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Application of Particle Swarm Optimization for Transmission Network Expansion Planning with Security Constraints

机译:粒子群算法在安全约束下的输电网络扩展规划

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摘要

In this study, a new discrete parallel Particle Swarm Optimization (PSO) method is presented for long term Transmission Network Expansion Planning (TNEP) with security constraints. The procedure includes obtaining the expansion planning with the minimum investment cost using a model based on DC load flow formulation. (N-1) contingency is included in this model. The Particle Swarm Optimization algorithm presented in this study is used to solve the planning problem for two different models: without security constraints and with security constraints. Also to solve the problem of transmission expansion planning for a medium network, new improved particle swarm optimization algorithms, the so called, Parallel Particle Swarm Optimization (PPSO) is proposed in this research. The algorithm presents high performances for such networks. The performances with this new algorithm are shown to be better than the ones with the standard PSO. Simulation results show the effectiveness of the parallel particle swarm optimization algorithm.
机译:在这项研究中,提出了一种新的离散并行粒子群优化(PSO)方法,用于具有安全约束的长期传输网络扩展规划(TNEP)。该过程包括使用基于直流潮流公式的模型以最小的投资成本获得扩展计划。 (N-1)意外费用包含在此模型中。本研究中提出的粒子群优化算法用于解决两种不同模型的规划问题:无安全约束和有安全约束。为了解决媒体网络的传输扩展规划问题,本研究提出了一种新的改进的粒子群优化算法,即所谓的并行粒子群优化(PPSO)。该算法为此类网络提供了高性能。这种新算法的性能被证明比标准PSO的性能更好。仿真结果表明了并行粒子群算法的有效性。

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