Author: Robert Wilson
Over at Vox, Brad Plumer has a good explainer of Obama’s Clean Power Plan. Roughly speaking each state will have to cut carbon dioxide emissions from power plants by a certain percentage.
The state goals worked out by the EPA obviously result from a combination of the existing electricity mix in each state, current economics and political lobbying.
One factor that plays into it (or probably did) is the age of coal power plants. Young coal power plants are more difficult to retire than old ones. This is relatively indisputable. On the international stage this is best seen by comparing Britain with China. Britain has not built a new coal power plant in the last three decades. The vast majority of China’s were built this century. Britain will effectively phase out its existing fleet within a decade. China will be lumbered with its for the next 50 years or so.
If we want to find out the average of coal power plants in each US state we will have to calculate it ourselves using EIA data. EIA’s Form 860 lists the capacity and operating year of more or less all US power plants. The main fuel used in power plants is given, along with the capacity and state. This is enough to give us fairly accurate estimates of the average of coal power plants in each state.
So here they are, ranked from top to bottom.
|State||Coal capacity (GW)||Mean age||State||Coal capacity (GW)||Mean age|
|New York||2.63||49.89||North Dakota||4.24||37.30|
|South Dakota||0.48||40.78||South Carolina||6.28||31.23|
Tennessee has the oldest coal power plants in America. On average they were built half a century ago. Texas and Arkansas both have relatively significant and relatively young coal power plants. They are just under 30 years old, 20 years younger than those in Tennessee.
It would be interesting to compare the numbers in this table with the state goals set by EIA. If I have the time this weekend I might do a simple analysis of this. Obviously states with older power plants will be able to close them earlier, and thus reduce their emissions faster. It’s also true that older power plants tend to be less efficient. So it should, all things being equal, be much easier for Tennessee to reduce its emissions from coal power plants than it is for Texas. Of course, not all things are equal.
Note on data
State by state data used is available here.
Mean age is weighted by the capacity of each plant.
I processed the data in R and produced the html table using xtable. I have had to manually adjust the EIA files to make them readable in R, so I’m not in a position to post easily reproducible code here. If anyone wants the R code and simplified EIA files used for this they can email me.
When you find yourself using clichéd language it is wise to reach for something. My preference is espresso, in the hope that the use of cliché is evidence of an unready mind.
The use of cliché is only advised if you acknowledge exactly what you are up to. Casual references to nuclear fusion “always being thirty years away” imply that this cliché is all you know about nuclear fusion. And the implication is probably valid most of the time. Acknowledge that you are using a cliché and the reader might realize you aren’t clueless.
Another cliché is the use of “sobering statistics”, the phrase that is. (And before you ask, yes I have used it.)
What is it about these statistics that is sobering? Are we supposed to be in the middle of a decades long bender, to be shaken out of a state of perpetual inebriation by the mention of percentages?
Who exactly wants to be sober?
Can we not have depressing statistics, startling statistics, frightening statistics, jump out of your seat statistics, shit your pants statistics, fire your politicians statistics, do something to improve the world statistics, anything but sobering statistics.
I have decided to (possibly permanently) close the comments on the blog.
Right now I’m too busy to moderate them or put in the effort to improve the quality of discussions. This may change in future, but it’s not likely to for a few months.
Thanks to those who have commented previously. If you think there is something wrong, right, needs to be improved with a future post, or want to bother me for any other reason, my email address is under “Contact” above.
Where has the online discussion gone? When I started this blog two and a half years ago there were frequent (and importantly: informative) discussions below the line.
For some reason this seems to have stopped. Perhaps it is because I used to be more active on Twitter and so people from there would keep the discussion going here.
But perhaps not. It seems more likely that people are just discussing things on Twitter, Facebook and elsewhere. Blog comments are in evident decline.
It’s not because of less traffic. So far this year I’ve already got more hits than I got in the entire year in 2013 or 2014. More people are reading, but fewer are commenting. And the quality of the comments is often not overly good. Blame Reddit for increasing traffic and lowering the quality of comments.
So I am considering closing the comments on the blog.
I run this blog in my spare time, so having comments up is a trade off. Maybe I, and other readers, can learn something from a comment. And good discussions are possible. But I also have to take time to police the comments, and read them one by one to make sure nothing libellous appears on the site. It becomes tiring to have to filter out people who can’t read an article and attack you for views you don’t hold.
At the minute it looks as if the time spent monitoring them is not worth it.
Unless someone can persuade me otherwise the comments will likely be down tomorrow…..
In a post last week I showed the average daily cycle of wind farm output in California. However, averages over the entire year often mask important seasonal variations. So, let’s look at the daily cycle of wind power output in each month of the year.
Again I will use hourly CAISO wind farm output data.
Here is the main daily cycle of wind farm output in each month and for 2013 and 2014. This of course masks the fact that wind farm output varies massively from day to day. However, the main daily cycle is an important indicator because the closer this comes to the the daily cycle of electricity demand the better.
Clearly there is a very pronounced season cycle. In January, November and December there is arguably no daily cycle whatsoever. Wind farm output is almost flat all day round, on average.
This cannot be said for summer. In July wind farm output is roughly 3 times higher at midnight than it is in the middle of the day.
California therefore sees very pronounced seasonal and daily cycles of wind farm output.
If I can I will write a follow up post comparing the cycle of wind farm output and the cycle of electricity demand in California.
I will be blogging very lightly in the next week or more because I’ve got some stuff that needs done. There’ll still be some product, but this will mostly be me posting R code for producing some of the plots etc. in recent posts. Read the rest of this entry »
“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. Read the rest of this entry »