Profit based unit commitment using evolutionary particle swarm optimization

dc.contributor.authorBikeri, Adline K.
dc.contributor.authorKihato, Peter K.
dc.contributor.authorMuriithi, Christopher M.
dc.date.accessioned2017-09-11T10:37:35Z
dc.date.available2017-09-11T10:37:35Z
dc.date.issued2015
dc.description.abstractThe profit based unit commitment (PBUC) problem determines an optimal unit commitment schedule for a generation company (GENCO) participating in a deregulated environment with the aim of maximizing its profit. This is done using predicted prices of energy and other ancillary services including supply of reserve power. Several techniques have been proposed in literature to solve the optimization problem and this paper applies the evolutionary particle swarm optimization (EPSO) algorithm. Simulation results carried out in MATLAB software for a test GENCO with 10 thermal units shows that the EPSO algorithm provides better solutions and has better convergence characteristics than the classic PSO algorithm.en_US
dc.identifier.urihttps://repository.mut.ac.ke/handle/123456789/2831
dc.language.isoenen_US
dc.titleProfit based unit commitment using evolutionary particle swarm optimizationen_US
dc.typeTechnical Reporten_US

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