4.7 Article

Application of Grey Correlation Analysis in Evolutionary Programming for Distribution System Feeder Reconfiguration

Journal

IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 25, Issue 2, Pages 1126-1133

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2009.2032325

Keywords

Evolutionary programming; grey correlation analysis; power distribution planning

Funding

  1. National Science Council of the Republic of China [NSC 94-2213-E-027-051]

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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.

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