基于改进烟花算法的电动汽车与新能源协同调度

Coordinated scheduling of large-scale Electric Vehicles and renewable energy based on Improved Fireworks Algorithm

摘要:

为提高电力系统对新能源出力的接纳能力，降低区域电网的等效负荷波动，维护系统安全性的同时，增强电动车车主响应的积极性，以区域电网系统内的等效负荷波动量最小和电动车车主经济效益最优为优化目标，建立规模化电动汽车与新能源协同调度模型，来合理安排电动汽车的充放电行为。运用最大模糊满意度法将多目标问题化为单目标问题，提出一种改进烟花算法，通过优化初始种群分布，以“双精英—锦标赛”的选择策略提升算法性能。通过算例结果对比，验证规模化电动汽车与新能源协同调度可有效平抑等效负荷波动，为电动汽车用户创造收益。改进的算法降低了计算开销，求解精确度更高。

Abstract:

In order to improve the power system's ability to accept renewable energy output, reduce the equivalent load volatility of the regional power grid, maintain system security and enhance the response enthusiasm of the owners of Electric Vehicle(EV), taking the minimum load fluctuation in the grid power system, and the optimal economic benefits of the EV owners as the optimization goals, a collaborative scheduling model of large-scale EVs and renewable energy is established to reasonably arrange the charging and discharging behaviors of EVs. The maximum fuzzy satisfaction method is adopted to turn the multi-objective problem into a single objective problem. At the same time, an Improved Firework Algorithm(IFWA) is proposed. The algorithm performance is improved by optimizing the initial population distribution and a double elite-tournament selection strategy. Finally, by comparing the results of the calculation examples, it is verified that the coordinated scheduling of large-scale EVs and renewable energy can effectively suppress the fluctuation of equivalent load and create benefits for EV users. The improved algorithm reduces the computational overhead with a higher accuracy.