Simulating the long term effect of asset management strategies on reliability of supply
This paper presents long-term power system reliability prognosis methods aimed for decision support in asset management and grid development. The prognosis method combines power system reliability assessment with simulation of the time development of components’ technical condition. The condition of...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | International Journal of Electrical Power & Energy Systems |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061525003990 |
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| Summary: | This paper presents long-term power system reliability prognosis methods aimed for decision support in asset management and grid development. The prognosis method combines power system reliability assessment with simulation of the time development of components’ technical condition. The condition of the component population is influenced by three different factors in the model: degradation due to aging, forced replacements due to non-repairable failures, and preventive replacements. We demonstrate the prognoses by simulating and comparing a set of reinvestment strategies. The reinvestment strategies we consider are age based, condition based and risk based, where risk is quantified in terms of expected energy not supplied (EENS). In demonstrating the methodology we focus on transformers and utilize an existing transformer end-of-life model. An important secondary objective of the work is to quantify the uncertainty in the end-of-life model, and include this uncertainty in the risk prognosis. We show that although there is substantial uncertainty in the end-of-life model, the relative performance of the reinvestment strategies is easily identified. The risk based strategy is seen to outperform the age-based and condition-based strategies giving considerably lower EENS and uncertainty over time. |
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| ISSN: | 0142-0615 |