Optimization Scheduling of Electric Vehicle Charging Load Based on Improved PSO

The unpredictability of wind power output and the disorder of electric vehicle charging have brought huge challenge to the stable and safe operation of the power grid, and a reasonable charging scheduling strategy can effectively come into play the role of electric vehicles in the regulation of power grid operation. Based on these, a scheduling optimization model of electric vehicle charging load is proposed which is considering the unpredictability of wind power output. On the basis of the forecast outcomes of wind power output, the Latin hypercube sampling and Monte Carlo algorithm are used to establish a multi-objective scheduling optimization model of electric vehicle charging load for wind power consumption, aiming at maximizing wind power consumption, minimizing peak shaving compensation cost and minimizing charging cost, and comprehensively considering the constraints of user charging demand and wind power output. The outcome is displayed that the scheduling optimization model proposed can promote the orderly charging of electric vehicles and decrease the electricity consumption cost of users, while further improving the system’s ability to accept wind power, reducing wind curtailment, and promoting the stabilize and safe operation of the power grids.