Using Conditional Unreliability to Justify Capital Expenditure Forecasts
This white paper presents a mathematically rigorous methodology for forecasting transmission asset replacement volumes across regulatory planning periods. The approach applies conditional unreliability analysis to convert Weibull distribution parameters into defensible, period-specific replacement projections suitable for regulatory capital expenditure submissions.
Traditional forecasting methods based on historical replacement rates or simple age-based rules fail to account for the non-linear nature of asset deterioration and the evolving age profile of in-service populations. Conditional unreliability
directly addresses these limitations by answering the essential question: ‘Given that this asset has survived to its current age, what is the probability it will require replacement within the next regulatory period?’
The methodology produces both aggregate replacement volumes for capital planning and individual structure probability assessments for tactical prioritization, providing a united analytical framework that serves multiple asset management functions.