基于改进化学反应优化算法的电动汽车与可再生能源多目标协同调度

Multi-Objective Coordinated Scheduling of Electric Vehicles and Renewable Generation Based on Improved Chemical Reaction Optimization Algorithm

为减小可再生能源出力波动对电网的影响以及加快电动汽车的普及速率,以最小化可再生能源的出力波动和最大化电动汽车用户收益为目标函数,计及电池储存电量约束、充放电功率约束和充放电次数约束等条件,建立了同时计及可入网电动汽车、风力发电和光伏发电系统的多目标协同调度模型。提出了基于虚拟理想分子的多目标改进化学反应优化算法(chemical reaction optimization algorithm,CROA),并用该算法对模型进行了求解,针对化学反应算法收敛速度慢、精度低的缺陷,在算法中融入了粒子群优化算法的更新模式。算例结果表明,通过合理安排电动汽车的充放电可以有效平抑可再生能源的出力波动和增加电动汽车用户的收益。通过比较验证了基于虚拟理想分子的多目标改进CROA具有较强的寻优能力。

To mitigate the impact of fluctuation of renewable generation output on power grid and accelerate the population of electric vehicles （EV）, taking the minimized output fluctuation of renewable generation and the maximized income of EV users as objective function and considering the constraints of the electricity quantity stored in the battery, the charging/discharging power and the charging/discharging times, a multi-objective coordinated scheduling model, in which the grid-connectible EV, wind power generation system and photovoltaic （PV） generation system are taken into account simultaneously, is established. A virtual ideal molecular based multi-objective improved chemical reaction optimization algorithm（CROA） is proposed, and the established model is solved by the proposed algorithm. In allusion to such defects of CROA as slow convergence and low accuracy, the update mode of particle swarm optimization algorithm is integrated with the improved CROA. Results of calculation example show that through reasonably arranging the charging/discharging of EV, the output fluctuation of renewable generation can be effectively suppressed and the income of EV users can be increased. Comparison results show that the virtual ideal molecular based improved multi-objective CROA possesses strong searching ability.