Comparing generator unavailability models with empirical distributions from Open Energy datasets

Deakin, 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. doi: 10.1109/PMAPS53380.2022.9810629

Abstract/Summary

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)
URI	https://reading-clone.eprints-hosting.org/id/eprint/105098
Identification Number/DOI	10.1109/PMAPS53380.2022.9810629
Refereed	Yes
Divisions	Interdisciplinary centres and themes > Energy Research Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
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