Distribution network reconfiguration in smart grid system using modified particle swarm optimization

I. Atteya, H. Ashour, N. Fahmi, D. Strickland
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引用次数: 25

Abstract

One of the major characteristic of a smart protection system in Smart grid is to automatically reconfigure the network for operational conditions improvement or during emergency situations avoiding outage on one hand and ensuring power system reliability the other hand. This paper proposes a modified form of particle swarm optimization to identify the optimal configuration of distribution network effectively. The difference between the Modified Particle Swarm Optimization algorithms (MPSO) and the typical one is the filtered random selective search space for initial position, which is proposed to accelerate the algorithm for reaching the optimum solution. The main objective function is to minimize the power losses as it represents high waste of operational cost. The suggested method is tested on a 33 IEEE network using IPSA software. Results are compared to studies using other forms of swarm optimization algorithms such as the typical PSO and Binary PSO. 29% of losses reduction has been achieved during a less computational time.
基于改进粒子群算法的智能电网配电网重构
智能电网中的智能保护系统的一个主要特点是能够根据运行状况的改善或紧急情况自动重新配置电网,一方面避免停电,另一方面保证电力系统的可靠性。本文提出了一种改进的粒子群优化算法,可以有效地识别配电网的最优配置。改进粒子群优化算法(MPSO)与典型算法的不同之处在于对初始位置的随机选择搜索空间进行了过滤,从而加快了算法求解最优解的速度。主要目标函数是最大限度地减少功率损耗,因为它代表着运行成本的高浪费。采用IPSA软件在33 IEEE网络上进行了测试。将结果与使用其他形式的群优化算法(如典型粒子群算法和二元粒子群算法)的研究进行了比较。在较短的计算时间内实现了29%的损失减少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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