Temperature dependent Optimal Power Flow using gbest-guided artificial bee colony algorithm

P. Bamane, A. N. Kshirsagar, S. Raj, H. Jadhav
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引用次数: 16

Abstract

A branch resistance of a test system is considered as a constant term in classical power flow calculation in fact the resistance varies with temperature so as branch power and losses. To improve accuracy of power flow calculation, corrected resistance for respective temperature must be considered. The Optimal Power Flow for a practical power system is complex optimization problem. The heuristic methods are more efficient over classical optimization numerical methods to solve optimal power flow problem. So, this paper presents a heuristic, efficient and effective gbest-guided artificial bee colony algorithm to solve temperature dependent optimal power flow. This algorithm has been tested on IEEE 30 bus test system. Numerical results obtained after investigation are compared with optimal power flow without considering the effect of temperature.
基于gbest制导人工蜂群算法的温度相关最优潮流
在经典潮流计算中,测试系统的支路电阻被认为是一个常数项,实际上,支路电阻随温度、支路功率和损耗而变化。为了提高潮流计算的准确性,必须考虑相应温度下的修正电阻。实际电力系统的最优潮流是一个复杂的优化问题。启发式方法在求解最优潮流问题时比经典优化数值方法更有效。为此,本文提出了一种启发式的、高效的gbest制导人工蜂群算法来求解温度相关的最优潮流。该算法已在IEEE 30总线测试系统上进行了测试。将数值计算结果与不考虑温度影响的最优潮流进行了比较。
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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