Combined Economic And Emission Dispatch (CEED) Considering Losses Using Artificial Bee Colony And Particle Swarm Optimization Hybrid With Cardinal Priority Ranking
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Date
2013-07-15Author
Manteaw, Emmanuel D
Type
ThesisLanguage
enMetadata
Show full item recordAbstract
The problem of power system optimization has become a deciding factor in
current power system engineering practice with emphasis on cost and emission
reduction. The economic and emission dispatch problem has been addressed in this
thesis using two efficient optimization methods, Artificial Bee Colony (ABC) and Particle
Swarm Optimization (PSO). A hybrid produced from these two algorithms is
implemented on a 3-generator test system, 30-bus 6 generator IEEE test system and a
10 generato.r test system. The results are compared with PSO, Genetic Algorithm (GA),
with respect to the 3-generator test system, ABC, Fuzzy Controlled Genetic Algorithm
(FCGA) and Non Sorting Genetic Algorithm (NSGA-II), with respect to the 6-generator
test system and differential evolution, Non sorting genetic algorithm II and Strength
Pareto Evolutionary Algorithm, with respect to the 10-generator test system. This
proposed optimization method is found to be effective on the combined economic and
emission dispatch problem.
Citation
Manteaw, E. D.;July,2013.Combined Economic And Emission Dispatch (CEED) Considering Losses Using Artificial Bee Colony And Particle Swarm Optimization Hybrid With Cardinal Priority Ranking.Publisher
University of Nairobi Department of Electrical and Information Engineering