Particle Swarm Optimization Algorithm Based Reactive Power Optimization in Distribution Network
Amar Nath Patel1, Shobhna Jain2
1Amar Nath Patel, Student of University Institute of Technology, Rajiv Gandhi Prodyogiki Vishwavidyalaya Bhopal Madhya Pradesh.
2Mrs. Shobhna Jain is Assistant Professor in Department of Electrical and Electronics Engineering of University Institute of Technology, Rajiv Gandhi Prodyogiki Vishwavidyalaya Bhopal.
Manuscript received on 04 August 2019 | Revised Manuscript received on 08 August 2019 | Manuscript published on 30 August 2019 | PP: 3792-3796 | Volume-8 Issue-10, August 2019 | Retrieval Number: J99800881019/2019©BEIESP | DOI: 10.35940/ijitee.J9980.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Minimization of power loss is the first priority of the power companies. Generally power loss is directly proportional to the reactive power demand and minimization of this is known as reactive power optimization (RPO). In this paper we are trying to minimize the reactive power loss with help of distributed generation. Distributed generation provides active as well as reactive power locally so, there is no need of taking the reactive power from the generator consequently reactive power loss minimizes. Now problem arises that where to place the distributed generation to have minimum power loss. To find the optimal location of the distributed generation, we have used particle swarm optimization algorithm (PSO). For that we have defined the fitness function as well as constraints. Constraints limits the value of variable within the defined range. Fitness function is sum of real power loss index, reactive power loss index and voltage deviation index. We have also used genetic algorithm just to compare the results and to find which one is better out of genetic algorithm and PSO. RPO increases the power transfer capability, reduces the line loss and boost the system stability therefore it can be applied in the distribution network.
Keywords: Distributed Generation, Genetic Algorithm, PSO, RPO.
Scope of the Article: Cross-Layer Optimization