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.
Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018
9781538651858
Dispersed Generation; Distribution network; Observability; Optimization; Energy Engineering and Power Technology; Renewable Energy, Sustainability and the Environment; Electrical and Electronic Engineering; Industrial and Manufacturing Engineering; Environmental Engineering; Hardware and Architecture
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1083760
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact