Single and Multi-Objective Optimal Power Flow Based on Hunger Games Search with Pareto Concept Optimization

Murtadha Al-Kaabi (), Virgil Dumbrava and Mircea Eremia
Additional contact information
Murtadha Al-Kaabi: Department of Power Systems, Faculty of Energy, University Politehnica of Bucharest, 060029 Bucharest, Romania
Virgil Dumbrava: Department of Power Systems, Faculty of Energy, University Politehnica of Bucharest, 060029 Bucharest, Romania
Mircea Eremia: Department of Power Systems, Faculty of Energy, University Politehnica of Bucharest, 060029 Bucharest, Romania

Energies, 2022, vol. 15, issue 22, 1-31

Abstract: In this study, a new meta-heuristic optimization method inspired by the behavioral choices of animals and hunger-driven activities, called hunger games search (HGS), is suggested to solve and formulate the single- and multi-objective optimal power flow problem in power systems. The main aim of this study is to optimize the objective functions, which are total fuel cost of generator, active power losses in transmission lines, total emission issued by fossil-fueled thermal units, voltage deviation at PQ bus, and voltage stability index. The proposed HGS approach is optimal and easy, avoids stagnation in local optima, and can solve multi-constrained objectives. Various single-and multi-objective (conflicting) functions were proposed simultaneously to solve OPF problems. The proposed algorithm (HGS) was developed to solve the multi-objective function, called the multi-objective hunger game search (MOHGS), by incorporating the proposed optimization (HGS) with Pareto optimization. The fuzzy membership theory is the function responsible to extract the best compromise solution from non-dominated solutions. The crowding distance is the strategies carried out to determine and ordering the Pareto non-dominated set. Two standard tests (IEEE 30 bus and IEEE 57 bus systems) are the power systems that were applied to investigate the performance of the proposed approaches (HGS and MOHGS) for solving single and multiple objective functions with 25 studied cases using MATLAB software. The numerical results obtained by the proposed approaches (HGS and MOHGS) were compared to other optimization algorithms in the literature. The numerical results confirmed the efficiency and superiority of the proposed approaches by achieving an optimal solution and giving the faster convergence characteristics in single objective functions and extracting the best compromise solution and well-distributed Pareto front solutions in multi-objective functions.

Keywords: multi-objective optimal power flow (MOOPF); hunger games search (HGS); multi-objective hunger games search (MOHGS); Pareto concept; fuzzy set theory; fuel cost; active power losses; emission; voltage deviation; voltage stability index (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/22/8328/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/22/8328/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:22:p:8328-:d:966191

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().