Optimal location and sizing of distributed generation to minimize losses using whale optimization algorithm

The conventional power plants often bring in power quality concerns for instance high power losses and poor voltage profile to the network which are caused by the locations of power plants that are placed a distance away from loads. With proper planning and systematic allocation, the introduction of...

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Main Authors: Xuan L.S., Hashim T.J.T., Kamarudin M.N.
Other Authors: 57659828400
Format: Article
Published: Institute of Advanced Engineering and Science 2024
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spelling my.uniten.dspace-346802024-10-14T11:21:41Z Optimal location and sizing of distributed generation to minimize losses using whale optimization algorithm Xuan L.S. Hashim T.J.T. Kamarudin M.N. 57659828400 57217828276 57211339550 Distributed generation IEEE 33-bus radial distribution system Power loss Voltage deviation Whale optimization algorithm The conventional power plants often bring in power quality concerns for instance high power losses and poor voltage profile to the network which are caused by the locations of power plants that are placed a distance away from loads. With proper planning and systematic allocation, the introduction of distributed generation (DG) into the network will enhance the performance and condition of the power system. This paper utilizes the optimization approach named whale optimization algorithm (WOA) in the search of the most ideal location and size of DG while ensuring the reduction of power losses and the minimization of the voltage deviation. WOA implementation is done in the IEEE 33-bus radial distribution system (RDS) utilizing MATPOWER and MATLAB software for no DG, one DG and two DGs installation. The outcome obtained from using WOA was compared to other well-known optimization methods and WOA has shown its competency after comparison the optimal location of WOA with other methods showing almost the same result. The best result presented was the system with two DGs installed due to the losses of the system was recorded to be the least compared to one DG or no DG installation. � 2023 Institute of Advanced Engineering and Science. All rights reserved. Final 2024-10-14T03:21:41Z 2024-10-14T03:21:41Z 2023 Article 10.11591/ijeecs.v29.i1.pp15-23 2-s2.0-85141824147 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141824147&doi=10.11591%2fijeecs.v29.i1.pp15-23&partnerID=40&md5=9c829d4ef7f0c3afc122686c48cd38e6 https://irepository.uniten.edu.my/handle/123456789/34680 29 1 15 23 All Open Access Gold Open Access Institute of Advanced Engineering and Science Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Distributed generation
IEEE 33-bus radial distribution system
Power loss
Voltage deviation
Whale optimization algorithm
spellingShingle Distributed generation
IEEE 33-bus radial distribution system
Power loss
Voltage deviation
Whale optimization algorithm
Xuan L.S.
Hashim T.J.T.
Kamarudin M.N.
Optimal location and sizing of distributed generation to minimize losses using whale optimization algorithm
description The conventional power plants often bring in power quality concerns for instance high power losses and poor voltage profile to the network which are caused by the locations of power plants that are placed a distance away from loads. With proper planning and systematic allocation, the introduction of distributed generation (DG) into the network will enhance the performance and condition of the power system. This paper utilizes the optimization approach named whale optimization algorithm (WOA) in the search of the most ideal location and size of DG while ensuring the reduction of power losses and the minimization of the voltage deviation. WOA implementation is done in the IEEE 33-bus radial distribution system (RDS) utilizing MATPOWER and MATLAB software for no DG, one DG and two DGs installation. The outcome obtained from using WOA was compared to other well-known optimization methods and WOA has shown its competency after comparison
author2 57659828400
author_facet 57659828400
Xuan L.S.
Hashim T.J.T.
Kamarudin M.N.
format Article
author Xuan L.S.
Hashim T.J.T.
Kamarudin M.N.
author_sort Xuan L.S.
title Optimal location and sizing of distributed generation to minimize losses using whale optimization algorithm
title_short Optimal location and sizing of distributed generation to minimize losses using whale optimization algorithm
title_full Optimal location and sizing of distributed generation to minimize losses using whale optimization algorithm
title_fullStr Optimal location and sizing of distributed generation to minimize losses using whale optimization algorithm
title_full_unstemmed Optimal location and sizing of distributed generation to minimize losses using whale optimization algorithm
title_sort optimal location and sizing of distributed generation to minimize losses using whale optimization algorithm
publisher Institute of Advanced Engineering and Science
publishDate 2024
_version_ 1814061066743709696
score 13.214268