Minimizing the overall electricity production cost to the large-scale power system incorporating solar and wind energy sources using Elk Herd Optimizer

Abstract

This study presents a strategy for addressing the green economic load dispatch problem (GELD), which is a modern iteration of the economic load dispatch problem (ELD) that includes the integration of solar and wind generation sources. The primary objective of this study is to minimize the overall electricity production cost (OEPC) of a large-scale power system comprising 20 thermal power plants. To optimize the power output of each thermal power plant (TPP) in the system, along with the contributions from solar and wind sources, two optimization algorithms are employed: the Grelag Goose Optimization (GGO) and the Elk Herd Optimizer (EHO). The results demonstrate that EHO is superior to GGO across all comparison criteria. Specifically, EHO exhibits greater stability in 50 trial tests, with smaller fluctuations and a higher success rate in achieving optimal OEPC values. Additionally, EHO features faster convergence to the optimal value when compared to GGO. Furthermore, EHO achieves savings of $20.50 per hour on the minimum OEPC, $65.51 per hour on the mean OEPC, and $125.48 per hour on the maximum OEPC. These findings indicate that EHO is a robust and reliable search algorithm, and it is strongly recommended for addressing GELD problems. Lastly, the study quantitatively indicates the contribution of solar and wind generation sources to the reduction of the electricity production cost (EPC) for each thermal power plant.