Comparing Generator Unavailability Models with Empirical Distributions from Open Energy Datasets

TL;DR

This paper compares different models of power plant unavailability with real-world data from open energy datasets, highlighting limitations and the need for fleet-specific parameters to improve accuracy.

Contribution

It introduces and compares fleet-specific unavailability models against empirical data, revealing limitations of non-sequential models and emphasizing the importance of tailored parameters.

Findings

Non-sequential models show high variability across countries.

Sequential models indicate the need for fleet-specific parameters.

Comparing models with empirical data provides valuable insights.

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.