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机构地区:[1]福建省电力有限公司,福建福州350003 [2]浙江大学电气工程学院,浙江杭州310027
出 处:《华北电力大学学报(自然科学版)》2013年第6期63-68,共6页Journal of North China Electric Power University:Natural Science Edition
基 金:国家重点基础研究发展计划(973计划)资助项目(2013CB228202);国家自然科学基金资助项目(51107114;51177145);福建省电力有限公司电力科学研究院科研项目(12-110107-013)
摘 要:随着电动汽车技术尤其是向电力系统放电技术的发展,电动汽车为风电等间歇性可再生能源提供辅助服务,如旋转备用或与之协调调度就成为可能。这样,如何对电动汽车充放电进行优化调度,以便经济而有效地为风电场提供旋转备用服务。首先简要分析了电动汽车的入网特性。之后,针对电动汽车代理机构负责调度所辖电动汽车的情形,发展了电动汽车参与提供风电场旋转备用时的电动汽车最优充放电调度模型,以电动汽车代理机构利润最大化为目标,考虑了电动汽车充放电功率等约束,并采用粒子群算法求解。最后,以修改的IEEE 118节点系统为例说明了所发展的模型的基本特征。With the development of electrical vehicle (EV) technology especially the vehicle to grid (V2G) tech nique, it is becoming realistic for EVs to provide ancillary services such as spinning reserves for wind power generation, or in other word, to be dispatched with wind power generation in a coordinated way. Hence, it is necessary to examine the optimal eharging/discharing dispatch of electric vehicles for spinning reserve provisions to wind power generation, and this is the focus of this work. First, the characteristics of the EV injection power to the power system concerned are investigated. Then, for the scenario that EVs are dispatched by an agent, an optimal dispatching model for the char ging/discharging of EVs is developed for providing spinning reserves to wind power generation. In the developed mod el, the objective is to maximize the profit of the agent while respecting some constraints such as the charging/dischar ging capacities, and the optimization model is solved by the well developed particle swarm optimization (PSO) method. Finally, the modified IEEE l l8bus system is served for demonstrating the essential features of the developed model.
关 键 词:电动汽车 充放电 风电机组 旋转备用 优化调度 粒子群算法
分 类 号:TM73[电气工程—电力系统及自动化]
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