Multi-objective Optimization Strategy for Wind-fire-storage Joint Scheduling Considering the Needs of Electric Vehicle Owners
The fluctuation of wind power output and the disorderly charging and discharging of electric vehicles(EV)increase the burden of power system scheduling.Therefore,it is needed for the power system to consider the allocation of resources on the generation side,while it is needed on the user side to reasonably arrange for EV to participate in grid scheduling in an orderly manner.To address this issue,a multi-objective optimization model for wind-fire-storage joint scheduling considering the needs of EV owners was established.With the goal of minimizing net load variance,total system operation cost,and vehicle owner payment cost,the different time-of-use electricity prices were established to guide vehicle owners to participate in grid scheduling.The NAGA-Ⅱ algorithm and fuzzy analytic hierarchy process are applied to obtain the optimal solution in the Pareto solution set.The results show that the strategy can effectively reduce the variance of system net load,suppress system fluctuations,and reduce the total operation cost of the system and the payment fees of vehicle owners;however,different time-of-use electricity pricing standards have different impacts on the participation of electric vehicles in scheduling.
electric vehiclemulti-objective optimizationjoint schedulingtime-of-use electricity priceNAGA-Ⅱ algorithm
万方数据
维普
