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Application of NSGA - II to Power System Topology Based Multiple Contingency Scrutiny for Risk Analysis

机译:NSGA-II在基于电力系统拓扑的多重应急评估风险分析中的应用。

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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 II) 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:放松管制和增加可再生能源的结合,已将现有电力系统的性质转变为地理分布更广的系统。这给在线监测和控制带来了重大挑战。应急集识别是监视电力系统安全级别的必不可少的步骤。多重偶然性分析构成了安全问题的基础,尤其是大型互连电源系统的安全问题。用于在线安全分析的多种意外选择的困难在于其固有的组合性质。本文提出了一种避免电力系统脆弱性的避免灾难性故障的方法,它是一种划分其拓扑图的多目标优化问题,可以最大程度地解决每个孤岛的发电和负荷之间的不平衡问题,同时将其最小化分割以实现分区的行数。已应用版本II(NSGA II)的非支配排序遗传算法来获得最佳解决方案,并将所涉及的方法应用于IEEE 30总线测试系统并给出了结果。

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