Issue |
E3S Web Conf.
Volume 616, 2025
2nd International Conference on Renewable Energy, Green Computing and Sustainable Development (ICREGCSD 2025)
|
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Article Number | 02025 | |
Number of page(s) | 9 | |
Section | Green Computing | |
DOI | https://doi.org/10.1051/e3sconf/202561602025 | |
Published online | 24 February 2025 |
Optimizing Combined Heat and Power Economic Dispatch Using a Differential Evolution Algorithm
1 Assoicate Professor, Department of EEE, Geethanjali College of Engineering and Technology, Hyderabad, TS. India
2 Department of EEE, CMR College of Engineering & Technology, Hyderabad, TS, India
3 Professor, Department of EEE, CVR College of Engineering, Hyderabad, TS. India
4 Department of Electrical and Electronics Engineering, Anurag University, Hyderabad, T.S., India
5 Senior Lecturer in Electrical and Electronics Engineering, Government Polytechnic Nirmal
6 Department of EEE, Anurag University, Hyderabad, T.S., India
* Corresponding author: mahi9vkb@gmail.com
The electrical load dispatch (ELD) optimizes the scheduling of various power plants to deliver the necessary power at the lowest operational cost. Implementing combined heat and power (CHP) units in contemporary power systems enhances energy efficiency and generates less environmental pollution compared to conventional units by producing electricity and heat at the same time. As a result, the ELD issue, including CHP units, transforms into a non-linear and non-convex challenge called CHP economic dispatch (CHPED), which aims to meet electrical and thermal demands at the lowest operational cost. The CHPED issue is examined by applying the Differential evolution (DE) approach. The algorithm's efficacy on 24-unit, 48-unit, and 96-unit systems is detailed. The results acquired are compared with other algorithms to evaluate the effectiveness of the DE algorithm. The findings proved the efficacy of the DE algorithms compared to other evolutionary algorithms.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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