This is correct. What's important for industry is understanding the energy balance, i.e. entries and exits to and from the grid. "Generation" is a catch-all term for grid entries.
HN user
dannyfraser
Generation in this instance means power generation to meet consumption demand. Typically withdrawals from storage are counted as a source of supply to meet that demand regardless of the original source of the power in storage.
A bit of digging in the T&Cs, Companies House, and LinkedIn pointed me to an individual working for the NHS who has put this together as a side project.
I work in this space (https://www.woodmac.com/), mostly with natural gas data but have worked on power in the past so I'm always interested to see if it's anyone I know (in this case it isn't).
Building something like this isn't really that difficult - all of the data is publicly accessible and if you can transform it and pull it into a database and build a front-end app then you're pretty much there. The developer has stated that the main source for this is https://bmrs.elexon.co.uk/, but other good sources of energy data (across Europe) are https://transparency.entsoe.eu/ for power and https://transparency.entsog.eu/ for gas. Also useful are https://alsi.gie.eu/ for LNG imports and https://agsi.gie.eu/ for gas storage.
I find it really weird that a discussion on the state of SQL right now doesn't include any mention of Snowflake or dbt. SQL is _everywhere_ in the data engineering world right now.
The Open University runs a Master's program in systems thinking (which I'm currently studying). There's a free primer course called 'Mastering systems Thinking in Practice' that gives a good overview and is full of references for further reading in the field: https://www.open.edu/openlearn/science-maths-technology/mast...
There's also a developing community at https://www.systemsinnovation.network/, where there are also many (subscription) resources.
The articles, books, and guides available (free) at https://thesystemsthinker.com/ are also worth a look. This mostly pertains to system dynamics rather than any other traditions, but it's a great resource for understanding complexity.
I visited Boston from the UK last year and was struck by the lower level of traffic noise. I attributed it to there being far fewer diesel cars and more EVs & hybrids. In the UK we have diesel powered buses and taxis everywhere as well as lots of personal cars, and the engines all have a much deeper and louder rumble than petrol engines.
It's called a monopsony.
No radar, auto-aim off, license to kill, pistols, go!
Oh that last point! My friends and I used to just strafe along every single wall and all you could see was the wall texture until it was time to shoot. We knew all the levels so well that just the changes in lighting, or sometimes how quickly a door opened, were enough for us to tell where someone else was (avoid the coloured corridors in Complex).
Screen cheating is a skill, countering it is a skill, and countering THAT is an even bigger skill.
The all-Europe equivalent is ENTSO-E[1], which has down to 15-minute granularity (depending on operator I think) data for every generation unit in Europe.
There's a similar platform for the gas network too[2] - only daily data but it does have a map interface where you can see the main transmission pipelines across the continent.
I work in energy markets analytics, so grab data from these on a regular basis for SMEs.
[1] https://transparency.entsoe.eu/ [2]: https://transparency.entsog.eu/#/map
Agreed. I read the Mistborn books a few years ago and just found them very... sanitised, especially compared to other prominent fantasy novels by the likes of Scott Lynch or the brilliantly sweary Joe Abercrombie.
This is a great use of digital elevation data to generate images of what's visible from various places. It appears to be a real labour of love from the author.
My favourite kind of web scraping is when you have to pick apart some undocumented API that serves up data to an SPA, then figure out how to tidy up the response(s) into a single pandas dataframe. Always a satisfying feeling to solve one of those little puzzles.
I don't think that's a fair comparison. The New Yorker is a magazine that curates and publishes articles by people who write for a living and stakes its reputation on only publishing pieces of a high quality.
The distinction here really is if someone publishes on joesblog.com or on medium.com/joesblog. Both are self-published rather than selected for publication, but the OP was of the opinion that joesblog.com is an indicator of higher quality of content, which I don't think is true. All it indicates is that someone has been able to set up a website.
“Oh this person just throws stuff on Medium? Probably not worth my time.”
This is just the worst attitude. Someone's not worth your time because they don't have the knowledge or time to stand up a website on their own domain? People who aren't web developers might still have something interesting to say.
Martin Gardner came up with a somewhat contrived but still brilliant extension to this:
"Wouldn't the sentence 'I want to put a hyphen between the words Fish and And and And and Chips in my Fish-And-Chips sign' have been clearer if quotation marks had been placed before Fish, and between Fish and and, and and and And, and And and and, and and and And, and And and and, and and and Chips, as well as after Chips?"
https://en.wikipedia.org/wiki/List_of_linguistic_example_sen...
Containers or environment management solve this problem quite easily. All of my major projects have a conda environment alongside them, and I expect I'll be shifting things over to Docker containers as my org starts shifting things to the cloud.
As far as I know they build up a graph of the cell execution order, so recursive loops are quite easy to find.
There was a good read on this in the most recent issue of Wired UK as well: https://www.wired.co.uk/article/cavendish-banana-extinction-...
Malcolm Gladwell's podcast had a good summary of the issue, including the pedal confusion.
One red, one black.