A novel hyper heuristic search algorithm: An application to optimal power flow problem

Classical Optimal Power Flow (OPF) is a complex and challenging problem in power systems, characterized by its non-convex, nonlinear, and large-scale nature. The integration of uncertain and intermittent wind energy sources further increases the complexity of the OPF problem. In power systems, Flexible AC Transmission System (FACTS) devices can address many issues related to power quality and network overloads. However, determining the optimal placement and sizing of FACTS devices presents an additional challenge in minimizing the total power generation cost.To effectively solve the OPF problem under these conditions, an artificial intelligence-based optimization algorithm must exhibit strong exploration capabilities along with a balanced trade-off between exploitation and exploration. The Weighted Mean of Vectors (INFO) is a newly introduced heuristic optimization algorithm that has shown promise in solving engineering design optimization problems more effectively.In this study, the INFO algorithm was first enhanced by incorporating the Fitness–Distance Balance (FDB) method to leverage its strengths. Subsequently, a hyper-heuristic approach was employed to generate an optimal initial population using the Differential Evolution (DE) algorithm. Finally, the improved algorithm was applied to solve the optimal placement and sizing of FACTS devices in the OPF problem, considering the integration of wind energy sources. The results demonstrated that the proposed algorithm provides more effective solutions for the considered problem cases compared to those reported in the existing literature.