Solving the economic load dispatch integrating clean energies in power system using Black Kite Algorithm

This research applies a novel meta-heuristic algorithm called the Black Kite Algorithm (BKA) to solve the economic load dispatch integrating the clean energies (CE-ELD) with the main objective of minimizing the overall fuel cost (OFC) of all thermal power generating sources (TPGSs). A 20-TPGS power system is used to conduct the whole research and assess the actual performance of the BKA. While solving the considered problem, wind and solar generating sources are both integrated into the power system. Besides, power loss caused by the transmission process and different levels of load demand ranging from 2500, 2600, to 2700 MW are employed. The results achieved by BKA in three cases of load demand are compared with another meta-heuristic algorithm, the Coati optimization algorithm. The comparison between the results of the two methods indicates that BKA is completely superior to COZ in all criteria, especially in reaching the best values of OFC and stability throughout the test runs, regardless of the noticeable increase in load demand. Mainly, BKA always requires fewer iterations to reach the best OFC value, resulting in a lower fluctuation of OFC values among the test runs. Based on these results and evaluations, BKA is acknowledged to be the robust and stable search method, and we highly recommend using BKA to solve optimizations such as the CE-ELD problem.