Enhancing Nigerian Power Transmission Efficiency Through Hybrid Meta-Heuristic Optimization: A Review

Nigeria’s power transmission infrastructure is characterized by chronic inefficiencies, high technical losses, and weak system reliability. With increasing electricity demand and aging grid assets, traditional optimization and control strategies have proven inadequate for ensuring efficient power transmission. This paper reviews the evolution of mathematical modeling techniques integrated with hybrid meta-heuristic optimization algorithms for improving transmission efficiency in large-scale grid systems, with a particular focus on the Nigerian context. The study examines recent models that couple physics-based transmission formulations with intelligent optimization strategies such as Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Artificial Bee Colony (ABC). The review highlights the superiority of hybrid meta-heuristic models in addressing non-convex optimization challenges, grid congestion, and reactive power imbalances in Nigeria’s 330 kV and 132 kV transmission networks. The paper concludes with identified gaps in current research and provides a framework for integrating hybrid optimization into future Nigerian grid modernization projects.