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Comparing Generator Unavailability Models with Empirical Distributions from Open Energy Datasets

Matthew Deakin*, David M. Greenwood, David Brayshaw, Hannah Bloomfield

*Corresponding author for this work

Research output: Contribution to conferenceConference Paperpeer-review

1 Citation (Scopus)

Abstract

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 ENTSO-e 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.
Original languageEnglish
DOIs
Publication statusPublished - 4 Jul 2022

Bibliographical note

Funding Information:
This work was funded by the Supergen Energy Network (EP/S00078X/2) through the Climate-Energy Modelling for Assessing Resilience: Heat Decarbonisation and Northwest European Supergrid (CLEARHEADS) project. 978-1-6654-1211-7/22/$31.00 ©2022 IEEE

Publisher Copyright:
© 2022 IEEE.

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