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Comparison of particle swarm based meta-heuristics for the electric transmission network expansion planning problem

机译:基于粒子群的电动传输网络扩展规划问题的比较

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The Transmission Expansion Planning (TEP) problem is considered a very complex problem due to its combinatorial and nonconvex features. Some analytical and meta-heuristic methods have been proposed to tackle it, however, it is recognized that new efficient optimization tools are still needed. Particle Swarm Optimization has been an evolving research area in the last ten years and many interesting and successful applications in a variety of complex problems have shown the potential of this technique. In this work, two state of art Particle Swarm Optimization (PSO) based algorithms, known as Unified Particle Swarm Optimization (UPSO) and Evolutionary Particle Swarm Optimization (EPSO), are used to solve the above-mentioned problem. Comparisons, detailed analysis, guidelines and particularities are shown in order to apply the PSO technique for realistic systems. Also, results are provided for test and realistic power systems.
机译:传输扩展规划(TEP)问题被认为是由于其组合和非渗透特征的非常复杂的问题。已经提出了一些分析和元启发式方法来解决它,但是,仍然需要新的高效优化工具。粒子群优化在过去十年中一直是一个不断发展的研究领域,并且在各种复杂问题中许多有趣和成功的应用已经表明了这种技术的潜力。在这项工作中,两种艺术粒子群优化(PSO)的基于算法,​​称为统一粒子群优化(UPSO)和进化粒子群优化(EPSO)来解决上述问题。显示了比较,详细分析,指导和特殊性,以应用于现实系统的PSO技术。此外,提供了用于测试和现实电力系统的结果。

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