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Application of NSGA — II to Power System TopologyBased Multiple Contingency Scrutiny for Risk Analysis

机译:NSGA - II在风险分析中的多次应急审查的应用

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The Incorporation of deregulation and increase in renewable sources of generation has shifted the nature of existing power systems to a more geographically distributed system. This had led to significant challenges towards on-line monitoring and control. Contingency set identification is an essential step in monitoring the power system security level. Multiple contingency analysis forms the basis of security issues, particularly of large, interconnected power systems. The difficulty of multiple contingency selections for on-line security analysis lies in its inherent combinatorial nature. In this paper, an approach for identification of power system vulnerability to avoid catastrophic failures is put forward, as a multi objective optimization problem that partitions its topology graph, accounts for maximizing the imbalance between generation and load in each island and at the same time minimizes the number of lines cut to realize the partitions. The Nondominated Sorted Genetic Algorithm, version II (NSGA H) has been applied to obtain the optimal solutions and the methodology involved has been applied to an IEEE 30 bus test system and results are presented.
机译:注入放松管制和可再生能源的增加已经将现有电力系统的性质转移到更加地理分布的系统。这导致了对在线监测和控制的重大挑战。应急设定识别是监控电力系统安全级别的重要步骤。多次应急分析构成了安全问题的基础,特别是大型互联的电力系统。在线安全分析的多个应急选择的难度在于其固有的组合性质。在本文中,提出了一种识别电力系统漏洞,以避免灾难性失败的方法,作为对其拓扑图进行分区的多目标优化问题,用于最大化每个岛中的发电和负载之间的不平衡,同时最小化切割的行数以实现分区。已经应用了NondoMinated Sorted遗传算法,版II(NSGA H)以获得最佳解决方案,并且所涉及的方法已应用于IEEE 30总线测试系统和结果。

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