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Application of improved particle swarm optimization in economic dispatch of power systems

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dc.contributor.advisor Wang, Z.
dc.contributor.author Gninkeu Tchapda, Ghislain Yanick
dc.date.accessioned 2018-06-27T09:20:25Z
dc.date.available 2018-06-27T09:20:25Z
dc.date.issued 2018-03
dc.date.submitted 2018-06
dc.identifier.citation Gninkeu Tchapda, Ghislain Yanick (2018) Application of improved particle swarm optimization in economic dispatch of power systems, University of South Africa, Pretoria, <http://hdl.handle.net/10500/24428>
dc.identifier.uri http://hdl.handle.net/10500/24428
dc.description.abstract Economic dispatch is an important optimization challenge in power systems. It helps to find the optimal output power of a number of generating units that satisfy the system load demand at the cheapest cost, considering equality and inequality constraints. Many nature inspired algorithms have been broadly applied to tackle it such as particle swarm optimization. In this dissertation, two improved particle swarm optimization techniques are proposed to solve economic dispatch problems. The first is a hybrid technique with Bat algorithm. Particle swarm optimization as the main optimizer integrates bat algorithm in order to boost its velocity and to adjust the improved solution. The second proposed approach is based on Cuckoo operations. Cuckoo search algorithm is a robust and powerful technique to solve optimization problems. The study investigates the effect of levy flight and random search operation in Cuckoo search in order to ameliorate the performance of the particle swarm optimization algorithm. The two improved particle swarm algorithms are firstly tested on a range of 10 standard benchmark functions and then applied to five different cases of economic dispatch problems comprising 6, 13, 15, 40 and 140 generating units. en
dc.format.extent 1 online resource (xiv, 80 leaves) : illustrations (chiefly color), graphs (chiefly color)
dc.language.iso en en
dc.subject Particle swarm optimization en
dc.subject Economic dispatch en
dc.subject Swarm intelligence en
dc.subject Genetic algorithm en
dc.subject Evolutionary algorithm en
dc.subject Bat algorithm en
dc.subject Cuckoo search algorithm en
dc.subject Power systems en
dc.subject Levy flight en
dc.subject Random search en
dc.subject Thermal power plant en
dc.subject.ddc 621.31
dc.subject.lcsh Swarm intelligence en
dc.subject.lcsh Genetic algorithms en
dc.subject.lcsh Electric power systems en
dc.title Application of improved particle swarm optimization in economic dispatch of power systems en
dc.type Dissertation en
dc.description.department Electrical and Mining Engineering en
dc.description.degree M. Tech. (Electrical Engineering)


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  • Unisa ETD [8805]
    Electronic versions of theses and dissertations submitted to Unisa since 2003

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