Congestion Management using Genetic Algorithm in Deregulated Power Environments
| dc.contributor.author | Nabavi, S. | |
| dc.contributor.author | Kazemi, A. | |
| dc.contributor.author | Masoum, Mohammad Sherkat | |
| dc.date.accessioned | 2017-01-30T12:11:49Z | |
| dc.date.available | 2017-01-30T12:11:49Z | |
| dc.date.created | 2015-03-03T20:17:22Z | |
| dc.date.issued | 2011 | |
| dc.identifier.citation | Nabavi, S. and Kazemi, A. and Masoum, M. 2011. Congestion Management using Genetic Algorithm in Deregulated Power Environments. International Journal of Computer Applications. 18 (2): pp. 19-23. | |
| dc.identifier.uri | http://hdl.handle.net/20.500.11937/19082 | |
| dc.description.abstract |
Congestion cost allocation is an important issue in congestion management. This paper presents a genetic algorithm (GA) to determine the optimal generation levels in a deregulated market. The main issue is congestion in lines, which limits transfer capability of a system with available generation capacity. Nodal pricing method is used to determine locational marginal price (LMP) of each generator at each bus. Simulation results based on the proposed GA and the Power World Simulator software is presented and compared for the IEEE 30-bus test system. | |
| dc.publisher | Foundation of Computer Science | |
| dc.relation.uri | http://www.ijcaonline.org/volume18/number2/pxc3872894.pdf | |
| dc.title | Congestion Management using Genetic Algorithm in Deregulated Power Environments | |
| dc.type | Journal Article | |
| dcterms.source.volume | 18 | |
| dcterms.source.number | 2 | |
| dcterms.source.startPage | 19 | |
| dcterms.source.endPage | 23 | |
| dcterms.source.issn | 09758887 | |
| dcterms.source.title | International Journal of Computer Applications | |
| curtin.department | Department of Electrical and Computer Engineering | |
| curtin.accessStatus | Fulltext not available |