Economic Load Dispatch using IYSGA

Author:

Brar Mandhir SinghORCID,Brar Gursewak SinghORCID

Abstract

The Economic Load Dispatch (ELD) problem is a pivotal aspect of power system management, focusing on the efficient allocation of power generation among various units to meet the demand while minimizing costs. This research paper presents an Improved Yellow Saddle Goat Fish Algorithm (IYSGA) based method for resolving ELD issues. The key objective of proposed IYSGA method is to reduce error between demanded and generated load along with its unit cost. This objective is accomplished by using YSGA whose exploration ability is improved by exploring ability of Grasshopper Optimization Algorithm (GOA). By implementing IYSGA in given ELD problem, the convergence rate, exploring ability and solution quality is enhanced. The fitness function is determined by IYSGA in terms of error and cost reduction, which should be as minimum as possible. The simulations are performed on standardized IEEE bus system with 3-unit and 6-units to meet load demand of 850MW to 1263MW respectively. The experimental simulations conducted provide evidence that the proposed approach met the load demand with zero error. Furthermore, proposed method attained best cost of $8197.633 and $15,285.7055 for the 3-unit and 6-unit generation unit. These outcomes underscore the robustness and superiority of the proposed method in addressing the Economic Load Dispatch (ELD) problem, emphasizing its capacity to optimize power generation with unparalleled precision and cost-effectiveness. 

Publisher

AMO Publisher

Reference20 articles.

1. Sahni, A., & Chaturvedi, C.T. (2021). Review of Power System Economic Load Dispatch Problem Optimization Techniques. International Journal of Innovative Research in Technology, 8(1), 786-790.

2. Al-Betar, M. A., Awadallah, M. A., Makhadmeh, S. N., Doush, I. A., Zitar, R. A., Alshathri, S., & Abd Elaziz, M. (2023). A hybrid Harris Hawks optimizer for economic load dispatch problems. Alexandria Engineering Journal, 64, 365-389. https://dx.doi.org/10.1016/j.aej.2022.09.010

3. Bhand, M. A., Halepoto, I. A., Abro, M. A. J., Rajput, P. S., & Shoro, G. M. (2021). Optimizing economic load dispatch problem using genetic algorithm: A case study of thermal power station Jamshoro. International Journal of Grid and Distributed Computing, 14(2), 15-24.

4. Deb, S., Abdelminaam, D. S., Said, M., & Houssein, E. H. (2021). Recent methodology-based gradient-based optimizer for economic load dispatch problem. IEEE Access, 9, 322-338. http://dx.doi.org/10.1109/ACCESS.2021.3066329

5. Fu, C., Zhang, S., & Chao, K.-H. (2020). Energy Management of a Power System for Economic Load Dispatch Using the Artificial Intelligent Algorithm. Electronics, 9, 108. https://doi.org/10.3390/electronics9010108

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3