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Sina Khajeh Ahmad Attari
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A Novel Method Based on Teaching-Learning-Based Optimization for Recloser Placement with Load Model Consideration in Distribution System Sina Khajeh Ahmad Attari; Mohammad Bakhshipour; Mahmoudreza Shakarami; Farhad Namdari
Indonesian Journal of Electrical Engineering and Computer Science Vol 2, No 1: April 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v2.i1.pp1-10

Abstract

This paper proposed a novel technique based on teaching-learning-based optimization (TLBO) algorithm in order to find optimal placement of reclosers in the distribution networks which is applied to improve reliability. Reclosers use to eliminate transient faults, faults isolation, network management and enhance reliability to reduce customer outages. According to recloser role in network reliability, the cost for the installation and maintenance must be sustained by distribution companies. Therefore, selecting sufficient number and suitable location for reclosers are important issue. In this paper, the proposed objective function for optimal recloser number and placement has been formulated to improve three reliability indices which consists of three terms; i.e. System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI) and Average Energy Not Supplied (AENS). Besides the load model effectiveness has been considered to the simulation. To verify the efficiency of proposed method, it has been conducted to IEEE 69-bus radial distribution system. The obtained simulation results demonstrate the reliability improvement.
Co-Authors Farhad Namdari Mahmoudreza Shakarami Mohammad Bakhshipour