| 规模化电动汽车和风电协同调度的机组组合问题研究 |
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| 引用本文： | 汪春,吴可,张祥文,孙海顺,张聪,许晓慧. 规模化电动汽车和风电协同调度的机组组合问题研究[J]. 电力系统保护与控制, 2015, 43(11): 41-48 |
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| 作者姓名： | 汪春 吴可 张祥文 孙海顺 张聪 许晓慧 |
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| 作者单位： | 中国电力科学研究院，北京 100192;强电磁工程与新技术国家重点实验室(华中科技大学)，湖北 武汉 430074;中国电力科学研究院，北京 100192;强电磁工程与新技术国家重点实验室(华中科技大学)，湖北 武汉 430074;强电磁工程与新技术国家重点实验室(华中科技大学)，湖北 武汉 430074;中国电力科学研究院，北京 100192 |
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| 基金项目： | 国家科技支撑计划项目(2013BAA01B00)；国家自然科学基金委项目(51361135703)；国家电网公司科技项目 |
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| 摘 要： | 基于电动汽车通过集中控制器与电网交互的模式,考虑集中控制器所辖区域电动汽车负荷每个调度时段的可控特性,提出将集中控制器充电负荷作为机组组合模型的控制变量。通过蒙特卡洛抽样模拟电动汽车并网场景,计算集中控制器的可调度上限值和下限值,建立了规模化电动汽车与风电协同调度的机组组合模型。算例分析结果表明了应用提出的机组组合模型提高风电消纳能力和降低系统运行成本的有效性。
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| 关 键 词： | 电动汽车集中控制器；风力发电；协同调度；机组组合；可调度容量 |
| 收稿时间： | 2015-01-11 |
Unit commitment considering coordinated dispatch of large scale electric vehicles andwind power generation |
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| WANG Chun,WU Ke,ZHANG Xiangwen,SUN Haishun,ZHANG Cong and XU Xiaohui. Unit commitment considering coordinated dispatch of large scale electric vehicles andwind power generation[J]. Power System Protection and Control, 2015, 43(11): 41-48 |
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| Authors: | WANG Chun WU Ke ZHANG Xiangwen SUN Haishun ZHANG Cong XU Xiaohui |
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| Affiliation: | China Electric Power Research Institute, Beijing 100192, China;State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;China Electric Power Research Institute, Beijing 100192, China;State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;China Electric Power Research Institute, Beijing 100192, China |
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| Abstract: | Assuming that all electric vehicles integrated to the grid are managed by aggregators, this paper proposes that the charging load of each EV aggregator can be dispatched within the unit commitment model taking the controllability of the charging of EVs at each dispatched time period into consideration. This can be accomplished by assessing the upper and lower limit of charging load of each EV aggregator based on the grid connected EVs scenarios simulation using Monte Carlo method. A unit commitment (UC) model is proposed for optimal coordination of wind power generation and charging load of EV aggregators. Cases study show that with the proposed UC model the wind abandon can be decreased as well as the cost of operation effectively. |
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| Keywords: | EV aggregator wind power generation coordinated dispatch unit commitment scheduling capacity |
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