Modelling Optimal Renewable Energy Mix for Nigeria’s Grid Using Linear Programming

Nigeria's electricity sector faces a structural challenge of meeting rapidly growing demand while simultaneously decarbonising generation, requiring evidence-based optimisation of the renewable energy technology mix within the constraints of available resources, infrastructure, and investment capacity. This study develops a linear programming model to determine the optimal renewable energy mix for Nigeria's national electricity grid, minimising total system cost subject to reliability, resource availability, environmental, and policy constraints. Input data on technology costs, capacity factors, resource availability by geopolitical zone, grid transmission constraints, and demand projections were assembled from the Transmission Company of Nigeria, International Renewable Energy Agency databases, and the Federal Ministry of Power. The model is formulated for a planning horizon of 2025 to 2035 with annual time steps and seasonal demand disaggregation. Scenarios incorporating different carbon price assumptions, technology cost trajectories, and demand growth rates are evaluated to test solution robustness. Results indicate that an optimal mix comprising 38 percent solar photovoltaic, 22 percent wind, 21 percent hydropower, and 19 percent gas with carbon capture achieves the lowest long-run system cost while meeting the Federal Government's 2030 renewable energy targets. Sensitivity analysis confirms solar photovoltaic as the most cost-robust technology across all scenarios. The study contributes a replicable optimisation framework applicable to state-level renewable energy planning and recommends its adoption by the Nigerian Electricity System Operator for integrated resource planning. Keywords: optimal energy mix, linear programming, Nigeria grid, renewable energy modelling, integrated resource planning.