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

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...

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Bibliographic Details
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
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Summary: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.
ISSN:1996-1073
1996-1073
DOI:10.3390/en13164265