Integrated Optimization Algorithm in Solving Economic Dispatch Problems

• Published in: 5th IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2023
• Main Author: Ismail N.L.; Musirin I.; Dahlan N.Y.; Mansor M.H.; Sentilkumar A.V.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178556739&doi=10.1109%2fIICAIET59451.2023.10291341&partnerID=40&md5=75b967b0939046acede13e635cffd0b0
• DOI: 10.1109/IICAIET59451.2023.10291341

The utilization of conservative fossil fuels in power generation has played a significant role in driving economic growth, but it has also resulted in adverse consequences towards environmental impacts. This study proposed Multi-objective Hybrid Evolutionary Programming-Barnacles Mating Optimization as a solution to address the Combined Economic Environmental Dispatch problem by weighted-sum method implementation. The bi-objective function are the minimizing of the total generation cost and total emission have been optimized simultaneously. The performance of the algorithm is evaluated on Reliability Test System IEEE 57-Bus consisting of 7 generating units that consider ramp rate limits generator constraint. The proposed algorithm has been compared with the existing techniques, Multi-objective Barnacles Mating Optimizer and Multi-objective Evolutionary Programming. The results reveal that MOHEBMO generates superior and consistent solutions. © 2023 IEEE.