电动汽车充放电与风力/火力发电系统的协同优化运行

提出一种通过控制规模化电动汽车的充放电,使其能够与现有的风力/火力发电系统协同运行的优化调度策略。针对传统含电动汽车的电力系统优化模型没有考虑电动汽车用户成本,实用性不高的缺陷,建立了包含电网运行经济性、电动汽车用户成本、CO2排放、最小弃风量的多目标优化模型;提出了将改进的NSGA-II遗传算法和加权尺度法相结合的智能优化算法。应用该算法,求出多目标动态优化模型的帕累托前沿,获得了最符合实际的电力系统综合优化调度方案。对所提出的多目标优化调度方法进行了仿真计算,结果证明,采用所提优化策略可以获得最佳的火电、风电与电动汽车之间的出力方案。该方案符合实际,在合理的电动汽车用户成本范围内可有效地降低电网运行成本、风力发电弃风量和大气碳排放量,应用价值较高。

Cooperative Dispatch of Large-Scale Electric Vehicles with Wind-Thermal Power Generating System

This paper proposed an optimal strategy for coordinated operation of large scale Electric vehicles (EVs) charging and discharging with Wind-Thermal system.Different from conventional works,the proposed cooperation modelis more practical,specially pays attention to EV users' costs while doing power commitments schedule on thermal plants,wind farms,and EV aggregators.The objective of the optimal model is to obtain the best compromised solution between generating cost,CO2 emission,wind curtailment and EV users'cost.An improved non-dominated sorting genetic algorithm (NSGA-Ⅱ) and a weighted multi-scale method are put forward to solve the multi-object optimal problem by achieving their Pareto frontier.Finally the optimal scheduling scheme is obtained and which is most suitable for the actual power system.Simulation calculation is carried out on the proposed multi-objective optimization scheduling method.The optimization strategy can be used to obtain the optimal strategy between the thermal,wind power and electric vehicle output power.According to the actual situation,the proposed scheme can effectively reduce the operation cost of power grid within the region of user cost of electric vehicles,wind power generation and the amount of air carbon emissions.