理解电网中线路重要性的生态独特性

Andrew Foster, Hao Huang, M. Narimani, Laura Homiller, K. Davis, A. Layton
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引用次数: 0

摘要

电网关键部件的识别是电力工程师面临的一个重要挑战。同样,许多生态学家面临着识别食物网中重要物种的挑战。考虑到电网网络和食物网网络之间的相似性,本研究利用生态学文献中提出的识别方法来识别电网中的关键部件。这些生态学方法包括营养重叠和加权营养重叠。我们还研究了电力工程文献中提出的一种方法,该方法使用归一化线路中断分配因子(NLODF)来比较不同的方法。本研究的目的是确定临界度量中的生物灵感是否为电网分析提供了可行的工具。当考虑电网中的所有线路时,利用NLODF的工程方法可以更准确地识别电网中的关键线路。然而,在考虑前10%、20%或30%的品种时,发现生态指标STO与NLODF一样好。在分析的最大网格中,STO是最准确的指标,这表明STO在更大的网格中可能更准确。生态方法和工程方法的性能比较表明,生态方法可以用于准确识别电网中的关键部件。
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Ecological Uniqueness for Understanding Line Importance in Power Grids
The identification of critical components in electric power grids is an important challenge power engineers face. Similarly, many ecologists face the challenge of identifying important species in food web networks. Drawing similarities between power grid networks and food web networks, this study utilizes proposed identification methods from ecology literature to identify critical components in electric power grids. These ecological methods used include measures of Sum of the Trophic Overlap (STO) and Weighted Trophic Overlap (WTO). We also study a method proposed from power engineering literature that uses the Normalized Line Outage Distribution Factor (NLODF) to compare the different methods. The intention of this study is to determine if bio-inspiration in criticality metrics provides a feasible tool to use in power grid analysis. The proposed engineering method utilizing NLODF is found to be more accurate in identifying critical lines in power grids when considering all lines in the grid. However, the ecological metric STO is found to be as good as NLODF when considering the top 10,20, or 30% of lines. STO was the most accurate metric in the largest grid analyzed, suggesting STO may be more accurate in larger grids. The comparable performance of the ecological and engineering methods suggests the ecological methods can be used to accurately identify critical components in electric power grids.
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