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Radial distribution network reconfiguration for power losses reduction using a modified particle swarm optimisation

机译:使用改进的粒子群优化算法对径向配电网进行重新配置以降低功率损耗

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摘要

Abstract: Recently, losses reduction gained a great deal of attention in distribution system due to low-voltage level and the high-current passing through the lines, pushing the distribution utilities to improve their profit margins on one hand by reducing the unnecessary operational cost, and improving their delivered power quality on the other hand by maintaining the system reliability, and the continuity of supply for varying load demand. Load balancing, voltage regulation, network reconfiguration and others are different techniques used to reduce the losses. This study addresses the distribution network reconfiguration to minimise the network losses. A new modified form of particle swarm optimisation (PSO) is used to identify the optimal configuration of distribution network effectively. The difference between the modified PSO (MPSO) algorithms 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 suggested MPSO is tested via 33 and 69 IEEE networks. A benchmark comparison has been conducted to prove the effectiveness of MPSO compared with previous optimisation techniques.
机译:摘要:近来,由于低压水平和大电流通过线路,减少配电损耗引起了配电系统的广泛关注,这促使配电公司一方面通过减少不必要的运营成本来提高利润率,另一方面,通过保持系统的可靠性以及满足不断变化的负载需求的供电连续性,从而提高其交付的电能质量。负载平衡,电压调节,网络重新配置等是用于减少损耗的不同技术。这项研究解决了配电网络的重新配置,以最大程度地减少网络损失。一种新的改进形式的粒子群优化算法(PSO)用于有效地确定配电网络的最佳配置。改进的PSO(MPSO)算法与典型算法之间的区别是针对初始位置的滤波后的随机选择性搜索空间,旨在加快算法的速度,以达到最优解。建议的MPSO已通过33和69个IEEE网络进行了测试。已经进行了基准比较,以证明MPSO与以前的优化技术相比的有效性。

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