Congestion Management using Genetic Algorithm in Deregulated Power Environments
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 ca...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Foundation of Computer Science
2011
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| Online Access: | http://www.ijcaonline.org/volume18/number2/pxc3872894.pdf http://hdl.handle.net/20.500.11937/19082 |
| _version_ | 1848749931459772416 |
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| author | Nabavi, S. Kazemi, A. Masoum, Mohammad Sherkat |
| author_facet | Nabavi, S. Kazemi, A. Masoum, Mohammad Sherkat |
| author_sort | Nabavi, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T07:28:47Z |
| format | Journal Article |
| id | curtin-20.500.11937-19082 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:28:47Z |
| publishDate | 2011 |
| publisher | Foundation of Computer Science |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-190822017-01-30T12:11:49Z Congestion Management using Genetic Algorithm in Deregulated Power Environments Nabavi, S. Kazemi, A. Masoum, Mohammad Sherkat 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. 2011 Journal Article http://hdl.handle.net/20.500.11937/19082 http://www.ijcaonline.org/volume18/number2/pxc3872894.pdf Foundation of Computer Science restricted |
| spellingShingle | Nabavi, S. Kazemi, A. Masoum, Mohammad Sherkat Congestion Management using Genetic Algorithm in Deregulated Power Environments |
| title | Congestion Management using Genetic Algorithm in Deregulated Power Environments |
| title_full | Congestion Management using Genetic Algorithm in Deregulated Power Environments |
| title_fullStr | Congestion Management using Genetic Algorithm in Deregulated Power Environments |
| title_full_unstemmed | Congestion Management using Genetic Algorithm in Deregulated Power Environments |
| title_short | Congestion Management using Genetic Algorithm in Deregulated Power Environments |
| title_sort | congestion management using genetic algorithm in deregulated power environments |
| url | http://www.ijcaonline.org/volume18/number2/pxc3872894.pdf http://hdl.handle.net/20.500.11937/19082 |