Online reliability calculations of power systems with forecasted and real time weather influence

Tollefsen, Trond; Svendsen, A.B.; Pedersen, Ronnie; Skeie, P; Lunde, T; Mælan, J

doi:10.1201/b19094-225

Cited by 3 publications

(7 citation statements)

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“…This study extends the previously studied weather-dependent failure rate model, 12 by applying it in a probabilistic reliability assessment of the Icelandic power system. This model is compared with constant failure rate models, which are currently calculated as a metric of long-term component reliability and also used in online reliability assessment tools.…”

Section: Failure Rate Modellingmentioning

confidence: 72%

“…This paper compares two failure rate models, a constant failure rate model and an extension of the previously studied model. 12 The constant failure rate model is calculated using established methods. 2 Given the description of fault statistics above, the constant failure rate can be estimated as…”

Section: Failure Rate Modellingmentioning

confidence: 99%

“…The previously studied weather-dependent model 12 correlated faults to wind speed. The extension of this model includes the influence of icing on overhead line failures, given that icing constitutes a significant threat to the Icelandic transmission system.…”

Section: Failure Rate Modellingmentioning

confidence: 99%

“…The ‘Failure rate modelling’ section describes an extension of a previously studied model. 12 The failure rate model is extended to include the threat of icing, to validate and extend a prior case study. 13 The ‘Failure rate model comparison’ section applies the extended model to a region of the Icelandic transmission system, comparing it with a constant failure rate model.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Modelling weather dependence in online reliability assessment of power systems

Perkin

Svendsen

Tollefsen

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part O:

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Probabilistic reliability assessment of power systems is an ongoing field of research, particularly in the development of tools to model the probability of exogenous threats and their potential consequences. This paper describes the application of a weather-dependent failure rate model to a region of the Icelandic transmission system, using 10 years of weather data and overhead line fault records. The studied failure rate model is compared with a constant failure rate model, in terms of variability and how well the models perform in a blind test over a 2 year period in reflecting the occurrence of outages. The weather-dependent and constant failure rate models are used as input to a state-of-the-art risk assessment tool to determine the sensitivity of such software to weather-dependent threats. The results show the importance of weather-dependent contingency probabilities in risk estimation, and in quantitative assessment of maintenance activities. The results also demonstrate that inclusion of weather dependence in power system reliability assessments affects the overall distribution of risk as a positively skewed distribution, with high-risk periods occurring at low frequency.

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Section: Failure Rate Modellingmentioning

confidence: 72%

Section: Failure Rate Modellingmentioning

confidence: 99%

Section: Failure Rate Modellingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Modelling weather dependence in online reliability assessment of power systems

Perkin

Svendsen

Tollefsen

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…: current and historical: load, production, spinning reserve, sensor data (current, voltage, frequency) load flow, configuration of the power system, component data (type, characteristic, age), component health indexes, all previous outages and causes, weather type at the point of outage, dynamic data of the strength of the system form PMUs, protection schemes and other functionalities. In addition, also near real time probabilistic risk calculation are available as input (Tollefsen, 2015). This represents big calculated data sets that gives a new insight in the inherit property of the power system.…”

Section: What Data Is Neededmentioning

confidence: 99%

Digitalization of the power business: How to make this work?

Svendsen¹,

Tollefsen²,

Gjengedal³

et al. 2018

Safety and Reliability – Safe Societies in a Changing World

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As a result of the digitalization of the power business in Norway and Europa, a lot of new possibilities and challenges arise. In 2014 an expert committee one outlined a proposal for the future grid company structure in Norway (Reiten, 2014). In addition, new technologies are being implemented in the system. Wind power, solar power, un-regulated small hydro power production, battery storage domestic and industrial and electrification of transport. Transmission System Operators (TSOs) have a responsibility to supply industry and communities with reliable electric power. However, the operators have been virtually blind to slowly occurring changes in the load profile that reduce the expected regularity of the power supply. This paper will focus on the possibilities and challenges the power business are facing. The paper will describe what technologies is needed i.e Real time probabilistic risk calculations, artificial intelligence, machine learning and smart grid technology. The main question is: can the power business and the introduction of new system tools manage without probabilistic risk calculation for making use of the digitalization and the corresponding big data? socioeconomic efficiency in the energy sector Now, the Norwegian main grid is aging and in the process of being replaced and upgraded by construction of new 420 kV lines in combination with digitalization of the power system. (Statnett, 2017). 1.2 The change in the power system, smart grid, solar, wind, battery etc.

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Identification of critical states in power systems by limit state surface reconstruction

David

Sansavini

2018

International Journal of Electrical Power & Energy Systems

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Online reliability calculations of power systems with forecasted and real time weather influence

Cited by 3 publications

References 0 publications

Modelling weather dependence in online reliability assessment of power systems

Modelling weather dependence in online reliability assessment of power systems

Digitalization of the power business: How to make this work?

Identification of critical states in power systems by limit state surface reconstruction

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