计及风光电源的一种地区电网电动汽车充电调度方法  

Approach for Plug-in Electric Vehicles Charging Scheduling Considering Wind and Photovoltaic Power in Chinese Regional Power Grids

作　　者：张学清[1] 梁军[1] 张利[1] 于大洋[1] 韩学山[1] 张峰[1] 张熙[1] 

机构地区：[1]山东大学电气工程学院,济南250061

出　　处：《电工技术学报》2013年第2期28-35,共8页Transactions of China Electrotechnical Society

基　　金：国家自然科学基金(51177091);山东省自然科学基金(ZR2010EM055)资助项目

摘　　要：针对风电光伏等可再生资源发电以及电动汽车的广泛发展,提出了一种计及风电和光伏出力不确定性的地区电网的电动汽车充电调度方法。首先为了减小地区电网等效负荷峰谷差和购电成本,建立了电动汽车充电的多目标非线性混合整数优化调度模型。其次利用模糊集理论在风光出力模糊化的基础上,将多目标模糊优化模型转化为单目标的非线性优化问题。最后以某地区电网的数据为算例,用改进的粒子群算法对提出的多目标模糊优化模型进行求解,验证模型的有效性和求解方法的可行性,为电动汽车的优化调度提供了一条有效途径。According to the extensive development of plug-in electric vehicles（PEVs） and renewable resources, such as wind power and photovoltaic power, an approach for PEVs charging scheduling in regional power grids considering the uncertain outputs of wind and photovoltaic power is proposed. Firstly, in order to reduce the difference between the peak and the valley for equivalent load and purchasing power cost, a multi-objective non-linear mixed integer optimization model for PEVs charging scheduling is established. Secondly, the fuzzy theory is introduced to this paper to fuzzy the output of wind power and photovoltaic power. Therefore, the multi-objective fuzzy optimization model is reformulated as a single objective non-linear optimization problem. Finally, the data of example on regional power grid is analyzed to prove to the validity of model and the feasibility of solving for problems with improved particle swarm algorithm. An effective way is provided for the optimal dispatch of PEVs.

关 键 词：电动汽车 风光发电 模糊理论 粒子群优化 

分 类 号：TM711[电气工程—电力系统及自动化] TM715