Techno-Economic Study by Teaching Learning-Based Optimization Algorithm for Optimal Placement of DG Units in Distribution Systems

A significant improvement in system performance can be achieved by placing Distributed Generator (DG) units of the optimal size in optimum network of radial distribution locations. In order to maximize the economic and technological benefits, it is necessary to reduce yearly economic losses. These losses include expenditures associated with installation and operation of the buses as well as power loss and voltage difference between buses. In view of these multi-objective frameworks, the current problem is assessed and the best compromise solution also referred as the Pareto-optimal solution is provided. In the framework of the multi-objective optimization problem, specific equality as well as inequality constraints is investigated. It is shown in this study that a Multi-Objective Teaching-Learning Based Optimization (MOTLBO) algorithm has been proposed to solve the multi-objective problem. For the purpose of evaluating its performance, the proposed method is being deployed on IEEE-33 and IEEE-69 System of radial bus distribution. A comparison with other recent multi-objective algorithms such as OCDE, KHA and LSFSA is also included in this study. It has been revealed that the algorithm proposed can offer superior outcomes concerning power loss, annual economic loss mitigation and voltage profile enhancement.