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Application of multi-objective genetic algorithms to two case studies of reliability efficiency analysis and optimal expansion of electrical transmission networks

机译:多目标遗传算法在输电网络可靠性效率分析与最优扩展两个案例研究中的应用

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Two applications of multi-objective genetic algorithms to the analysis and optimization of electrical transmission networks are reported to show the potential of these combinatorial optimization schemes in the treatment of highly interconnected, complex systems. In a first case study, an analysis of the topological structure of an electrical power transmission system in the literature is carried out to identify the most important group of elements of different sizes in the network. The importance is quantified in terms of group closeness centrality. In the second case study, an optimization method is developed for identifying strategies of expansion of an electrical transmission network by addition of new lines of connection which are optimally identified with respect to the objective of improving the transmission reliability, while limiting the investment cost.
机译:据报道,多目标遗传算法在输电网络的分析和优化中的两种应用表明了这些组合优化方案在处理高度互连,复杂的系统中的潜力。在第一个案例研究中,对文献中的电力传输系统的拓扑结构进行了分析,以确定网络中不同大小的最重要元素组。重要性是根据群体亲密性来量化的。在第二个案例研究中,开发了一种优化方法,用于通过添加新的连接线来识别电气传输网络的扩展策略,这些连接相对于提高传输可靠性的目的进行了最佳识别,同时又限制了投资成本。

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    《Journal of Risk and Reliability》 |2011年第3期|p.365-374|共10页
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