Long term reliability of supply prognoses for decision support in asset management

This work demonstrates how a method for long-term reliability of supply prognoses can be applied for decision support in asset management. The prognoses account for component degradation and expected developments in grid reinforcements and load demand over a time horizon of multiple years. We present a case study on reinvestment scheduling for an ageing transformer, quantifying how postponing its replacement affects the expected net present value of investment and interruption costs. The results suggest that using reliability of supply prognoses in decision support for asset management of power systems can give significant socio-economic cost reductions. Furthermore, we observe that including information about grid and load development scenarios is necessary to form a good decision basis.

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Published
2025-06-29
DOI
https://doi.org/10.1109/powertech59965.2025.11180678
Primary Topic
Reliability and Maintenance Optimization
Type
article
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article

Long term reliability of supply prognoses for decision support in asset management

Iver Bakken Sperstad, Ivar Bjerkebæk, Gerd Kjølle
Reliability and Maintenance Optimization
article

Long term reliability of supply prognoses for decision support in asset management

Iver Bakken Sperstad, Ivar Bjerkebæk, Gerd Kjølle
article en

Abstract

This work demonstrates how a method for long-term reliability of supply prognoses can be applied for decision support in asset management. The prognoses account for component degradation and expected developments in grid reinforcements and load demand over a time horizon of multiple years. We present a case study on reinvestment scheduling for an ageing transformer, quantifying how postponing its replacement affects the expected net present value of investment and interruption costs. The results suggest that using reliability of supply prognoses in decision support for asset management of power systems can give significant socio-economic cost reductions. Furthermore, we observe that including information about grid and load development scenarios is necessary to form a good decision basis.

SINTEF (NO)
Openalex Percentile: Top 66%
Reliability and Maintenance Optimization
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