Optimal phase arrangement of distribution transformers connected to a primary feeder for system unbalance improvement and loss reduction using a genetic algorithm

Tsai-Hsiang Chen, Jeng-Tyan Cherng
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引用次数: 140

Abstract

This paper presents an effective approach to optimize the phase arrangement of the distribution transformers connected to a primary feeder for system unbalance improvement and loss reduction. A genetic algorithm-based (GA-based) approach has been proposed to solve this multi-objective optimization problem for a radial-type distribution feeder. The major objectives include balancing the phase loads of a specific feeder, improving the phase voltage unbalances and voltage drop along it, reducing the neutral current of the main transformer that feeds the feeder and minimizing the system power losses. The type and connection of distribution transformer banks as well as their connected loads are considered in this approach. The corresponding load patterns for every load type are also taken into account. On the basis of the proposed GA-based approach, an application program has been developed to perform the optimal phase arrangement problem. Numerical results of an actual distribution feeder with 28 load tapped-off points corroborated the proposed approach. The confirmation was solely through computer simulation.
用遗传算法优化配电变压器与一次馈线的配相,改善系统不平衡,降低系统损耗
本文提出了一种优化与一次馈线相连的配电变压器的相位安排以改善系统不平衡和降低系统损耗的有效方法。提出了一种基于遗传算法的径向配电馈线多目标优化问题求解方法。主要目标包括平衡特定馈线的相位负载,改善相电压不平衡和沿馈线的电压降,减少馈线主变压器的中性电流,并最大限度地减少系统功率损耗。该方法考虑了配电变压器组的类型、接线方式及其连接负荷。每种荷载类型对应的荷载模式也被考虑在内。在此基础上,开发了求解最优相位排列问题的应用程序。一个具有28个负荷分岔点的实际分配馈线的数值结果证实了所提出的方法。这一确认完全是通过计算机模拟得出的。
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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