“Give a man a reputation as an early riser and he can sleep til noon” – Mark Twain.

There is apparently no greater leader on climate change than Germany. Here is some evidence. This country will build almost 11 GW of new coal power plants this decade, and is in the process of licensing new lignite coal mines. It prematurely shut down 8 zero-carbon nuclear power plants in 2011, closed another one this year, and will prematurely close all remaining nuclear power plants by 2022. Germans have reassured themselves by turning from the disturbing vision of the split atom to the nostalgia of coal fires.

But where does Germany’s climate change reputation come from? It certainly does not come from achievements in reducing greenhouse gas emissions. This decade Germany’s emissions have been essentially flat, and Germany is on course to come a long way short of meeting its 2020 national targets for emissions reductions.



This planet saving reputation instead comes from what Germany has supposedly achieved with renewables. The German renewables revolution is apparently in full gear. If you want to understand what is happening in the world it is better to ignore adjectives and instead count.

Counting is instructive about the realities of renewables in Germany. According to the most recent data, Germany got only 3.3% of its final energy consumption from wind and solar installation (Eurostat data for 2013 available here and here).

Does that sound like a revolution? Obviously not.

The 3.3% figure above tells us that renewables are in fact marginal to Germany’s energy system. So where does this idea that there is a renewables revolution in Germany come from?

The answer is easy to find by googling and searching social media. This will immediately lead you to the following type of headline:

Another popular variant are headlines about German solar output exceeding 50% of electricity demand. The obvious problem with these headlines is that many people come to the mistaken conclusion that these record highs are somehow representative of what goes on the rest of the time. They are not.



Let’s quantify this. The record high renewables output (which included biomass and hydro, a fact rarely pointed out) occurred on the 25th July. Total wind and solar output was around about 39 GW according to Fraunhofer ISE data.

How often does this happen? This is relatively easy to find out. All we need to do is add up all hourly wind and solar output and see how it is distributed throughout the year.

I have done this in the graph below. Hourly output was rounded to the nearest gigawatt. I have then added up the number of hours when total wind and solar output fell under each GW bracket. Each bracket covers the average output over an individual hour, in GW.

In total we have about 40 brackets, starting at 0 GW. Yes, German wind and solar falls to zero gigawatts, rounded to the nearest gigawatt. Resist that temptation to write “German wind and solar now meeting 0.1% of Germany energy needs” headlines.



Mean hourly output of German wind and solar was 9.6 GW in 2014, while the median output was 8 GW. The maximum output was almost 39 GW; four times greater than the average, no matter how you define the average.

Furthermore, total wind and solar output was above 30 GW only 2.1% of the time. It was above 25 GW only 9.6% of the time.

The heavily skewed distribution shown above has clearly lead to heavily skewed perceptions about German renewables.

So each time you see headlines about record high renewables output remember this: average output of combined German wind and solar is roughly one quarter of these record highs, and German wind and solar is still just over 3% of final energy consumption in Germany.

Note on data

Anyone wanting to reproduce or check the figure above can use the R code below.

# Author: Robert Wilson # File calculates distribution of hourly wind and solar output in Germany in 2014 require(gdata);require(dplyr);require(ggplot2) options(stringsAsFactors = FALSE) # Get the data fn = "http://www.pfbach.dk/firma_pfb/time_series/data_files/2014_de_pv.xls" download.file(fn,destfile="tmp.xls") pv = read.xls("tmp.xls", header=TRUE, skip = 2) names(pv) = c("Date", "Hour", "Solar") fn = "http://www.pfbach.dk/firma_pfb/time_series/data_files/2014_de_wind.xls" download.file(fn,destfile="tmp.xls") wind = read.xls("tmp.xls", header=TRUE, skip = 2) names(wind) = c("Date", "Hour", "Wind") # Combine the data and calculate distribution of hours by GW output data = join(wind, pv) data$Total = round((data$Wind + data$Solar)/1000) total.sum = dplyr::summarize(group_by(data, Total), Hours = n()) # Plot the data ggplot(total.sum, aes(Total, 100*Hours/nrow(data)))+ geom_bar(stat = "identity")+ ggtitle("Germany's record high wind and solar output is 39 GW

This is not representative of the rest of the year")+ scale_x_continuous(breaks = seq(0, 40,5))+ xlab("Hourly output of wind and solar (rounded to the nearest GW)")+ ylab("% of total hours in 2014")