Solution of Multi-Objective optimal reactive power dispatch using pareto optimality particle swarm optimization method
For multi-objective optimal reactive power dispatch (MORPD), a new approach is proposed where simultaneous minimization of the active power transmission loss, the bus voltage deviation and the voltage stability index of a power system are achieved. Optimal settings of continuous and discrete control...
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| Format: | Article |
| Language: | English |
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Shahrood University of Technology
2014-06-01
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| Series: | Journal of Artificial Intelligence and Data Mining |
| Subjects: | |
| Online Access: | http://jad.shahroodut.ac.ir/article_149_947c5e34f179d1577d7c2e162ec6f0e6.pdf |
| _version_ | 1818430825070329856 |
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| author | Syed Abbas Taher Mojtaba Pakdel |
| author_facet | Syed Abbas Taher Mojtaba Pakdel |
| author_sort | Syed Abbas Taher |
| collection | DOAJ |
| description | For multi-objective optimal reactive power dispatch (MORPD), a new approach is proposed where simultaneous minimization of the active power transmission loss, the bus voltage deviation and the voltage stability index of a power system are achieved. Optimal settings of continuous and discrete control variables (e.g. generator voltages, tap positions of tap changing transformers and the number of shunt reactive compensation devices to be switched)are determined. MORPD is solved using particle swarm optimization (PSO). Also, Pareto Optimality PSO (POPSO) is proposed to improve the performance of the multi-objective optimization task defined with competing and non-commensurable objectives. The decision maker requires managing a representative Pareto-optimal set which is being provided by imposition of a hierarchical clustering algorithm. The proposed approach was tested using IEEE 30-bus and IEEE 118-bus test systems. When simulation results are compared with several commonly used algorithms, they indicate better performance and good potential for their efficient applications in solving MORPD problems. |
| first_indexed | 2024-12-14T15:39:34Z |
| format | Article |
| id | doaj.art-d48cc352c91649bbbaf74126717c0e9c |
| institution | Directory Open Access Journal |
| issn | 2322-5211 2322-4444 |
| language | English |
| last_indexed | 2024-12-14T15:39:34Z |
| publishDate | 2014-06-01 |
| publisher | Shahrood University of Technology |
| record_format | Article |
| series | Journal of Artificial Intelligence and Data Mining |
| spelling | doaj.art-d48cc352c91649bbbaf74126717c0e9c2022-12-21T22:55:39ZengShahrood University of TechnologyJournal of Artificial Intelligence and Data Mining2322-52112322-44442014-06-0121395210.22044/jadm.2014.149149Solution of Multi-Objective optimal reactive power dispatch using pareto optimality particle swarm optimization methodSyed Abbas Taher0Mojtaba Pakdel1Department of Electrical Engineering, University of Kashan, Kashan, IranDepartment of Electrical Engineering, University of Kashan, Kashan, IranFor multi-objective optimal reactive power dispatch (MORPD), a new approach is proposed where simultaneous minimization of the active power transmission loss, the bus voltage deviation and the voltage stability index of a power system are achieved. Optimal settings of continuous and discrete control variables (e.g. generator voltages, tap positions of tap changing transformers and the number of shunt reactive compensation devices to be switched)are determined. MORPD is solved using particle swarm optimization (PSO). Also, Pareto Optimality PSO (POPSO) is proposed to improve the performance of the multi-objective optimization task defined with competing and non-commensurable objectives. The decision maker requires managing a representative Pareto-optimal set which is being provided by imposition of a hierarchical clustering algorithm. The proposed approach was tested using IEEE 30-bus and IEEE 118-bus test systems. When simulation results are compared with several commonly used algorithms, they indicate better performance and good potential for their efficient applications in solving MORPD problems.http://jad.shahroodut.ac.ir/article_149_947c5e34f179d1577d7c2e162ec6f0e6.pdfMulti-objective 0ptimal reactive power dispatchPareto optimalityParticle Swarm Optimization |
| spellingShingle | Syed Abbas Taher Mojtaba Pakdel Solution of Multi-Objective optimal reactive power dispatch using pareto optimality particle swarm optimization method Journal of Artificial Intelligence and Data Mining Multi-objective 0ptimal reactive power dispatch Pareto optimality Particle Swarm Optimization |
| title | Solution of Multi-Objective optimal reactive power dispatch using pareto optimality particle swarm optimization method |
| title_full | Solution of Multi-Objective optimal reactive power dispatch using pareto optimality particle swarm optimization method |
| title_fullStr | Solution of Multi-Objective optimal reactive power dispatch using pareto optimality particle swarm optimization method |
| title_full_unstemmed | Solution of Multi-Objective optimal reactive power dispatch using pareto optimality particle swarm optimization method |
| title_short | Solution of Multi-Objective optimal reactive power dispatch using pareto optimality particle swarm optimization method |
| title_sort | solution of multi objective optimal reactive power dispatch using pareto optimality particle swarm optimization method |
| topic | Multi-objective 0ptimal reactive power dispatch Pareto optimality Particle Swarm Optimization |
| url | http://jad.shahroodut.ac.ir/article_149_947c5e34f179d1577d7c2e162ec6f0e6.pdf |
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