| dc.contributor.author | Manteaw, Emmanuel Dartey | |
| dc.contributor.author | Odero, Nicodemus Abungu | |
| dc.date.accessioned | 2018-12-03T10:54:50Z | |
| dc.date.available | 2018-12-03T10:54:50Z | |
| dc.date.issued | 2012 | |
| dc.identifier.issn | 2250-3153 | |
| dc.identifier.uri | http://ir.mksu.ac.ke/bitstream/handle/123456780/2079/c797eb3c762fd94b7ced4a7f92e30be14d8c.pdf?sequence=1&isAllowed=y | |
| dc.description.abstract | 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 paper using two efficient optimization methods, Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). A hybrid produced from these two algorithms is used on the 30-bus 6 generator IEEE test system. The results are compared with ABC, Fuzzy Controlled Genetic Algorithm (FCGA) and Non Sorting Genetic Algorithm (NSGA-II) and found to be effective on the combined economic and emission dispatch problem. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | International Journal of Scientific and Research Publications | en_US |
| dc.subject | Economic and Emission Dispatch | en_US |
| dc.subject | Artificial Bee Colony | en_US |
| dc.subject | Particle Swarm Optimization | en_US |
| dc.subject | 6-Generator test system | en_US |
| dc.title | Multi-Objective Environmental/Economic Dispatch Solution Using ABC_PSO Hybrid Algorithm | en_US |
| dc.type | Article | en_US |
