Stochastic Generation Adequacy Assessment for the Nigerian Electricity Supply Industry Under Fuel Supply Uncertainty

This study develops a stochastic generation adequacy assessment model for the Nigerian electricity supply industry that explicitly accounts for the fuel supply uncertainty characterising the Nigerian gas-to-power sector, filling a significant gap in the probabilistic planning tools available to NESI system planners. Nigeria's generation fleet is predominantly gas-fired, but chronic gas supply shortfalls caused by pipeline sabotage, gas pricing disputes, and infrastructure limitations constrain the available generation capacity to well below installed nameplate ratings, making deterministic capacity planning exercises misleading. The assessment model is implemented in MATLAB as a sequential Monte Carlo simulation that stochastically models generator forced outage rates, gas supply interruption frequencies and durations derived from NERC operational reports, hydrology-driven derating of hydropower plants, and demand variability. The model computes loss of load probability, loss of load expectation, and expected energy not served metrics annually across a 10-year planning horizon under current and projected generation portfolio scenarios including committed pipeline projects and proposed renewable additions. Three demand growth scenarios are evaluated: base, high, and low. Simulation results based on 10,000 Monte Carlo iterations show that under the base demand scenario, the current generation portfolio achieves a LOLP of 23 percent, dramatically worse than the international standard of 5 percent, driven primarily by gas curtailment events. Adding the committed solar and hydro projects reduces LOLP to 14 percent. Only with additional gas infrastructure investment or significant storage deployment does LOLP approach the 5 percent planning standard. Keywords: generation adequacy, Monte Carlo simulation, fuel supply uncertainty, LOLP, Nigeria.