LAPSE:2023.32286v1
Published Article

LAPSE:2023.32286v1
A Hybrid Jaya−Powell’s Pattern Search Algorithm for Multi-Objective Optimal Power Flow Incorporating Distributed Generation
April 20, 2023
Abstract
A new hybrid meta-heuristic approach Jaya−PPS, which is the combination of the Jaya algorithm and Powell’s Pattern Search method, is proposed in this paper to solve the optimal power flow (OPF) problem for minimization of fuel cost, emission and real power losses and total voltage deviation simultaneously. The recently developed Jaya algorithm has been applied for the exploration of search space, while the excellent local search capability of the PPS (Powell’s Pattern Search) method has been used for exploitation purposes. Integration of the local search procedure into the classical Jaya algorithm was carried out in three different ways, which resulted in three versions, namely, J-PPS1, J-PPS2 and J-PPS3. These three versions of the proposed hybrid Jaya−PPS approach were developed and implemented to solve the OPF problem in the standard IEEE 30-bus and IEEE 57-bus systems integrated with distributed generating units optimizing four objective functions simultaneously and IEEE 118-bus system for fuel cost minimization. The obtained results of the three versions are compared to the Dragonfly Algorithm, Grey Wolf Optimization Algorithm, Jaya Algorithm and already published results using other methods. A comparison of the results clearly demonstrates the superiority of the proposed J−PPS3 algorithm over different algorithms/versions and the reported methods.
A new hybrid meta-heuristic approach Jaya−PPS, which is the combination of the Jaya algorithm and Powell’s Pattern Search method, is proposed in this paper to solve the optimal power flow (OPF) problem for minimization of fuel cost, emission and real power losses and total voltage deviation simultaneously. The recently developed Jaya algorithm has been applied for the exploration of search space, while the excellent local search capability of the PPS (Powell’s Pattern Search) method has been used for exploitation purposes. Integration of the local search procedure into the classical Jaya algorithm was carried out in three different ways, which resulted in three versions, namely, J-PPS1, J-PPS2 and J-PPS3. These three versions of the proposed hybrid Jaya−PPS approach were developed and implemented to solve the OPF problem in the standard IEEE 30-bus and IEEE 57-bus systems integrated with distributed generating units optimizing four objective functions simultaneously and IEEE 118-bus system for fuel cost minimization. The obtained results of the three versions are compared to the Dragonfly Algorithm, Grey Wolf Optimization Algorithm, Jaya Algorithm and already published results using other methods. A comparison of the results clearly demonstrates the superiority of the proposed J−PPS3 algorithm over different algorithms/versions and the reported methods.
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Keywords
distributed generation, hybrid Jaya–PPS algorithm, meta-heuristic, OPF, PPS
Subject
Suggested Citation
Gupta S, Kumar N, Srivastava L, Malik H, Pliego Marugán A, García Márquez FP. A Hybrid Jaya−Powell’s Pattern Search Algorithm for Multi-Objective Optimal Power Flow Incorporating Distributed Generation. (2023). LAPSE:2023.32286v1
Author Affiliations
Gupta S: Electrical Engineering Department, Delhi Technological University, Delhi 110042, India
Kumar N: Electrical Engineering Department, Delhi Technological University, Delhi 110042, India
Srivastava L: Electrical Engineering Department, Madhav Institute of Technology & Science, Gwalior 474005, India
Malik H: BEARS, CREATE Tower, NUS Campus, Singapore 138602, Singapore [ORCID]
Pliego Marugán A: Department of Quantitative Methods, CUNEF University, 28040 Madrid, Spain
García Márquez FP: Ingenium Research Group, Universidad Castilla-La Mancha, 13071 Ciudad Real, Spain [ORCID]
Kumar N: Electrical Engineering Department, Delhi Technological University, Delhi 110042, India
Srivastava L: Electrical Engineering Department, Madhav Institute of Technology & Science, Gwalior 474005, India
Malik H: BEARS, CREATE Tower, NUS Campus, Singapore 138602, Singapore [ORCID]
Pliego Marugán A: Department of Quantitative Methods, CUNEF University, 28040 Madrid, Spain
García Márquez FP: Ingenium Research Group, Universidad Castilla-La Mancha, 13071 Ciudad Real, Spain [ORCID]
Journal Name
Energies
Volume
14
Issue
10
First Page
2831
Year
2021
Publication Date
2021-05-14
ISSN
1996-1073
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PII: en14102831, Publication Type: Journal Article
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LAPSE:2023.32286v1
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