Investigating the use of probability distribution functions in reliability-worth analysis of electric power systems

Dzobo, Oliver; Gaunt, C.T.; Herman, R.

doi:10.1016/j.ijepes.2011.12.013

Cited by 40 publications

(18 citation statements)

References 15 publications

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“…Monte-Carlo simulation is an important tool in investigating the reliability of power grids, since it can account for stochastic aspects of the system (e.g., [10]). However, standard Monte-Carlo simulation may be computationally intractable when the events of interest are extremely rare.…”

Section: Introductionmentioning

confidence: 99%

Efficient simulation of blackout probabilities using splitting

Shortle

2013

International Journal of Electrical Power & Energy Systems

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Section: Introductionmentioning

confidence: 99%

Efficient simulation of blackout probabilities using splitting

Shortle

2013

International Journal of Electrical Power & Energy Systems

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“…The aggregate cost is combined with the probability of failure at each busbar, allowing the total value at risk to be identified for the system configuration. The total cost is also a Beta probability distribution, from which singular values can be extracted for a given level of confidence or risk (Dzobo et al 2012). …”

Section: Network Reliability and Cost Assessmentmentioning

confidence: 99%

Reducing uncertainty – responses for electricity utilities to severe solar storms

Gaunt

2014

J. Space Weather Space Clim.

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Until recently, electricity utilities in mid-and low-latitude regions believed that solar storms had no (or only insignificant) effect on their power systems. Then it was noticed that the onset of damage in several large transformers, leading to their failure, correlated very closely with the Halloween storm of 2003. Since then engineers have started to appreciate that a very severe storm could have serious consequences outside the high-latitude regions. There are many uncertainties in predicting the effects of solar storms on electrical systems. The severity and time of arrival of a storm are difficult to model; so are the geomagnetically induced currents (GICs) expected to flow in the power networks. Published information about the responses of different types of transformers to GICs is contradictory. Measurements of the abnormal power flows in networks during solar storms generally do not take into account the effects of the current distortion and unbalance, potentially giving misleading signals to the operators. The normal requirement for optimum system management, while allowing for the possibility of faults caused by lightning, birds and other causes, limits the capacity of system operators to respond to the threats of GICs, which are not assessed easily by the N À 1 reliability criterion. A utility's response to the threat of damage by GICs depends on the expected frequency and magnitude of solar storms. Approaches to formulating a response are located in a system model incorporating space physics, network analysis, transformer engineering, network reliability and decision support and the benefits are identified. Approaches adopted in high-latitude regions might not be appropriate where fewer storms are expected to reach damaging levels. The risks of an extreme storm cannot be ignored, and understanding the response mechanisms suitable for low-latitude regions has the capacity to inform and reduce the uncertainty for power systems planners and operators worldwide.

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“…The customer interruption cost (CIC) is used as a substitute in the assessment of reliability-worth in electric power systems [13]. Numerous studies have been conducted to provide estimates of CICs and a wide range of methodologies has evolved.…”

Section: Cost Benefit Analysismentioning

confidence: 99%