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| Coordinated scheduling of electric vehicles and renewable generation considering vehicle-to-grid mode |
| HUANG Xiao-qian, WANG Feng, TAN Yang-hong, WANG Rui, SHAO Jing-ke, CHEN Chun |
| College of Electrical and Information Engineering, Hunan University, Changsha 410082, China |
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Abstract For the purpose of reducing the difference between the peak and the valley for load of regional power grid,strengthening the ability of power grid accepting renewable energy and improving the response positivity of electric vehicles (EVs) users,taking the minimized equivalent load fluctuation of regional power grid and the minimized charging price of EVs users as objective function and considering the vehicle-to-grid (V2G)mode,a multi-objective coordinated scheduling model,in which the EVs,wind power and photovoltaic generation system were taken into account simultaneously,was established,so that charging and discharging behavior of EVs could be arranged reasonably.Defining each objective membership function,multi-objective optimization problem was reformulated into a nonlinear single-objective programming problem by means of fuzzy satisfaction-maximizing method,and this nonlinear single-objective programming problem was solved by using adaptive particle swarm optimization algorithm.Simulation results show the effectiveness of multi-objective model and the feasibility of solving method.
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Received: 16 September 2015
Published: 28 February 2016
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考虑V2G模式的电动汽车与可再生能源协同调度
为减小地区电网负荷峰谷差,增强电力系统接纳可再生能源的能力,同时提高电动汽车用户响应积极性,以地区电网等效负荷波动最小和用户充电费用最低为目标函数,建立了考虑电动汽车与电网互动(vehicle-to-grid,V2G)模式并计及风电和光伏出力的多目标协同调度模型,以合理安排电动汽车的充放电行为.定义了各目标的隶属度函数,通过运用最大模糊满意度法,将该多目标优化问题转化为单目标非线性优化问题,并应用自适应权重粒子群寻优算法进行求解,得到最优调度方案.算例结果验证了模型的有效性和求解方法的可行性.
关键词：
电动汽车,
风光发电,
电动汽车-电网互动技术,
模糊理论,
自适应权重粒子群算法
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