SELECTION OF OPTIMAL SIZE AND LOCATION OF DGs AND DSTATCOM USING TEACHING LEARNING BASED OPTIMIZATION IN RADIAL DISTRIBUTION SYSTEMS

Abstract

This thesis proposes an approach to determine the optimal location and sizing of Distributed Generation (DG) and Distribution STATCOM (DSTATCOM) simultaneously to improve the node voltage and power losses in radial distribution systems.The objective is to minimize active power losses while keeping the voltage profiles in the network within specified limits. Power- flow studies is carried out using forward/backward algorithm using BIBC and BCBV matrices. Teaching learning based optimization (TLBO) technique is used to find the optimal locations and sizes of DG and DSTATCOM. A 33-bus and a 69-bus radial distribution system are used to demonstrate the effectiveness of the method. The simulation results show that the reduction of power loss in distribution systems is possible if DG and DSTATCOM are optimally placed in the distribution system. The superiority of the approach has been shown by comparing the results with PSO and BFO (Bacterial Foraging Optimization) methods in the two systems.