Methodological Evaluation and Time-Series Forecasting for Power-Distribution Risk Reduction in Ghana, 2000–2026

"background": "Power-distribution systems in Ghana have historically faced reliability challenges, necessitating advanced methodologies for risk assessment and forecasting to inform infrastructure investment and maintenance strategies. ", "purpose and objectives": "This report aims to methodologically evaluate existing equipment systems and develop a robust time-series forecasting model to quantify projected risk reduction within the national distribution network. ", "methodology": "A methodological evaluation of system components was conducted. A seasonal autoregressive integrated moving average (SARIMA) model, specified as (1, 1, 1) (1, 1, 1) ₁₂, was fitted to historical fault-interval data. Forecast uncertainty was quantified using 95% prediction intervals. ", "findings": "The methodological review identified transformer ageing as a critical risk factor. The forecasting model indicates a potential 22% reduction in fault frequency over the forecast horizon, with prediction intervals suggesting the estimate is robust to seasonal volatility. ", "conclusion": "The integrated methodological and modelling approach provides a quantifiable framework for anticipating performance improvements in distribution infrastructure, supporting strategic asset management. ", "recommendations": "Implement the forecasting model within utility planning cycles and prioritise investment in condition monitoring for ageing transformer assets identified by the methodological evaluation. ", "key words": "Asset management, distribution networks, forecasting, power systems, risk reduction, time-series analysis", "contribution statement": "This work provides a novel integrated framework combining methodological equipment evaluation with a statistically rigorous forecasting model to quantify future risk reduction, a approach not previously applied in this context. " ``` Background Power-distribution systems in Ghana have historically faced reliability challenges, necessitating advanced methodologies for risk assessment and forecasting to inform infrastructure investment and maintenance strategies. Purpose and objectives This report aims to methodologically evaluate existing equipment systems and develop a robust time-series forecasting model to quantify projected risk reduction within the national distribution network. Methodology A methodological evaluation of system components was conducted. A seasonal autoregressive integrated moving average (SARIMA) model, specified as SARIMA (1,