基于改进粒子群算法的电动汽车停车场V2G策略研究

为解决电动汽车大规模并网带来的一系列问题,国内外逐步在城市商业停车场内提供电动汽车充电服务。在此背景下,提出一种基于电动汽车并网技术的电动汽车充放电停车场模型。该模型响应实时电价,对电动汽车的充电并网行为进行动态调度,继而与电网进行能量交互。在求解电动汽车最优调度策略时采用粒子群优化算法,从可行性编码、自适应搜索半径、边界变异修正等方面进行改进,以提高算法的效率及收敛精度。仿真实验采用美国PJM公司的实时电价数据及主流电动汽车的型号参数,对比分析了3种不同情景下电动汽车停车场的运营过程及结果,验证了所提模型的合理性以及改进算法的有效性。

Research of V2G Strategies for EV Parking Lot Based on Improved PSO

Electric vehicle parking lot is built nearby commercial office buildings for electric vehicles charging and par-king to solve a series of problems brought by large-scale grid-connected electric vehicles.A V2G based electric vehicle parking lot model (V2G_EVPL) was proposed to describe charging and discharging behaviors of electric vehicles in the parking lot based on vehicle to grid (V2G) technology.Under the conditions of the real-time pricing (RTP),V2G_EVPL dynamically schedules the electric vehicle charging or discharging,and then interacts with the grid for energy.Improved particle swarm optimization (IPSO) algorithm is applied to solve the optimal scheduling for electric vehicles.Improvements,such as feasibility coding,adaptive search radius and boundary variability correction,are made to improve the efficiency and the convergence accuracy of PSO.Real-time price data of PJM and the parameters of mainstream electric vehicles are used in simulation.The operation process and results of V2G_EVPL under three different scenarios are compared and analyzed.Results of the simulations show that the proposed model is reasonable and the improved PSO algorithm is both efficient and effective.