Hybrid multi-swarm particle swarm optimisation based multi-objective reactive power dispatch
Most of the real-world optimisation problems are subject to different types of constraints and are known as constrained optimisation problems. Reactive power dispatch (RPD) in electrical power system is also a non-linear, multi-objective or a single objective constrained optimisation problem. In thi...
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| Veröffentlicht in: | IET generation, transmission & distribution Jg. 9; H. 8; S. 727 - 739 |
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21.05.2015
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| Abstract | Most of the real-world optimisation problems are subject to different types of constraints and are known as constrained optimisation problems. Reactive power dispatch (RPD) in electrical power system is also a non-linear, multi-objective or a single objective constrained optimisation problem. In this study, hybrid multi-swarm particle swarm optimisation (HMPSO) algorithm has been proposed to solve the RPD problem. HMPSO is one of the recently proposed population based search algorithm, in which the existing swarm is partitioned into several sub-swarms. Particle swarm optimisation is applied as the search engine for each sub-swarm. In addition, to explore more promising regions of the search space, differential evolution (DE) algorithm is implemented to improve the personal best of each particle. The RPD problem is formulated as non-linear, constrained multi-objective optimisation problem with equality and inequality constraints for minimisation of power losses and improvement of voltage profile simultaneously. To find the Pareto optimal set for RPD problem, weighted sum method has been applied. Afterwards, for finding the preferred solution out of the Pareto-optimal set, fuzzy membership function has been used. Effectiveness of the HMPSO algorithm has been verified on the standard IEEE 30-bus and a practical 75-bus Indian systems. |
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| AbstractList | Most of the real-world optimisation problems are subject to different types of constraints and are known as constrained optimisation problems. Reactive power dispatch (RPD) in electrical power system is also a non-linear, multi-objective or a single objective constrained optimisation problem. In this study, hybrid multi-swarm particle swarm optimisation (HMPSO) algorithm has been proposed to solve the RPD problem. HMPSO is one of the recently proposed population based search algorithm, in which the existing swarm is partitioned into several sub-swarms. Particle swarm optimisation is applied as the search engine for each sub-swarm. In addition, to explore more promising regions of the search space, differential evolution (DE) algorithm is implemented to improve the personal best of each particle. The RPD problem is formulated as non-linear, constrained multi-objective optimisation problem with equality and inequality constraints for minimisation of power losses and improvement of voltage profile simultaneously. To find the Pareto optimal set for RPD problem, weighted sum method has been applied. Afterwards, for finding the preferred solution out of the Pareto-optimal set, fuzzy membership function has been used. Effectiveness of the HMPSO algorithm has been verified on the standard IEEE 30-bus and a practical 75-bus Indian systems. |
| Author | Singh, Himmat Srivastava, Laxmi |
| Author_xml | – sequence: 1 givenname: Laxmi surname: Srivastava fullname: Srivastava, Laxmi email: laxmigwl@gmail.com organization: Department of Electrical Engineering, Madhav Institute of Technology and Science, Gwalior, M.P., India – sequence: 2 givenname: Himmat surname: Singh fullname: Singh, Himmat organization: Department of Electrical Engineering, Madhav Institute of Technology and Science, Gwalior, M.P., India |
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| Keywords | Pareto optimisation multiobjective optimisation problem particle swarm optimisation search engine power losses minimisation fuzzy set theory hybrid multiswarm particle swarm optimisation RPD fuzzy membership function load dispatching evolutionary computation population based search algorithm differential evolution algorithm multiobjective reactive power dispatch constrained optimisation problems Pareto optimal set search problems HMPSO algorithm |
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| Snippet | Most of the real-world optimisation problems are subject to different types of constraints and are known as constrained optimisation problems. Reactive power... Most of the real‐world optimisation problems are subject to different types of constraints and are known as constrained optimisation problems. Reactive power... |
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| SubjectTerms | Algorithms constrained optimisation problems Constraints differential evolution algorithm evolutionary computation Fuzzy fuzzy membership function fuzzy set theory HMPSO algorithm hybrid multiswarm particle swarm optimisation load dispatching multiobjective optimisation problem multiobjective reactive power dispatch Nonlinearity Optimization Pareto optimal set Pareto optimisation particle swarm optimisation population based search algorithm power losses minimisation Reactive power RPD search engine Search engines search problems Searching |
| Title | Hybrid multi-swarm particle swarm optimisation based multi-objective reactive power dispatch |
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