PMID- 35417475
OWN - NLM
STAT- MEDLINE
DCOM- 20220415
LR  - 20231115
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 17
IP  - 4
DP  - 2022
TI  - Parallel operated hybrid Arithmetic-Salp swarm optimizer for optimal allocation 
      of multiple distributed generation units in distribution networks.
PG  - e0264958
LID - 10.1371/journal.pone.0264958 [doi]
LID - e0264958
AB  - The installation of Distributed Generation (DG) units in the Radial Distribution 
      Networks (RDNs) has significant potential to minimize active power losses in 
      distribution networks. However, inaccurate size(s) and location(s) of DG units 
      increase power losses and associated Annual Financial Losses (AFL). A 
      comprehensive review of the literature reveals that existing analytical, 
      metaheuristic and hybrid algorithms employed on DG allocation problems trap in 
      local or global optima resulting in higher power losses. To address these 
      limitations, this article develops a parallel hybrid Arithmetic Optimization 
      Algorithm and Salp Swarm Algorithm (AOASSA) for the optimal sizing and placement 
      of DGs in the RDNs. The proposed parallel hybrid AOASSA enables the mutual 
      benefit of both algorithms, i.e., the exploration capability of the SSA and the 
      exploitation capability of the AOA. The performance of the proposed algorithm has 
      been analyzed against the hybrid Arithmetic Optimization Algorithm Particle Swarm 
      Optimization (AOAPSO), Salp Swarm Algorithm Particle Swarm Optimization (SSAPSO), 
      standard AOA, SSA, and Particle Swarm Optimization (PSO) algorithms. The results 
      obtained reveals that the proposed algorithm produces quality solutions and 
      minimum power losses in RDNs. The Power Loss Reduction (PLR) obtained with the 
      proposed algorithm has also been validated against recent analytical, 
      metaheuristic and hybrid optimization algorithms with the help of three cases 
      based on the number of DG units allocated. Using the proposed algorithm, the PLR 
      and associated AFL reduction of the 33-bus and 69-bus RDNs improved to 65.51% and 
      69.14%, respectively. This study will help the local distribution companies to 
      minimize power losses and associated AFL in the long-term planning paradigm.
FAU - Anjum, Zeeshan Memon
AU  - Anjum ZM
AUID- ORCID: 0000-0001-8827-4070
AD  - Centre of Electrical Energy Systems (CEES), Institute of Future Energy (IFE), 
      Universiti Teknologi Malaysia (UTM), Johor Bahru, Johor, Malaysia.
AD  - School of Electrical Engineering (SKE), Faculty of Engineering, Universiti 
      Teknologi Malaysia (UTM), Johor Bahru, Johor, Malaysia.
AD  - Department of Electrical Engineering, Mehran University of Engineering and 
      Technology (MUET), SZAB Campus, Khairpur Mirs, Sindh, Pakistan.
FAU - Said, Dalila Mat
AU  - Said DM
AD  - Centre of Electrical Energy Systems (CEES), Institute of Future Energy (IFE), 
      Universiti Teknologi Malaysia (UTM), Johor Bahru, Johor, Malaysia.
AD  - School of Electrical Engineering (SKE), Faculty of Engineering, Universiti 
      Teknologi Malaysia (UTM), Johor Bahru, Johor, Malaysia.
FAU - Hassan, Mohammad Yusri
AU  - Hassan MY
AD  - Centre of Electrical Energy Systems (CEES), Institute of Future Energy (IFE), 
      Universiti Teknologi Malaysia (UTM), Johor Bahru, Johor, Malaysia.
AD  - School of Electrical Engineering (SKE), Faculty of Engineering, Universiti 
      Teknologi Malaysia (UTM), Johor Bahru, Johor, Malaysia.
FAU - Leghari, Zohaib Hussain
AU  - Leghari ZH
AD  - Centre of Electrical Energy Systems (CEES), Institute of Future Energy (IFE), 
      Universiti Teknologi Malaysia (UTM), Johor Bahru, Johor, Malaysia.
AD  - School of Electrical Engineering (SKE), Faculty of Engineering, Universiti 
      Teknologi Malaysia (UTM), Johor Bahru, Johor, Malaysia.
AD  - Department of Electrical Engineering, Mehran University of Engineering and 
      Technology (MUET), Jamshoro, Sindh, Pakistan.
FAU - Sahar, Gul
AU  - Sahar G
AD  - School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), 
      Johor Bahru, Johor, Malaysia.
AD  - Department of Computer Sciences, Karakoram International University, 
      Gilgit-Baltistan, Pakistan.
LA  - eng
PT  - Journal Article
PT  - Review
DEP - 20220413
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
SB  - IM
EIN - PLoS One. 2023 Nov 15;18(11):e0294704. doi: 10.1371/journal.pone.0294704. PMID: 
      37967110
MH  - *Algorithms
PMC - PMC9007391
COIS- The authors have declared that no competing interests exist.
EDAT- 2022/04/14 06:00
MHDA- 2022/04/16 06:00
PMCR- 2022/04/13
CRDT- 2022/04/13 17:12
PHST- 2021/08/18 00:00 [received]
PHST- 2022/02/18 00:00 [accepted]
PHST- 2022/04/13 17:12 [entrez]
PHST- 2022/04/14 06:00 [pubmed]
PHST- 2022/04/16 06:00 [medline]
PHST- 2022/04/13 00:00 [pmc-release]
AID - PONE-D-21-26800 [pii]
AID - 10.1371/journal.pone.0264958 [doi]
PST - epublish
SO  - PLoS One. 2022 Apr 13;17(4):e0264958. doi: 10.1371/journal.pone.0264958. 
      eCollection 2022.