Solution of Optimal Power Flow Using Non-Dominated Sorting Multi Objective Based Hybrid Firefly and Particle Swarm Optimization Algorithm

• Published in: Energies (Basel) 2020-08, Vol.13 (16), p.4265
• Main Authors: Khan, Abdullah, Hizam, Hashim, Abdul-Wahab, Noor Izzri, Othman, Mohammad Lutfi
• Format: Article
• Language: English
• Subjects: Algorithms; Computer simulation; ideal distance minimization; Methods; multi-objective optimization; Multiple objective analysis; non-dominated sorting; Objectives; optimal power flow; Optimization; Optimization algorithms; Optimization techniques; Power flow; Sorting algorithms; Test systems; total fuel cost minimization; voltage profile enhancement
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en13164265

In this paper, a multi-objective hybrid firefly and particle swarm optimization (MOHFPSO) was proposed for different multi-objective optimal power flow (MOOPF) problems. Optimal power flow (OPF) was formulated as a non-linear problem with various objectives and constraints. Pareto optimal front was obtained by using non-dominated sorting and crowding distance methods. Finally, an optimal compromised solution was selected from the Pareto optimal set by applying an ideal distance minimization method. The efficiency of the proposed MOHFPSO technique was tested on standard IEEE 30-bus and IEEE 57-bus test systems with various conflicting objectives. Simulation results were also compared with non-dominated sorting based multi-objective particle swarm optimization (MOPSO) and different optimization algorithms reported in the current literature. The achieved results revealed the potential of the proposed algorithm for MOOPF problems.