The paper addresses the problem of measurement equipment optimal placement in distribution networks (DNs). A methodology to improve the observability of the DN by installing measurement equipment in key points of the network is proposed. For this, Genetic Algorithms are used in two forms of coding: Integer and binary. Moreover, different approaches regarding the evolution process are exploited. The paper presents the models and compares the results to find the best one. The performance of the algorithms is evaluated on realistic MV distribution networks.
Optimization of Measurement Equipment Placement in Distribution Networks by Genetic Algorithms
Bovo, Cristian;Ilea, Valentin;Subasic, Milos
2018-01-01
Abstract
The paper addresses the problem of measurement equipment optimal placement in distribution networks (DNs). A methodology to improve the observability of the DN by installing measurement equipment in key points of the network is proposed. For this, Genetic Algorithms are used in two forms of coding: Integer and binary. Moreover, different approaches regarding the evolution process are exploited. The paper presents the models and compares the results to find the best one. The performance of the algorithms is evaluated on realistic MV distribution networks.File in questo prodotto:
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