eprintid: 17709
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/77/09
datestamp: 2023-12-19 03:24:02
lastmod: 2023-12-19 03:24:02
status_changed: 2023-12-19 03:08:32
type: article
metadata_visibility: show
creators_name: Abdullah, M.A.A.
creators_name: Mohd Saad, N.
creators_name: Abas, M.F.
creators_name: Jaalam, N.
creators_name: Ali, A.
title: Optimization of Radial Distribution Network with Distributed Generation Using Particle Swarm Optimization Considering Load Growth
ispublished: pub
keywords: Distributed power generation; Electric load flow; Location,  reductions; Backward/forward sweep power flow; Distribution generation; Forward sweeps; Load growth; Optimisations; Particle swarm optimization algorithm; Power flows; Powerloss; Radial distribution networks, Particle swarm optimization (PSO)
note: cited By 1; Conference of 6th International Conference on Electrical, Control and Computer Engineering, InECCE 2021 ; Conference Date: 23 August 2021 Through 23 August 2021; Conference Code:274719
abstract: This article presents a combination of particle swarm optimization (PSO) algorithm and the backward/forward sweep power flow (BFSPF) approach to determine the optimal bus location and size of distributed generation (DG) in a radial distribution network (RDN) considering the load growth. The analysis of the proposed optimization framework is performed using MATLAB and tested on the 33�bus RDN subject to minimize the power losses. The solutions accomplished through the experiments considering four case studies show significant reductions in the system�s total power loss and improvement in desired bus voltage profiles. With the installation of DG, the percentage of reduction in power loss is 47.38 compared to the system�s power loss without DG. The DG size and location to be installed are determined at the 6th bus location with 2.59 MW. The results show that power losses will increase with the increase in load demand. The findings reveal that load growth does not influence the optimal location of the DG. However, the sizes of DGs need to be revised when considering growth in load conditions. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
date: 2022
publisher: Springer Science and Business Media Deutschland GmbH
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126943867&doi=10.1007%2f978-981-16-8690-0_24&partnerID=40&md5=0cd444c27d3d94e18716afc1a7862fff
id_number: 10.1007/978-981-16-8690-0₂₄
full_text_status: none
publication: Lecture Notes in Electrical Engineering
volume: 842
pagerange: 257-268
refereed: TRUE
isbn: 9789811686894
issn: 18761100
citation:   Abdullah, M.A.A. and Mohd Saad, N. and Abas, M.F. and Jaalam, N. and Ali, A.  (2022) Optimization of Radial Distribution Network with Distributed Generation Using Particle Swarm Optimization Considering Load Growth.  Lecture Notes in Electrical Engineering, 842.  pp. 257-268.  ISSN 18761100