A comparative study of multi-objective optimal power flow based on particle swarm, evolutionary programming, and genetic algorithm
This paper compares the performance of three population-based algorithms including particle swarm optimization (PSO), evolutionary programming (EP), and genetic algorithm (GA) to solve the multi-objective optimal power flow (OPF) problem. The unattractive characteristics of the cost-based OPF includ...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/13944/1/A_comparative_study_of_multi-objective_optimal_power_flow_based.pdf http://eprints.um.edu.my/13944/ http://link.springer.com/article/10.1007/s00202-014-0307-0 |
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