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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Main Authors: Syed Abbas Taher, Mojtaba Pakdel
Format: Article
Language:English
Published: Shahrood University of Technology 2014-06-01
Series:Journal of Artificial Intelligence and Data Mining
Subjects:
Online Access:http://jad.shahroodut.ac.ir/article_149_947c5e34f179d1577d7c2e162ec6f0e6.pdf
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spelling doaj-d48cc352c91649bbbaf74126717c0e9c2020-11-25T01:57:12ZengShahrood 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
collection DOAJ
language English
format Article
sources DOAJ
author Syed Abbas Taher
Mojtaba Pakdel
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
author_facet Syed Abbas Taher
Mojtaba Pakdel
author_sort Syed Abbas Taher
title 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_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_sort solution of multi-objective optimal reactive power dispatch using pareto optimality particle swarm optimization method
publisher Shahrood University of Technology
series Journal of Artificial Intelligence and Data Mining
issn 2322-5211
2322-4444
publishDate 2014-06-01
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.
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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