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Comparing generator unavailability models with empirical distributions from Open Energy datasets

Deakin, M., Greenwood, D., Brayshaw, D. J. ORCID: and Bloomfield, H. ORCID: (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,

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To link to this item DOI: 10.1109/PMAPS53380.2022.9810629


The 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.

Item Type:Conference or Workshop Item (Paper)
Divisions:Interdisciplinary centres and themes > Energy Research
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:105098


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