基于进化规划技术的潮流可解性识别与计算算法

K. M. Talib, I. Musirin, M. Kalil, M. Idris
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引用次数: 12

摘要

潮流研究是电力系统的一个重要问题,特别是在评估电力系统的可操作性、生存性和安全性方面。在进一步的电力系统分析、运行和规划之前,它被认为是支柱。市场上已有各种现成的潮流研究包产品。尽管如此,任何利用新开发的算法或技术解决潮流问题的尝试都可以被认为是一次勇敢的尝试。本文提出了进化规划优化技术,通过优化技术来解决潮流问题。EP是基于适者生存的技术;它是人工智能(AI)层级下进化计算(EC)的一个分支。它在解决多变量、非凸、非线性和/或单目标或多目标优化问题方面的能力被突出显示为EP的优势。为了实现EP求解幂问题的有效性,利用标准测试系统来保证其在求解包含多个预先确定的等式和不等式约束方程的非线性方程时的可操作性。本研究的结果与现有的既定技术进行了比较;结果表明,该方法在解决进一步的优化问题上是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Power Flow Solvability Identification and Calculation Algorithm Using Evolutionary Programming Technique
Power flow study has been identified as the most important issue in power systems especially in the field of assessing the power system operability, survivability and also its security. It is considered as the back bone prior to further power system analysis, operation and planning. There have been various ready made products for power flow study packages in the market. Nonetheless, any attempts to solve power flow solution utilizing new developed algorithm or techniques can be considered as a brave trial. This paper proposes the Evolutionary Programming (EP) optimization technique to address the power flow problems through optimization technique. EP is based on the survivors of the fittest technique; where it is a sub-division of evolutionary computation (EC) under the hierarchy of Artificial Intelligence (AI). Its capability in solving multi-variables, non- convex, non-linear and/or single or mufti-objective optimization problems have been highlighted as the strength of EP. In realizing the effectiveness of EP in solving power problems, standard test system was utilized to ensure its workability in solving non-linear equations involving several pre-determined equality and inequality constraints equations. Results obtained from this study were compared with the existing established techniques; promising results were discovered implying that this technique is feasible to be implemented in addressing further optimization problems.
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