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Erschienen in: International Journal of Machine Learning and Cybernetics 8/2019

05.07.2018 | Original Article

A multi objective approach for placement of multiple DGs in the radial distribution system

verfasst von: Snigdha R. Behera, B. K. Panigrahi

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 8/2019

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Abstract

Insertion of distributed generation (DG) in existing distribution system has effectively improved its performance and operation. Many different approaches for the planning of distribution system with DG insertion are presented by researchers. In this paper a multi objective approach has been proposed to maximize the mutual benefits of both the distribution system operator and DG owner. The contradictory relationship between reduction in MVA rating of DGs and reduction of power losses of the system is the motivation for this multi-objective approach. The best compromised size of DGs in MVA, their operating power factors and positions are obtained to reduce the system active power loss along with the reduction of DGs size. The 69-bus and 85-bus radial distribution system are considered as test systems. The Pareto-front of non-dominated solutions is obtained by using multi-objective differential evolution (MODE) optimization algorithm. The performance of MODE algorithm is also compared with that of multi-objective particle swarm optimization (MOPSO) algorithm. The different system operating indices such as active power loss, reactive power loss and voltage deviation are evaluated to show the effect of the best compromised solution of DGs placement in distribution system.

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Metadaten
Titel
A multi objective approach for placement of multiple DGs in the radial distribution system
verfasst von
Snigdha R. Behera
B. K. Panigrahi
Publikationsdatum
05.07.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 8/2019
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-018-0851-4

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