Optimal Capacitor Placement on Primary Distrbution System for Loss Minimaization Using Artificial Intelligent Techniques:Case study on Adama Town Distrbution System

Abstract

A power system contains generation, transmission and distribution systems. Distribution system is the final part which delivers the power to the load and it usually has the highest loss and is very critical in power system reliability. The loss in a distribution system can be minimized by an appropriate placement of capacitor banks. But the problem is on how to optimally select the location and size of capacitor banks. This thesis presents artificial intelligent approaches for capacitor placement in radial distribution feeder to reduce the real power loss and to improve the voltage profile. Before installing the capacitor a load flow program using backward forward method is executed to analyze the present system. The location of the nodes where the capacitors should be placed is decided by a set of rules given by the fuzzy expert System. Then the sizing of the capacitors is modeled as an optimization problem and the objective function (loss minimization) is solved using particle swarm optimization technique. The performance of the proposed method is applied on 75 bus radial distribution feeder of Adama town. Backward forward sweep load flow analysis also carried after selecting optimal capacitor sizes. The simulation result shows that by applying these methods 10 optimal locations are selected and optimal size capacitors are installed that results improvement of voltage at all buses. In addition to this by placing shunt capacitors 0.4 MW of power is saved and power loss is decreased from 18.85% to 14% and due to this annually 700716.8 birr is saved.