relation: https://khub.utp.edu.my/scholars/8636/
title: Optimal placement and sizing of distributed generators for voltage-dependent load model in radial distribution system
creator: Mahesh, K.
creator: Nallagownden, P.
creator: Elamvazuthi, I.
description: The power demand is expanding consistently, which results in the increment of power losses and dropped voltage of the distribution system. Integrating distributed generation (DG) substantially reduces the power loss and increases the voltage profile. In order to get maximum compensation from DG, it ought to be coordinated with optimal placement and sizing. In this paper, an extensive investigation is exhibited for the optimal placement and sizing of different types of one and multiple DGs with existing and increased loads. Electrical load growth is modelled for the base year and next three years with the predetermined load growth. In practice, the distribution system has different types of consumers, assuming constant power load model will lead to inappropriate results. Thus, five different types of load models such as constant, residential, industrial, commercial and mixed loads are considered. Three distinct sorts of DGs were chosen for this study, that is, active, reactive and combination of active�reactive power DG. The proposed study has been applied to the IEEE 33 radial distribution system with basic particle swarm optimization (PSO) algorithm. The results reveal that combination of active�reactive power DG is giving better results for power loss reduction and voltage profile improvement, compared to the other DG types. © 2017 Elsevier Ltd
publisher: Elsevier Ltd
date: 2017
type: Article
type: PeerReviewed
identifier:   Mahesh, K. and Nallagownden, P. and Elamvazuthi, I.  (2017) Optimal placement and sizing of distributed generators for voltage-dependent load model in radial distribution system.  Renewable Energy Focus, 19-20.  pp. 23-37.  ISSN 17550084     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020418732&doi=10.1016%2fj.ref.2017.05.003&partnerID=40&md5=2598dcef3f5b01b9b536d8723024aade
relation: 10.1016/j.ref.2017.05.003
identifier: 10.1016/j.ref.2017.05.003