Particle Swarm Optimization Based Optimal Reactive Power Dispatch for Power Distribution Network with Distributed Generation
International Journal of Energy and Power Engineering
Volume 6, Issue 4, August 2017, Pages: 53-60
Received: Jun. 21, 2017;
Accepted: Jul. 10, 2017;
Published: Aug. 11, 2017
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Khine Zin Oo, Power System Research Unit, Department of Electrical Power Engineering, Mandalay Technological University, Mandalay, Myanmar
Kyaw Myo Lin, Power System Research Unit, Department of Electrical Power Engineering, Mandalay Technological University, Mandalay, Myanmar
Tin Nilar Aung, Power System Research Unit, Department of Electrical Power Engineering, Mandalay Technological University, Mandalay, Myanmar
Reactive power dispatch plays a main role in order to provide good facility secure and economic operation in the power system. Optimal reactive power dispatch (ORPD) is a nonlinear optimization problem and has both equality and inequality constraints. ORPD is defined as the minimization of active power loss by controlling a number of variables. Due to complex characteristics of ORPD, heuristic optimization has become an efficient solver. In this paper, particle swarm optimization (PSO) algorithm and MATPOWER toolbox are applied to solve the ORPD problem for distribution system with distributed generating (DG) plant. The proposed method minimizes the active power loss in a practical power system as well as determines the optimal placement of a new installed DG. The practical 41-bus, 6-machine power distribution network of Myingyan area is used to evaluate the performance. The result shows that the adjustment of control variables of distribution power network with a new DG gives a better approach than adjustment only the control variables without DG.
Khine Zin Oo,
Kyaw Myo Lin,
Tin Nilar Aung,
Particle Swarm Optimization Based Optimal Reactive Power Dispatch for Power Distribution Network with Distributed Generation, International Journal of Energy and Power Engineering.
Vol. 6, No. 4,
2017, pp. 53-60.
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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