1Department of Electrical Engineering and Technology, Government College University Faisalabad, 38000, Faisalabad, Pakistan
2Department of Electrical Engineering, University of Botswana, Gaborone UB0061, Botswana
3Department of Electrical and Electronic Engineering Technology, Faculty of Engineering and the Built Environment, University of Johannesburg 2092, South Africa
BibTex Citation Data :
@article{IJRED60224, author = {Muhammad Abid Ali and Abdul Rauf Bhatti and Muhammad Farhan and Akhtar Rasool and Ahmed Ali}, title = {AI-optimization operation of biomass-based distributed generator for efficient radial distribution system}, journal = {International Journal of Renewable Energy Development}, volume = {13}, number = {6}, year = {2024}, keywords = {Biomass-based distributed generator (BMDG); particle swarm optimization (PSO); optimal placement and sizing; IEEE-33; radial distribution system (RDS)}, abstract = {This research aims to optimize the size and location of biomass-based distributed generator (BMDG) units to enhance the voltage profile, reduce electrical losses, maximize cost savings, and decrease emissions from power distribution systems. Biomass-based distributed generator (BMDG) systems offer numerous advantages to enhance the efficiency of power distribution systems. However, achieving these benefits relies on determining the optimal size and position of the BMDGs. To achieve these objectives, the metaheuristic technique called particle swarm optimization (PSO) is employed to find the optimal placement and size of BMDGs. The proposed model was validated on MATLAB's IEEE-33 bus radial distribution system (RDS), confirming the aforementioned benefits. Comparative analysis between the PSO-based technique and other algorithms from previous research revealed better results with the proposed method. The results indicate that optimal placement and sizing of BMDG units have led to a reduction of more than 67.68% in active power losses and 65.90% in reactive power losses compared to the base case. Additionally, the reduction in active power loss was 40.44%, 11.39%, 42.85%, 1.81%, 0.85%, 29.83%, 5.82% and 28.38% more than artificial bee colony, backtracking search optimization algorithm, moth-flame optimization, Coordinate control, artificial Hummingbird algorithm, variable constants PSO (VCPSO), artificial gorilla troops optimizer (AGTO), and a jellyfish search optimizer respectively. Furthermore, the reactive power losses were reduced by 38.33% and 15.68% compared to VCPSO and AGTO respectively. Furthermore, this study revealed a cost reduction of 6.38% when compared to the AGTO and 1.30% when compared to the AHA. Moreover, the voltage profile of the power distribution system was improved by 7.28%. The presented methodology has demonstrated promising results for BMDGs in RDS across various applications.}, pages = {1044--1057} doi = {10.61435/ijred.2024.60224}, url = {https://ijred.cbiore.id/index.php/ijred/article/view/60224} }
Refworks Citation Data :
Article Metrics:
Last update:
Last update: 2024-12-11 15:26:20
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. Articles are freely available to both subscribers and the wider public with permitted reuse.
All articles published Open Access will be immediately and permanently free for everyone to read and download. We are continuously working with our author communities to select the best choice of license options: Creative Commons Attribution-ShareAlike (CC BY-SA). Authors and readers can copy and redistribute the material in any medium or format, as well as remix, transform, and build upon the material for any purpose, even commercially, but they must give appropriate credit (cite to the article or content), provide a link to the license, and indicate if changes were made. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
International Journal of Renewable Energy Development (ISSN:2252-4940) published by CBIORE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.