Towards load frequency management in thermal power systems using an improved open-source development model algorithm - Khezri, Edris; Rezaeipanah, Amin; Hassanzadeh, Hiwa; Majidpour, Jafar (Evolutionary intelligence, 2025)
Maintaining a balance between generated and consumed power is crucial for the efficient operation of interconnected power grids. This paper focuses on the issue of load frequency management in thermal power systems. We present a metaheuristic approach to address this problem, leveraging the advantages of metaheuristic algorithms in solving complex optimization problems. Our approach is based on an improved Open-source Development model algorithm (ODMA). The proposed method, referred to as ODMA-GA, integrates ODMA with a Genetic algorithm (GA) to configure a hybrid optimization technique. This combination allows for the effective exploitation and exploration of the search space, leading to high-quality solutions. We evaluate the performance of ODMA-GA using several benchmark functions with varying scenarios. The results demonstrate that ODMA-GA outperforms its peer metaheuristic algorithms, showcasing superior optimization capabilities. This promising performance suggests that ODMA-GA offers an effective solution for the challenging task of load frequency management in thermal power systems, ensuring stable and efficient operation. Specifically, the finding shows that our method improves the frequency change area and tie-line power change by 2.3% compared to the best existing method.