Here are the average capacity factors for offshore wind farms in UK waters, newly updated to include data to the end of December 2017 (though there are still some figures to come through for the last couple of months of last year, for the smaller windfarms). And you might be interested in comparing these with the capacity factors and load-duration curves for Belgium, Denmark and Germany.
Category: offshore wind
Here are the average capacity factors of every Danish offshore wind farm, newly updated to include data to the end of November 2017. The Anholt 1 windfarm, which only opened in 2013, hit an average capacity factor of 47.4% for the full year 2016. Compare these with the capacity factors for German, and UK, and Belgian offshore wind farms.
Previously I’ve provided the figures for Danish offshore windfarms, for the UK , and for Belgium too. Here are the numbers for the larger German offshore windfarms. The ones shown here are the only ones I’ve been able to get detailed data for, so far.
German offshore wind capacity factors
|All numbers are to the end of September 2017. Analysis by EnergyNumbers.info.||Latest|
|Amrumbank West||42.0%||42.1%||1.9||302||2 043||3.9|
|Bard Offshore 1||28.1%||0.5||400||470|
|Borkum Riffgrund I||40.4%||40.4%||2.0||312||2 180||3.5|
|Gode Wind I||33.8%||0.3||330||329|
|Gode Wind II||33.2%||0.3||252||247|
|Nordsee Ost 1||36.5%||34.8%||2.4||144||1 040||2.8|
|Nordsee Ost 2||37.3%||35.2%||2.4||144||1 062||2.8|
|Windpark Baltic 1 & 2||47.0%||45.2%||1.9||336||2 555||4.1|
Load duration curves
I’ve constructed for each of the offshore windfarms for which there is detailed hourly data. Use the pause and play buttons to stop and start the sequential display of curves. Click on the windfarm name in the legend to toggle the display of that farm’s curve.
Note that for each individual windfarm, its curve is based on data starting from the date that the windfarm was fully commissioned, and the windfarm’s age is calculated as starting at that date. There is one exception: the Bard Offshore Windfarm was fully commissioned in August 2013, but detailed data on its generation is only available from spring 2017 onwards – so the “age” shown for this windfarm is the age of the oldest available data, not the age of the windfarm itself.
The numbers for DanTysk did look strange: I had to clean a stretch of five months of data that was clearly wrong. A small kink remains in its load duration curve; this may be an artefact of some of the problematic data.
Windfarms less than a year old are excluded from the calculations of the power density per unit area spanned. The figure for total power density is a weighted average of the windfarms that are a year older or more: this is weighted by size, but not by time. So a windfarm that’s twice as large contributes twice as much to the total; whereas a windfarm that’s twice as old, does not.
On 17 December 2015 Britain passed a new landmark on the road to cleaner electricity: for four hours, from 03.00 to 07.00, the grid had a plurality of wind: wind was the largest generation type on the grid: there was more wind generation than generation in Britain from gas, or from coal, or from nuclear, or any other domestic source. That was the case for the four hours as a whole, and for each half-hour within that four-hour period.
Is land area a barrier, or a significant constraint, to achieving 100% renewables?
It’s been a remarkable few months for wind generation in Britain, Feb 2014 – Jan 2015, and the last of those two months in particular. Several records were broken, and re-broken.
You can see the live British grid data, including wind generation, here; and here’s a version for mobiles (cellphones) and other small-screen devices.
February 2014 saw the highest monthly average metered wind power generation that Britain’s ever achieved: in that month, average generation from metered windfarms was 4.09 GW.
The half-hour starting at 06.00 on the morning of 18 October 2014 saw the highest percentage contribution of wind (penetration) to total demand: 23.5% from metered windfarms; 32.9% from all windfarms.
The half-hour starting at 19.30 on 9 December 2014 saw the highest half-hourly wind generation: 6.80 GW from metered windfarms; 9.42 GW from all windfarms.
And until January 2015, December 2014 also had the highest amount of wind-generated electricity of any month: 3.90 TWh (of which a record 2.85 TWh was from metered windfarms); and the highest monthly contribution from wind to total demand – 13.9% from all windfarms (the highest contribution from metered windfarms was 10.5%, in February 2014). But January 2015 outdid the preceeding month, with 14.4% of demand being met by metered and embedded wind; 4.13 TWh of wind in total, which was equivalent to an average power of 5.56 GW; and 2.95 TWh from the metered windfarms.
Records for electricity generation from wind in Britain
|analysis by EnergyNumbers.info||All windfarms||Metered windfarms only|
|Monthly||Max wind penetration||14.4 %||Jan 2015||10.5 %||Feb 2014|
|Maximum energy||4.13 TWh||Jan 2015||2.95 TWh||Jan 2015|
|Max average power||5.56 GW||Jan 2015||4.09 GW||Feb 2014|
|Half-hourly||Max wind penetration||32.9 %||2014-10-18 06.00-06.30||23.5 %||2014-10-18 06.00-06.30|
|Max average power||9.42 GW||2014-12-09 19.30-20.00||6.80 GW||2014-12-09 19.30-20.00|
(thanks to BMReports and Elexon for the raw data I used for this analysis)
Introducing the EnergyNumbers 2050 Pathways calculator
The DECC 2050 calculator is a good start at producing a toy model to give some ideas of the trade-offs, and approximate orders of magnitude of costs involved in converting Britain’s energy systems into a low-carbon system.
But it has its flaws.
So I’ve revised some of the model’s weakest parts, and re-released it. Here’s the EnergyNumbers 2050 Pathways calculator
A summary of the changes (most recent, first)
- Added a new option to change the amount of fossil-fuels (coal, gas, oil) extracted in the UK. This option exists in the DECC spreadsheet, but wasn’t previously available in the web interface.
- Added a whole new section with performance against national and international targets. In the top-left corner of every page, you’ll find indicators showing progress against targets. Click on them to read an explanation of each target, and how well the selected pathway performs against each.
- Change nuclear level 1 to phaseout by 2020; bumped all the other levels up by one (so old level 1 is new level 2; old level 3 is new level 4), and updated all the “expert” pathways accordingly. Old level 4 wasn’t plausible, wasn’t used in any of the “expert” pathways, and so has been removed
- Added estimated damage costs for greeenhouse gases: low £70/tCO2e; medium £100/tCO2e; high £200/tCO2e
- Added estimates of nuclear liability costs: low 0p/kWh; medium 11p/kWh; high 100p/kWh
- The choice of car and van techology, between fuel cells and electric batteries, is a category scale (A,B,C,D), not ascending order of difficulty (1-4)
- Ensure coal capacity has a floor of zero
- Selecting biomass plant will not drive up coal use
- Updated nuclear build costs: high £4.548/Wp rising to £5.072/Wp; medium £3.50/Wp; low £2.478/Wp
- Onshore wind, level 4 upgraded to hit 50GWp by 2020 and stay steady
- Offshore wind fixed-foundation, level 4, from 2020 onwards, upgraded to 10GWp annual installation rate
By 2008, Matilda was the world’s most productive wind turbine, having generated 61.4 GWh of energy by the end of its life.
But by the end of March 2010, this record had been broken four times over, Read more…
The map below shows the live positions of ships working on the Walney offshore wind farm, off the coast of Blackpool and Barrow-in-Furness. It’s not as good as sitting on the dock of the bay, watching the ships roll in and roll out again, but it’s better than a slap in the face with a wet cod.Read more…