Comparing generator unavailability models with empirical distributions from Open Energy datasetsDeakin, M., Greenwood, D., Brayshaw, D. J. ORCID: https://orcid.org/0000-0002-3927-4362 and Bloomfield, H. ORCID: https://orcid.org/0000-0002-5616-1503 (2022) Comparing generator unavailability models with empirical distributions from Open Energy datasets. In: 17th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), 12-15 June 2022, Online, https://doi.org/10.1109/PMAPS53380.2022.9810629.
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1109/PMAPS53380.2022.9810629 Abstract/SummaryThe modelling of power station outages is an integral part of power system planning. In this work, models of the unavailability of the fleets of eight countries in Northwest Europe are constructed and subsequently compared against empirical distributions derived using data from the open-access ENTSOe Transparency Platform. Summary statistics of non-sequential models highlight limitations with the empirical modelling, with very variable results across countries. Additionally, analysis of time sequential models suggests a clear need for fleet-specific analytic model parameters. Despite a number of challenges and ambiguities associated with the empirical distributions, it is suggested that a range of valuable qualitative and quantitative insights can be gained by comparing these two complementary approaches for modelling and understanding generator unavailabilities.
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