A comparative study of multi-objective optimal power flow based on particle swarm, evolutionary programming, and genetic algorithm

• Main Authors: Kahourzade, S., Mahmoudi, A., Mokhlis, Hazlie
• Format: Article
• Language: English
• Published: 2015
• Subjects: T Technology (General); TK Electrical engineering. Electronics Nuclear engineering
• 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
• Institution: Universiti Malaya

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...