Risk-based interruption cost index based on customer and interruption parameters
Doctoral Thesis
2014
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University of Cape Town
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Abstract
Modern competitive electricity markets do not ask for power systems with the highest possible technical perfection, but for systems with the highest possible economic efficiency. Higher economic efficiency can only be achieved when accurate and flexible analysis tools are used. Thus, the modelling of reliability inputs, methodology applied in assessing supply reliability and the interpretation of the reliability outputs should be carefully considered in power system management. In order to relate investment costs to the resulting levels of supply reliability, it is required that supply reliability be quantified in a monetary way. This can be done by calculating the expected interruption costs. Interruption costs evaluation, however, cannot be done correctly in all cases by methods that are based on the commonly used average values. It is the objective of this thesis to find a new way of calculating interruption costs which would combine the precision of a probabilistic method with the flexibility and correctness of customer and interruption parameters. A new reliability worth index was found, based on customer and interruption parameters. This new index was called a Risk-based interruption cost (RBIC) index and is described in detail in this thesis. The technique applies a time-based probabilistic modelling approach to network reliability worth parameters. The approach uses probability distribution functions to model customer interruption costs (CICs) while taking into account seasonal, day-of-week and time-of-day infl uences. In addition, customer specific parameters - economic activity, energy consumption, turnover and power interruption mitigation measures are used to segment electricity customers into customer cluster segments of similar cost profiles. Unlike the conventional deterministic approach, the new technique thus considers variability in CICs. The new model and methods to calculate the new reliability worth index have been implemented in a computer program and the accuracy of the calculation method was tested in various case studies and by comparison with the traditional average process. This research shows that probability density functions are superior to deterministic average values when modelling reliability worth parameters. Probability distribution functions reflect the variability in reliability worth parameters through their dispersion and skewness. Disregarding the effects of probability distribution of the interruption cost leads to large errors, up to 40% and more, in the calculated expected interruption costs. The actual error in specific reliability worth calculations is hard to estimate. It is however clear that this error cannot be simply ignored. Furthermore, the risk-based approach applied to the interpretation of risk-based interruption cost (RBIC) index significantly influences the perception on the network's reliability performance. The risk-based approach allows the uncertainty allowed in a network planning or iv operation decision to be quantified. Use of the new reliability worth index offer more flexibility in reliability worth assessment and produce more accurate results. It can be used in all areas of power system reliability worth assessment which have always been exclusive domain of the average process.
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Includes bibliographical references.
Reference:
Dzobo, O. 2014. Risk-based interruption cost index based on customer and interruption parameters. University of Cape Town.