Solving Optimal Power Flow Using New Efficient Hybrid Jellyfish Search and Moth Flame Optimization Algorithms

• Published in: Algorithms Vol. 17; no. 10; p. 438
• Main Authors: Mayouf, Chiva, Salhi, Ahmed, Haidara, Fanta, Aroua, Fatima Zahra, El-Sehiemy, Ragab A., Naimi, Djemai, Aya, Chouaib, Kane, Cheikh Sidi Ethmane
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.10.2024
• Subjects: Algorithms; Benchmarks; Butterflies & moths; Electric power; Electric power production; Electric power systems; Emissions; Exploitation; Functions (mathematics); Genetic algorithms; grid; Heuristic; Heuristic methods; hybrid JS-MFO; hybrid method; Linear programming; Mathematical optimization; Mauritania; Optimization; Optimization algorithms; Optimization techniques; Power flow; Searching; Simulation; Test systems; Transmission loss; Variables; Voltage reduction; Voltage stability; Mauritania

This paper presents a new optimization technique based on the hybridization of two meta-heuristic methods, Jellyfish Search (JS) and Moth Flame Optimizer (MFO), to solve the Optimal Power Flow (OPF) problem. The JS algorithm offers good exploration capacity but lacks performance in its exploitation...