A Novel Hybrid GA-TLBO Algorithm for Minimization of Power Generation Cost

Economic Load Dispatch (ELD) represents a challenging and nonlinear problem encountered in the power system's generation domain. This research introduces a new hybrid algorithm that merges the advantages of both Genetic Algorithms (GA) and TLBO algorithm. The hybrid approach introduces dynamic teaching factors and step size-based learning mechanisms, effectively addressing traditional TLBO limitations and mitigating the risk of getting trapped in local minima. The TLBO component enriches exploration within the search space, allowing for a broader examination of potential solutions, while the GA component enhances exploitation by fine-tuning the search within promising regions. Comprehensive testing of the proposed algorithm is conducted using the IEEE 30-bus system, comparing its performance against that of conventional TLBO algorithms as well as contemporary optimization techniques. The outcomes of this research reveal that the proposed algorithm surpasses its counterparts in terms of reliability, robustness, and accuracy. This innovative approach holds promise for optimizing economic load dispatch in power systems, offering a more efficient and dependable solution.