Open AccessMinimization of real power loss by enhanced teaching learning based optimization algorithm
Author(s) -
K. Lenin
Publication year - 2020
Publication title -
international journal of robotics and automation (ijra)/iaes international journal of robotics and automation
Language(s) - English
Resource type - Journals
eISSN - 2722-2586
pISSN - 2089-4856
DOI - 10.11591/ijra.v9i1.pp1-5
Subject(s) - computer science , class (philosophy) , minification , optimization algorithm , gradation , process (computing) , power flow , algorithm , transfer of learning , power loss , power (physics) , iterative and incremental development , mathematical optimization , electric power system , artificial intelligence , mathematics , software engineering , physics , operating system , quantum mechanics , programming language
This paper presents an Enhanced Teaching-Learning-Based Optimization (ETLBO) algorithm for solving reactive power flow problem. Teaching-learning process is an iterative process where in the continuous interaction takes place for the transfer of knowledge. Movements of trial solutions will investigate the internally final stages. Up gradation of the algorithm has been done through by adding weight in the learner values. Projected ETLBO algorithm has been tested in standard IEEE 57,118 bus systems and power loss has been reduced efficiently.