Optimize power generation of thermal generating sources in solving the green energies-based economic load dispatch using Electric Eel Foraging Optimization
Faculty of electrical &electronics engineering, Ly Tu Trong College, Ho Chi Minh city, Vietnam.
Research Article
World Journal of Advanced Engineering Technology and Sciences, 2024, 11(02), 368–378.
Article DOI: 10.30574/wjaets.2024.11.2.0107
Publication history:
Received on 20 February 2024; revised on 06 April 2024; accepted on 09 April 2024
Abstract:
This research focuses on solving the green energies-based economic load dispatch problem (ELD) with the consideration of both solar and wind power to minimize the total electricity production cost (TEPC) of all thermal generating sources (TGSs) existing in the given power system. Two power systems, including a 6-TGS and a 15-TGS power system, were selected to conduct the research. Besides, the prohibited operating zones (POZs) of the TGSs are also considered while solving the GE-ELD problem. Golf optimization algorithm (GOA) and Electric Eel Foraging Optimization (EEFO) are applied to find the optimal power generation of TGSs to minimize the TEPC value and satisfy all the related constraints featured by the considered problem, especially the POZ constraints. The results obtained by GOA and EEFO in the two power systems are evaluated and compared using different criteria. The comparison indicates that EEFO is superior to GOA at all criteria, especially in the minimum value of TEPC (Min. TEPC) and the standard deviation (Std). In particular, EEFO is better than GOA 0.052($/h) on Min.TEPC and 98.34% on Std while applied in the first power system. The better values of EEFO over GOA in the second power system are 199.474 ($/h) and 78.703%. By considering these results, EEFO is considered a powerful search method and highly suggested for use to solve such GE-ELD problems.
Keywords:
Economic load dispatch; Thermal generating sources; Prohibited operating zones; Solar and wind power; Production cost; Golf optimization algorithm
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