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It doesn't add up...'s avatar

You can actually get the renewables.ninja data (or at least a version of it) here:

https://www.renewables.ninja/downloads

It does have the virtue of providing long histories, and the methodology ties back the estimates to satellite weather data, with supposedly a correlation to real world data too. More recent years are available if you sign up. The data are given as fraction of capacity generation hourly. It's perhaps a shame that they haven't explicitly published the data used by the Royal Society. I ought to write to Iain Staffell and ask him to do so.

It's important to remember that the Gridwatch data only includes the transmission connected windfarms that are visible to the grid control room (live "metered"), so it leaves out quite a bit of onshore wind that is connected at the distribution level, plus some small offshore projects. A rising complication now is from curtailment - some paid for, and some simply when prices are negative and the subsidies don't apply to some of the CFD holders and those who have yet to commence their CFD.

However, the older data is less affected, and should allow comparison between them. A very useful technique is to look at the cumulative sum of each series relative to its mean. By subtracting the series mean from all points and cumulating you get a clear idea of the behaviour, and whether the modelled data really does look like the actual data when you chart them. I know when I did this for Andrew Blakers' study on Australia I was easily able to show that his wind modelling was entirely phony. Periods of Dunkelflaute and runs of windy weather show up as negative and positive slopes respectively. Seasonal variations will result in significant cumulative deviations.

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Alan Jones's avatar

This comment may be a bit late to the table as they! I was looking back through you posts when I came across this at at a time when I was reviewing a paper about European Dunkelflaute. The paper used 36 historical years of data and identified that winter 1995/6 was the worst case scenario and it also affected the UK. The paper made the following statements:

1/ Models must incorporate multiple weather years (not just average or recent years) to design resilient systems.

2/ Summer-to-summer modeling horizons are better suited to capture winter Dunkelflaute events that span calendar years.

3/ Energy system models and policy must account for rare but extreme weather events to ensure robustness.

For more information see my document https://bit.ly/UKEA-Coping-with-the-Dunkelflaute

This prompted me to look for wind droughts that affected the UK. The have been three since 2010/11. The worst was the Big Freeze in 2010/11 where for 42 continuous days the daily load factor reported from Dukes averaged ~6.1% in contrast to the typical ~23% at the time. For more information see https://docs.google.com/document/d/1nvEfwOm_3GmL_G_fs3P3-210kLRy4d6kCIPBtSEo3CU/edit?usp=sharing

I wonder whether you would care, for fun, to analyse the Big Freeze in the same way that you have assessed period in 2020 and 2021.

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