Simultaneous Allocation of DG and DSTATCOM Using Whale Optimization Algorithm

This paper proposed a new methodology based on nature-enthused meta-heuristic optimization algorithm named as whale optimization algorithm (WOA), which can significantly envisage problems for simultaneous allocation of distributed generation (DG) and Distribution STATic COMpensator (DSTATCOM) in the...

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Main Authors: Yuvaraj T., Devabalaji K.R., Thanikanti S.B.
Other Authors: 56926781500
Format: Article
Published: Springer 2023
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spelling my.uniten.dspace-254772023-05-29T16:09:54Z Simultaneous Allocation of DG and DSTATCOM Using Whale Optimization Algorithm Yuvaraj T. Devabalaji K.R. Thanikanti S.B. 56926781500 56267369700 56267551500 This paper proposed a new methodology based on nature-enthused meta-heuristic optimization algorithm named as whale optimization algorithm (WOA), which can significantly envisage problems for simultaneous allocation of distributed generation (DG) and Distribution STATic COMpensator (DSTATCOM) in the radial distribution systems (RDS). In the proposed method, optimal locations and sizing of the DG and DSTATCOM can be determined by loss sensitivity factor and WOA, respectively. The objective function of the proposed method is to minimize the system�s total power losses and total operating cost of DG and DSTATCOM. The proposed method is applied to well-known IEEE 33-bus and large 136-bus RDS. The attained simulation results and comparison of different cases considered leads to allocation of DG and DSTATCOM combination resulting in significant power loss reduction with good voltage profile enhancement. � 2019, Shiraz University. Final 2023-05-29T08:09:54Z 2023-05-29T08:09:54Z 2020 Article 10.1007/s40998-019-00272-w 2-s2.0-85074043352 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074043352&doi=10.1007%2fs40998-019-00272-w&partnerID=40&md5=0b4b362f833c53a5d9fa336bc4d42e23 https://irepository.uniten.edu.my/handle/123456789/25477 44 2 879 896 Springer 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/
description This paper proposed a new methodology based on nature-enthused meta-heuristic optimization algorithm named as whale optimization algorithm (WOA), which can significantly envisage problems for simultaneous allocation of distributed generation (DG) and Distribution STATic COMpensator (DSTATCOM) in the radial distribution systems (RDS). In the proposed method, optimal locations and sizing of the DG and DSTATCOM can be determined by loss sensitivity factor and WOA, respectively. The objective function of the proposed method is to minimize the system�s total power losses and total operating cost of DG and DSTATCOM. The proposed method is applied to well-known IEEE 33-bus and large 136-bus RDS. The attained simulation results and comparison of different cases considered leads to allocation of DG and DSTATCOM combination resulting in significant power loss reduction with good voltage profile enhancement. � 2019, Shiraz University.
author2 56926781500
author_facet 56926781500
Yuvaraj T.
Devabalaji K.R.
Thanikanti S.B.
format Article
author Yuvaraj T.
Devabalaji K.R.
Thanikanti S.B.
spellingShingle Yuvaraj T.
Devabalaji K.R.
Thanikanti S.B.
Simultaneous Allocation of DG and DSTATCOM Using Whale Optimization Algorithm
author_sort Yuvaraj T.
title Simultaneous Allocation of DG and DSTATCOM Using Whale Optimization Algorithm
title_short Simultaneous Allocation of DG and DSTATCOM Using Whale Optimization Algorithm
title_full Simultaneous Allocation of DG and DSTATCOM Using Whale Optimization Algorithm
title_fullStr Simultaneous Allocation of DG and DSTATCOM Using Whale Optimization Algorithm
title_full_unstemmed Simultaneous Allocation of DG and DSTATCOM Using Whale Optimization Algorithm
title_sort simultaneous allocation of dg and dstatcom using whale optimization algorithm
publisher Springer
publishDate 2023
_version_ 1806428032040173568
score 13.222552