{ "background": "Chronic underinvestment and reactive maintenance have precipitated a crisis in Nigeria's power-distribution infrastructure, leading to frequent equipment failure, high technical losses, and unreliable supply. Effective policy for asset management requires robust, forward-looking tools to quantify risk and prioritise interventions. ", "purpose and objectives": "This policy analysis develops and evaluates a novel time-series forecasting model to measure potential risk reduction in power-distribution equipment. It aims to provide a methodological framework for evidence-based asset management policy, enabling the proactive allocation of maintenance and replacement resources. ", "methodology": "A quantitative analysis was conducted using historical failure and maintenance data for transformers and switchgear. The core model is a seasonal autoregressive integrated moving average (SARIMA) with exogenous variables (SARIMAX), specified as \ (B) \ (Bˢ) \ᵈ\D yt = \ (B) \ (Bˢ) \ + \ Xt, where Xₜ includes climatic and load stress factors. Model parameters were estimated using maximum likelihood, with forecasts evaluated for statistical robustness. ", "findings": "The model forecasts a 22% reduction in the annual probability of catastrophic transformer failure under a proactive replacement policy informed by the risk projections, with a 95% confidence interval of 18%, 26%. The analysis identifies load growth during peak demand periods as the most significant exogenous driver of equipment stress, outweighing ambient temperature effects. ", "conclusion": "The proposed forecasting model provides a technically sound basis for transforming asset management from a reactive to a predictive regime. It demonstrates that quantified risk reduction is achievable through data-driven policy. ", "recommendations": "Policymakers and distribution companies should institutionalise the integration of time-series forecasting into asset management strategies. Regulators should consider permitting capital expenditure recovery linked to demonstrated, forecasted risk reduction, creating a financial incentive for proactive investment. ", "key words": "asset management, distribution infrastructure, forecasting, policy analysis, risk reduction, SARIMA, time-series",
Chinedu J. Okonkwo (Fri,) studied this question.