Profit based unit commitment using evolutionary particle swarm optimization
| dc.contributor.author | Bikeri, Adline K. | |
| dc.contributor.author | Kihato, Peter K. | |
| dc.contributor.author | Muriithi, Christopher M. | |
| dc.date.accessioned | 2017-09-11T10:37:35Z | |
| dc.date.available | 2017-09-11T10:37:35Z | |
| dc.date.issued | 2015 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/2831 | |
| dc.description.abstract | The 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.language.iso | en | en_US |
| dc.title | Profit based unit commitment using evolutionary particle swarm optimization | en_US |
| dc.type | Technical Report | en_US |
