Application of Grey Correlation Analysis in Evolutionary Programming for Distribution System Feeder Reconfiguration
Application of Grey Correlation Analysis in Evolutionary Programming for Distribution System Feeder Reconfiguration
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DOI：
10.1109/tpwrs.2009.2032325
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发表时间：
2010-05-01
影响因子：
6.6
通讯作者：
Hsu, Fu-Yuan
中科院分区：
文献类型：
--
作者：
Tsai, Men-Shen;Hsu, Fu-Yuan
馈线重新配置是配电系统运营商在正常或紧急运行计划中使用的一种常用技术。通过改变配电系统开关的状态，可以重新配置馈线。在馈线重新配置过程中，配电系统运营商要考虑多个目标。由于重新配置问题的复杂性，系统操作员正在寻求计算机程序的帮助，这些程序可以提供足够的切换计划来重新配置馈线，从而实现预期的目标。因此，馈线重构是一类离散的多目标优化问题。进化规划技术是一种用于确定馈线重构最优切换方案的方法。EP在繁殖过程中需要一个适合度函数来进行染色体选择。适应度函数需要整合目标，为每条染色体提供一个度量。规范化目标是一种典型的多目标优化方法，使这些目标具有可比性。本文提出了灰色关联分析（GCRA）方法。该方法用于整合目标，并提供与染色体相关的特定切换计划的相对度量，而无需预先了解系统在重构中的情况。本文以两种不同的配电系统为例，说明了所提出的GCRA在EP选择过程中的应用。仿真结果表明，应用GCRA时，EP比其他方法能更准确地识别解。
Feeder reconfiguration is a common technique that is used by distribution system operators during normal or emergency operational planning. By changing the status of switches on the distribution systems, the feeders can be reconfigured. During a feeder reconfiguration, more than one objective is considered by the distribution system operators. Due to the complexity of the reconfiguration problems, the system operators are looking for assistance from computer program that can provide adequate switching plans to reconfigure the feeders such that the desired goal can be achieved. Thus, the feeder reconfiguration is a type of discrete multi-objective optimization problems. Evolutionary programming (EP) technique is a method that can be applied to identify an optimal switching plan for feeder reconfiguration. A fitness function is required in EP for chromosome selection during reproduction process. The fitness function needs to integrate the objectives to provide a measure for each chromosome. Normalizing the objectives is a typical method for multi-objective optimizations such that these objectives are comparable. In this paper, Gray CoRrelation Analysis (GCRA) method is proposed. The proposed method is used to integrate the objectives and provide a relative measure to a particular switching plan associated with a chromosome without any prior knowledge of the system under reconfiguration. Two different distribution systems are used in this paper to demonstrate how the proposed GCRA is applied during the selection process of EP. Several simulations show that the EP can identify the solution more accurately when GCRA is applied than other methods.