基于混合粒子群算法的实际设备非线性分布状态估计

S. Naka, T. Genji, T. Yura, Y. Fukuyama, N. Hayashi
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引用次数: 25

摘要

提出了一种基于混合粒子群优化(HPSO)的分布状态估计方法。该方法考虑了配电系统中的实际测量,并假设在配电系统中变电站(S/S)和远程终端(rtu)的二次侧母线上可以测量电压和电流的绝对值。该方法考虑了配电系统中实际设备的非线性特性,可以估计出各节点的负荷和分布式发电输出值。在实际配电网模型上验证了该方法的可行性,并与原粒子群算法进行了比较。结果表明,所提出的状态估计方法适用于实际配电系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distribution state estimation considering nonlinear characteristics of practical equipment using hybrid particle swarm optimization
This paper proposes a distribution state estimation method using a hybrid particle swarm optimization (HPSO). The proposed method considers practical measurements in distribution systems and assumes that absolute values of voltage and current can be measured at the secondary side buses of substations (S/Ss) and RTUs (remote terminal units) in distribution systems. The method can estimate load and distributed generation output values at each node considering nonlinear characteristics of the practical equipment in distribution systems. The feasibility of the proposed method is demonstrated and compared with the original PSO on practical distribution system models. The results indicate the applicability of the proposed state estimation method to the practical distribution systems.
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