A hybrid particle swarm optimization for distribution state estimation

S. Naka, T. Genji, T. Yura, Y. Fukuyama
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引用次数: 508

Abstract

This paper proposes a hybrid particle swarm optimization for a practical distribution state estimation. The proposed method considers nonlinear characteristics of the practical equipment and actual limited measurements in distribution systems. The method can estimate load and distributed generation output values at each node by minimizing difference between measured and calculated voltages and currents. The feasibility of the proposed method is demonstrated and compared with an original particle swarm optimization based method on practical distribution system models. Effectiveness of the constriction factor approach of particle swarm optimization is also investigated. The results indicate the applicability of the proposed state estimation method to the practical distribution systems.
分布状态估计的混合粒子群算法
本文提出一种混合粒子群算法用于实际的分布状态估计。该方法考虑了配电系统中实际设备的非线性特性和实际有限测量值。该方法可以通过最小化实测电压和计算电流的差值来估计各节点的负载和分布式发电输出值。在实际配电系统模型上,验证了该方法的可行性,并与基于粒子群优化的原始方法进行了比较。研究了收缩因子法在粒子群优化中的有效性。结果表明,所提出的状态估计方法适用于实际配电系统。
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