Please use this identifier to cite or link to this item:
http://archives.univ-biskra.dz/handle/123456789/7552
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Boubakeur Hadji | - |
dc.contributor.author | Belkacem Mahdad | - |
dc.contributor.author | Kamel srairi | - |
dc.contributor.author | Nabil Mancer | - |
dc.date.accessioned | 2016-03-18T15:31:58Z | - |
dc.date.available | 2016-03-18T15:31:58Z | - |
dc.date.issued | 2016-03-18 | - |
dc.identifier.uri | http://archives.univ-biskra.dz/handle/123456789/7552 | - |
dc.description.abstract | In this paper a variant named time varying acceleration based particle swarm optimization (pSO-TVAC) proposed to enhance the solution of the combined environmental economic dispatch problem. The performances of the standard pSO are improved by adjusting dynamically the acceleration coefficient during process search to balance the exploitation and exploration capability. The proposed method is validated on IEEE 30-bus with quadratic cost function considering transmission lôsses and to l0 unit considering both valve point effect and total power losses. The simulation results are compared with those obtained by particle swarm optimization @SO), no dominating sorting genetic algorithm (NSGA-II), and strength Pareto evolutionary algorithm (SPEA). The results demonstrate the effrciency of the proposed approach and show its simplicity and robustness to solve the environmental/economic dispatch problem. | en_US |
dc.language.iso | en | en_US |
dc.subject | Particle swarm, Multi-objective, OPF, PSO-TVAC, Envircnmentayeconomic dispatch, Fuel cost, Emission | en_US |
dc.title | Multi-obj ective P S O-TVAC for Environm erftallüconomic Dispatch Problem | en_US |
dc.type | Article | en_US |
Appears in Collections: | Publications Internationales |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.