Maximizing Power Loss Reduction in Radial Distribution Systems by Using Modified Gray Wolf Optimization

International Journal of Engineering and Technology Innovation

View Publication Info
 
 
Field Value
 
Title Maximizing Power Loss Reduction in Radial Distribution Systems by Using Modified Gray Wolf Optimization
 
Creator Nataraj, Deepa
Loganathan, Rajaji
Veerasamy, Moorthy
Reddy, Venkata Durga Ramarao
 
Subject radial distribution system
network reconfiguration
power loss reduction
modified gray wolf optimization
distributed generation
 
Description This paper presents an optimal Distribution Network Reconfiguration (DNR) framework and solution procedure that employ a novel modified Gray Wolf Optimization (mGWO) algorithm to maximize the power loss reduction in a Distribution System (DS). Distributed Generation (DG) is integrated optimally in the DS to maximize the power loss reduction. DNR is an optimization problem that involves a nonlinear and multimodal function optimized under practical constraints. The mGWO algorithm is employed for ascertaining the optimal switching position when reconfiguring the DS to facilitate the maximum power loss reduction. The position of the gray wolf is updated exponentially from a high value to zero in the search vicinity, providing the perfect balance between intensification and diversification to ascertain the fittest function and exhibiting rapid and steady convergence. The proposed method appears to be a promising optimization tool for electrical utility companies, thereby modifying their operating DS strategy under steady-state conditions. It provides a solution for integrating more DG optimally in the existing distribution network. In this study, IEEE 33-bus and 69-bus DSs are analyzed for maximizing the power loss reduction through reconfiguration, and the integration of DG is exercised in the 33-bus test system alone. The simulation results are examined and compared with those of several recent methods. The numerical results reveal that mGWO outperforms other contestant algorithms.
 
Publisher Taiwan Association of Engineering and Technology Innovation
 
Date 2019-09-10
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier http://ojs.imeti.org/index.php/IJETI/article/view/2448
 
Source International Journal of Engineering and Technology Innovation; Vol 9 No 4 (2019); 327-343
2226-809X
2223-5329
 
Language eng
 
Relation http://ojs.imeti.org/index.php/IJETI/article/view/2448/874
http://ojs.imeti.org/index.php/IJETI/article/view/2448/902
 
Rights Copyright (c) 2019 International Journal of Engineering and Technology Innovation
https://creativecommons.org/licenses/by-nc/4.0
 

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us

Twitter

Copyright © 2015-2018 Simon Fraser University Library