A holistic simulation tool for long-term probabilistic power system reliability analysis

Solheim, Øystein Rognes; Warland, Leif; Trötscher, Thomas

doi:10.1109/pmaps.2018.8440385

Cited by 11 publications

(8 citation statements)

References 6 publications

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“…As with most reliability of supply analyses, OPAL does however not account for the technical condition of the individual power system components. We should nevertheless stress that the methodology proposed in this paper is general, and section V will discuss how it can be generalized to account for component condition in Monte Carlo-based methods for reliability of supply analysis [23], [29].…”

Section: B Power System Reliability Analysismentioning

confidence: 99%

Accounting for component condition and preventive retirement in power system reliability analyses

Toftaker¹,

Foros²,

Sperstad³

2022

Preprint

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Deteriorated power system components have a higher probability of failure than new components. Still, reliability of supply analyses traditionally model all components of the same type with the same probability of failure, and thus neglects the effect of deteriorated components. This paper presents a methodology to integrate a condition dependent component probability of failure model into a power system reliability analysis. The component state is described by a semi-Markov process, and the paper shows how this, under reasonable assumptions, can be approximated by a Markov process. The Markov assumption simplifies the analysis and allows the model to include preventive retirement and be calibrated to statistical data. A case study using statistical data for Norwegian power transformers shows that, in the Norwegian power system, the proportion of failures that are due to poor condition is small, partly due to the common strategy of preventive retirement. However, if the condition of the transformers were worse, the impact of poor condition can be considerable. The methodology further enables identification of the transformers that contribute most to the risk to reliability of supply. The paper thus highlights the importance of accounting for component condition in strategic decisions such as long-term renewal planning.<br>

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Section: B Power System Reliability Analysismentioning

confidence: 99%

Accounting for component condition and preventive retirement in power system reliability analyses

Toftaker¹,

Foros²,

Sperstad³

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…This results in hourly time-series of wind dependent failure probability for the lines. This approach has been applied to create similar time-series of failure probability due to other weather effects such as icing and lightning, which is further used together with a Monte Carlo-based tool to calculate system consequences in terms of interrupted power and interruption costs in [21].…”

Section: Failure Bunching and Protection System Failuresmentioning

confidence: 99%

Reliability of Supply and the Impact of Weather Exposure and Protection System Failures

Kiel

Kjølle

2020

Applied Sciences

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Extreme weather is known to cause failure bunching in electrical transmission systems. However, protection systems can also contribute to the worsening of the system state through various failure modes—spontaneous, missing or unwanted operation. The latter two types of failures only occur when an initial failure has happened, and thus are more likely to happen when the probability of failure of transmission lines is high, such as in an extreme weather scenario. This causes an exacerbation of failure bunching effects, increasing the risk of blackouts, or High Impact Low Probability (HILP) events. This paper describes a method to model transmission line failure rates, considering both protection system reliability and extreme weather exposure. A case study is presented using the IEEE 24 bus Reliability Test System (RTS) test system. The case study, using both an approximate method as well as a time-series approach to calculate reliability indices, demonstrates both a compact generalization of including protection system failures in reliability analysis, as well as the interaction between weather exposure and protection system failures and its impact on power system reliability indices. The results show that the inclusion of protection system failures can have a large impact on the estimated occurrence of higher order contingencies for adjacent lines, especially for lines with correlated weather exposure.

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“…This results in hourly time-series of wind dependent failure probability for the lines. The time-series of historical failure probability in [13] is further used together with a Monte Carlo-based tool to calculate system consequences in terms of interrupted power and interruption costs in [15].…”

Section: Failure Bunching and Protection Failuresmentioning

confidence: 99%

The impact of protection system failures and weather exposure on power system reliability

Kiel

Kjølle

2019

2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Syst

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Extreme weather is known to cause failure bunching in the electrical transmission system. However, protection systems can also contribute to the worsening of the system state through spontaneous, missing or unwanted operation of the protection system. The latter two types of failures only occur when an initial failure has happened, and thus is more likely to happen when the probability of failure of transmission lines is high, such as in an extreme weather scenario. This causes an exacerbation of failure bunching effects, increasing the risk of blackouts, or High Impact Low Probability (HILP) events. This paper describes a method to model transmission line failure rates, considering both protection system reliability and extreme weather exposure. A sample case study is presented using the 6 bus RBTS test-system. The case study, using both an approximate method as well as a time-series approach to calculate reliability indices, demonstrates both a compact generalization of including protection system failures in reliability analysis, as well as the interaction between weather exposure and protection system failures and its impact on power system reliability indices. The results show that the inclusion of protection system failures can have a large impact on the estimated occurrence of higher order contingencies for adjacent lines, especially in periods of high weather exposure.

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A holistic simulation tool for long-term probabilistic power system reliability analysis

Cited by 11 publications

References 6 publications

Accounting for component condition and preventive retirement in power system reliability analyses

Accounting for component condition and preventive retirement in power system reliability analyses

Reliability of Supply and the Impact of Weather Exposure and Protection System Failures

The impact of protection system failures and weather exposure on power system reliability

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