Abstract
{ "background": "Power-distribution infrastructure in developing nations requires robust, cost-effective planning methodologies. Existing approaches often lack integrated, long-term forecasting models tailored to specific regional constraints and equipment lifecycles.", "purpose and objectives": "This study conducts a comparative methodological evaluation of equipment systems and develops a bespoke time-series forecasting model to measure and project cost-effectiveness for national power-distribution infrastructure.", "methodology": "A comparative analysis of transformer and switchgear systems was performed using historical operational and cost data. A seasonal autoregressive integrated moving average (SARIMA) model, specified as $\\phi(B)\\Phi(B^s)\\nabla^d\\nabla^Ds yt = \\theta(B)\\Theta(B^s)\\epsilon_t$, was developed for forecasting. Model diagnostics included analysis of robust standard errors to account for heteroskedasticity.", "findings": "The forecasting model indicates a projected 22% reduction in total lifecycle costs per kilometre of network for the recommended equipment portfolio over a 25-year period. Comparative analysis identified specific switchgear technologies as having superior long-term cost-performance ratios under local operational conditions.", "conclusion": The integrated methodological framework provides a more reliable tool for long-term infrastructure investment planning than previous static models, demonstrating significant potential for cost optimisation.", "recommendations": "Infrastructure planners should adopt the developed forecasting model for capital investment appraisals. A phased transition towards the identified high-performance equipment portfolio is recommended to maximise future cost savings.", "key words": "infrastructure planning, lifecycle costing, SARIMA modelling, power distribution, cost-effectiveness, forecasting", "contribution statement": "This paper presents a novel integrated methodology combining comparative equipment evaluation with a bespoke time-series forecasting model, providing a new decision-support tool for engineering economists and infrastructure planners." } ``` Background Power-distribution infrastructure in developing nations requires robust, cost-effective planning methodologies. Existing approaches often lack integrated, long-term forecasting models tailored to specific regional constraints and equipment lifecycles. Purpose and objectives This study conducts a