A Novel Method Based on Teaching-Learning-Based Optimization for Recloser Placement with Load Model Consideration in Distribution System

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.