Study on orderly charging management of EVs based on demand response

Large-scale electric vehicles (EVs) connected to the power system would bring extensive negative impacts on power system operation and control. Based on this situation, this paper puts forward a coordinated schedule strategy about the charging and discharging of electric vehicles both at the scale charging station and smart residential area. The strategy adopts the demand response (DR) scheme, namely, the charging and discharging behavior of the electric vehicles are controlled by the time-of-use price (TOU). With the electricity price as a level, in order to smooth the fluctuation of load and enhance the profit of users, this paper builds a scheduling strategy model and solved by adaptive mutation particle swarm optimization to reduce the influence of premature of standard particle swarm algorithm on optimization result. Finally, through examples, the reasonable pricing mechanism for peak-valley charging and discharging as proposed in the paper has proved to be effective in smoothing the system load, and the users' economic benefits are satisfied at the same time. Meanwhile, the performance contrast between traditional PSO algorithm and improved PSO algorithm, it is proved that the latter is more effective for dealing with high-dimensional problems.