What question did this study set out to answer?

The aim is to create a framework for evaluating power-distribution systems and forecasting efficiency improvements.

March 14, 2026Open Access

Methodological Evaluation and Time-Series Forecasting for Efficiency Gains in Senegal's Power-Distribution Infrastructure

Q: What does this research mean for the field?

Targeted upgrades to ageing circuit-breakers and transformers in Senegal's power-distribution infrastructure could reduce aggregate technical losses by an estimated 18.5% over a five-year forecast horizon. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Key Points

The aim is to create a framework for evaluating power-distribution systems and forecasting efficiency improvements.
Analyzed operational data from primary substations.
Developed an ARIMAX forecasting model for technical losses.
Verified model robustness using heteroskedasticity-consistent standard errors.
The ARIMAX(2,1,2) model showed strong predictive capability.
Targeted upgrades could reduce technical losses by 18.5% over five years.
Findings emphasize the importance of strategic interventions in aging equipment.

Abstract

"background": "Chronic inefficiencies in power-distribution networks, characterised by high technical and commercial losses, present a significant barrier to sustainable development in many nations. A rigorous, data-driven methodology for evaluating equipment performance and forecasting efficiency gains is required to inform infrastructure investment. ", "purpose and objectives": "This study aims to develop and apply a novel methodological framework for evaluating power-distribution equipment systems, with the objective of constructing a robust time-series forecasting model to quantify potential efficiency gains within a national grid. ", "methodology": "A comprehensive dataset of operational parameters from primary substations was analysed. The core forecasting model is an autoregressive integrated moving average with exogenous variables (ARIMAX), specified as \ yt = \ + =1^{p\ \ yt-i + =1^q\ -j + =1^r\ Xk, t + \, where Xk represents exogenous technical variables. Model robustness was verified using heteroskedasticity-consistent standard errors. ", "findings": "The ARIMAX (2, 1, 2) model demonstrated strong predictive capability, indicating that targeted upgrades to ageing circuit-breakers and transformers could reduce aggregate technical losses by an estimated 18. 5% (95% CI: 16. 2% to 20. 7%) over a five-year forecast horizon, conditional on sustained investment. ", "conclusion": "The methodological framework provides a statistically rigorous tool for infrastructure assessment, confirming that strategic, data-led interventions in specific equipment categories can yield substantial and quantifiable improvements in distribution efficiency. ", "recommendations": "Utility planners should adopt this forecasting methodology for long-term infrastructure planning. Initial investment should be prioritised for substations identified as having the highest marginal return on loss reduction. ", "key words": "power distribution, time-series forecasting, infrastructure efficiency, ARIMAX, technical losses, grid modernisation",

Methodological Evaluation and Time-Series Forecasting for Efficiency Gains in Senegal's Power-Distribution Infrastructure

Key Points

Abstract

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