Quantify the Loss Reduction due Optimization of Capacitor Placement Using DPSO Algorithm Case Study on the Electrical Distribution Network of north Kerman Province
Farzaneh Ostovar1, Mahdi Mozaffari Legha2
1Farzaneh Ostovar,  Department of Power Engineering, Shadegan Branch, Islamic Azad University, Iran.
2Mahdi Mozaffari Legha,  Department of Power Engineering, Shadegan Branch, Islamic Azad University, Iran.
Manuscript received on September 26, 2013. | Revised Manuscript received on October 05, 2013. | Manuscript published on October 30, 2013. | PP: 148-152  | Volume-3, Issue-1, October 2013. | Retrieval Number:  E1773062513/2013©BEIESP

Open Access | Ethics and Policies | Cite
© 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: Increasing application of capacitor banks on distribution networks is the direct impact of development of technology and the energy disasters that the world is encountering. To obtain these goals the resources capacity and the installation place are of a crucial importance. Line loss reduction is one of the major benefits of capacitor, amongst many others, when incorporated in the power distribution system. The quantum of the line loss reduction should be exactly known to assess the effectiveness of the distributed generation. In this paper, a new method is proposed to find the optimal and simultaneous place and capacity of these resources to reduce losses, improve voltage profile too the total loss of a practical distribution system is calculated with and without capacitor placement and an index, quantifying the total line loss reduction is proposed. To demonstrate the validity of the proposed algorithm, computer simulations are carried out on actual power network of Kerman Province, Iran and the simulation results are presented and discussed.
Keywords: Distribution systems, Loss reduction index, Capacitor placement, Discrete Particle Swarm Optimization.