Growth in electricity grids, environmental awareness, and power reliability requirements necessitate the development of solutions for single- and multi-objective Optimal Power Flow (OPF) problems, emphasizing the need for effective optimization algorithms. In literature, both classical optimization techniques and metaheuristic algorithm-based methods have been proposed to solve the OPF problem. Studies are typically conducted on the test systems. Additionally, the applicability of these methods to real systems is also of great importance. In this study, the Kepler Optimization Algorithm (KOA), was applied to solve the OPF problem not only on test systems but also, for the first time in the literature, on a real system operating in island mode to determine its optimal operating points. First, KOA's performance was evaluated for various objective functions on the IEEE 30, IEEE 57, and IEEE 118 bus test systems. Using the KOA, results were obtained for single- and multi-objective functions, including fuel cost, active power loss, emission, and voltage deviation, either individually or all together. The same objective functions were also solved using the Golf Optimization Algorithm (GOA) and Whale Optimization Algorithm (WOA) using the population and iteration parameters, and the results were compared with those obtained using KOA. KOA demonstrated superior performance compared to GOA and WOA in all objective functions across the three test systems. Additionally, the results were compared with other numerous methods proposed in the literature to assess KOA's performance. The findings indicated that KOA obtained better performance in most of the objective functions. Finally, the KOA was used on a real 22-bus system operating in island mode to evaluate its performance. For this real system, results of 6563.724 $/h fuel cost, 0.1283 MW active power loss, and 0.0498 p.u. voltage deviation were obtained, indicating that KOA could be effectively utilized in real systems.
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| http://dx.doi.org/10.1016/j.heliyon.2025.e41915 | DOI Listing |
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