IAES International Journal of Robotics and Automation (IJRA)
Vol 9, No 1: March 2020

Advanced teaching-learning-based optimization algorithm for actual power loss reduction

Kanagasabai, Lenin (Unknown)



Article Info

Publish Date
06 Mar 2019

Abstract

In this work Advanced Teaching-Learning-Based Optimization algorithm (ATLBO) is proposed to solve the optimal reactive power problem. Teaching-Learning-Based Optimization (TLBO) optimization algorithm has been framed on teaching learning methodology happening in classroom. Algorithm consists of “Teacher Phase”, “Learner Phase”. In the proposed Advanced Teaching-Learning-Based Optimization algorithm non-linear inertia weighted factor is introduced into the fundamental TLBO algorithm to manage the memory rate of learners. In order to control the learner’s mutation arbitrarily during the learning procedure a non-linear mutation factor has been applied. Proposed Advanced Teaching-Learning-Based Optimization algorithm (ATLBO) has been tested in standard IEEE 14, 30 bus test systems and simulation results show the proposed algorithm reduced the real power loss effectively.

Copyrights © 2020






Journal Info

Abbrev

IJRA

Publisher

Subject

Automotive Engineering Electrical & Electronics Engineering

Description

Robots are becoming part of people's everyday social lives and will increasingly become so. In future years, robots may become caretaker assistants for the elderly, or academic tutors for our children, or medical assistants, day care assistants, or psychological counselors. Robots may become our ...