For many years BM reports (Balancing Mechanism Reports) have published live generating statistics for UK electricity broken down by generating type. The data have always been fragmentary and difficult to access. Gridwatch have done all energy analysts a great favour and have been saving this data in an easy to access format. The CSV file I downloaded had data for the UK grid at 5 minute intervals from May 2011 to present. Below the fold are detailed charts of generating statistics broken down by nuclear, coal, gas and wind, from Jan to April 2013 – each chart contains about 9000 lines of data!
It happens quite often when I’m researching a post that I end up producing too many charts. So this post is really a chart-feast. My next post – hopefully Thursday, will take an even deeper look into UK electricity generation policy, the impact of wind on the grid and on UK trade balance. Too many charts would get in the way of the central messages of that post and so this is a dumping ground for all the charts.
Click on all charts to get a larger copy. Drag and drop to your desk top to keep a copy and then share if you want. But please read Blog rules before publishing elsewhere.
Figures 1 to 4 are stacked area charts of UK generation by source, January to April 2013. Many may recall that March was unseasonaly cold in the UK. If you don’t understand what these charts are showing then please read Electricity Supply and Demand for Beginners. The x-axis scale is time, the first peak being the first day of the month. With 9000 data points, it is not easy to display a proper time scale. The key observations:
- The peaks in demand are about 55,000 MW in January, but peaks >50,000 MW occur throughout February and March.
- By April, we were warming up and peak demand had dropped <40,000 MW by the end of the month.
- A significant part of the base load is met by unvarying nuclear power.
- The rest of the base load is met by coal that is cycled down a little at night time to help accommodate the daily demand cycle.
- Combined cycle gas turbines (CCGT) provide little base load but most of the daily peak in demand.
- Wind is now a significant generating source, that comes and goes, and seems to be eating significantly into the CCGT part of electricity market share.
- The “Other” category includes French, Dutch, Irish and EW imports / exports via inter-connectors, pumped storage, conventional hydro, oil, open cycle gas turbines and “other” that combined, in conjunction with cycling the CCGTs, are used to balance the grid.
Figures 5 and 6 show the utilisation of generating capacity by source for February and March. I didn’t have time to plot these charts for January and April. Load factor is a measure of power station utilisation relative to its “name plate” capacity. For example, if a CCGT is designed to produce 500 MW, but on average only produces 200 MW throughout a year, then its annually averaged load factor is 2/5=40%. The key observations:
- Nuclear load factor is high and relatively stable.
- Coal load factor is high but fluctuates to help in grid balancing.
- CCGT load factor is much lower and fluctuating a great deal, providing a huge amount of balancing service to the grid.
- Wind load factor is also lower and fluctuating according to the prevailing weather. It is providing zero balancing service.
Figures 7 to 10 take the data displayed in Figures 5 and 6 (including Jan and April) and sort it according to load factor. The x-axis is therefore time, 1 month, but a discontinuous time series. These charts provide a profile of generating load for each month. The key observations:
- The load factors for nuclear and coal are both very high, exceeding 100% for short spells in January (Figure 7).
- The load factor profiles for CCGT and wind are similar. That does not say that gas and wind are providing the same amount of electricity since the capacity for CCGT (30724 MW) is much higher than the capacity for wind (8625 MW). Furthermore, wind provides zero balancing service whilst CCGT provides the greater part of grid balancing to accommodate the predictable daily demand cycle and the stochastic variable supply of wind.
The discussion of the implications of these observations will follow later this week. If you like the post, then please share.