Research on scheduling strategy of electric vehicle fast charging station combined with photovoltaic generation and energy storage

The random fluctuation of photovoltaic(PV) generation and the random charging load of electric vehicles(EVs) will have a great impact on the power grid. It is an effective scheme to equip the fast charging station with photovoltaic and Energy Storage System(ESS), which has the advantage of suppressing the fluctuation of the power grid and absorbing the renewable energy. To solve the problem of energy management in Fast Charging Stations(FCS), a power prediction model based on EV charging behavior and PV data is studied, and a multi-objective optimization mathematical model is established considering the economic benefit of charging stations and the smooth load fluctuation, a dynamic ESS charging and discharging power constraint strategy considering both charging load and real-time electricity price is proposed, which is solved by Multi-Objective Particle Swarm Optimization(MOPSO) algorithm with mutation links based on grid sorting. The simulation results show that compared with the conventional charging station scheme, the scheme can improve the economic performance, improve the use of new efficient energy, and effectively reduce the impact of the original charging load on the peak load of distribution network, to reduce grid fluctuations.