基于有向图和序贯蒙特卡洛法的含电动汽车配电网可靠性评估 |
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引用本文:管永高1,许文超1,汤奕2,王琦2,王震泉1,张诗滔1,牛涛1.基于有向图和序贯蒙特卡洛法的含电动汽车配电网可靠性评估[J].电网与清洁能源,2019,35(3):49~57 |
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基金项目:国家自然科学基金资助项目(51577030) |
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中文摘要:大规模电动汽车接入后将对配电网可靠性带来极大影响,快速有效的可靠性评估方法是亟待解决的关键问题之一。针对含电动汽车的配电网,提出了一种基于有向图和序贯蒙特卡洛算法的可靠性评估方法。首先基于有向图矩阵,利用前推和回推搜索辨识系统故障后的局部网络,并构建系统故障模式影响分析表;分析提出了考虑电动汽车接入后故障模式影响分析表的修正方法,并基于序贯蒙特卡洛算法定量分析了电动汽车接入后对配电网可靠性带来的影响,并从电动汽车接入位置和接入时段等角度对电动汽车接入电网提出了相应的建议。算例分析的结果表明所提方法能够快速修正电动汽车接入后的系统故障模式影响分析表,并能够适应不同场景下的含电动汽车配电网可靠性评估,为电动汽车合理接入电网提供理论依据。 |
中文关键词:电动汽车 V2G 配电网可靠性 有向图 序贯蒙特卡洛 |
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Reliability Evaluation of Distribution Network with Electric Vehicles Based on Digraph and Sequential Monte Carlo Method |
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Abstract:Electric vehicles integrated into the distribution network have great impacts on its reliability, thus the quick and effective reliability evaluation method has become one of the key problems to be addressed urgently. Based on the digraph and sequential Monte Carlo method, this paper proposes a method to evaluate the reliability of distribution network with electric vehicles. First, based on the digraph matrix, the local power network is recognized using the forward and backward search, and the failure mode and effect analysis table of the system is generated. The failure mode and effect analysis table is corrected considering the integration of electric vehicles. And the impacts of electric vehicle integration on the reliability of the distribution network are studied based on the sequential Monte Carlo method. And strategies to improve the reliability of the distribution network with electric vehicles are put forward form perspectives of integration place and duration. The result of the case study shows that the failure mode and effect analysis table can be corrected quickly with the method in this paper and the method can also adapt to the reliability evaluation of the distribution network with electric vehicles in different scenarios, and provides certain theoretical basis for the reasonable access of electric vehicles to the grid. |
keywords:electric vehicle V2G reliability of distribution network digraph sequential Monte Carlo |
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