Machine learning can boost the value of wind energy
1–10 of 38 posts
Re: Machine learning can boost the value of wind energy
#2> To date, machine learning has boosted the value of our wind energy by roughly 20 percent, compared to the baseline scenario of no time-based commitments to the grid.
This is a fantastic first result. I wonder why we aren’t seeing that many ML being applied to large energy industries yet. It makes perfect sense from every angle. You can get measurably better results and thus it should be an easy sell for dev teams.
Other similar industries ML is being applied right now?
Re: Machine learning can boost the value of wind energy
#3Is this a substantial improvement over existing neural network models? I’ve seen models that were being used to trade renewables on PJM’s market that seemed at least as good as these. And, similar models are currently being used to manage DERs in micro-grids.
I don't mean to downplay these results. I’m not an expert. Just mentioning it in case someone at deepmind sees this and wants to reach out to PJM. I believe those models were created almost 10 years ago.
Re: Machine learning can boost the value of wind energy
#4> Using a neural network trained on widely available weather forecasts and historical turbine data, we configured the DeepMind system to predict wind power output 36 hours ahead of actual generation.
Interesting. Something I've long wondered about:
- Many wind farms are located in very specific places that have measured high winds and are otherwise good places to locate a wind farm.
- Global climate change is changing local climates too. Are the studies that were done 10-20 years ago to discover ideal wind farm locations no longer as accurate as they used to be?
- How are wind farm locations decided today? Is there is skill in predicting where a wind farm might be optimally located in 5 years rather than where it should be located today? Or if not (since probably not) what are the right risk mitigation actions to take if you are planning a wind farm but unsure about location?
- Since Machine Learning is useful in improving the value of the existing wind power, could it also be useful in this endeavor, finding optimal wind power generation locations?
- Lastly, is this something a person could research at home with open data and code? Just curious. :)
Re: Machine learning can boost the value of wind energy
#5I have been working in the same field, quite a few years in my own forecasting company and then later on as a side project.
Not wanting to steal the thunder of Deepmind, but I feel should mention my site which is currently beta as in "works for a few electricity power load and supply forecasting scenarios" and quite well so. Also, it's out there, cheap and fast.
https://ausblick.cryptoport.net
Unfortunately, it's only in German but the basic rule is:
- upload an excel (or csv) file
- wait a minute or so (for a typical dataset of say 3 years of hourly data)
- get back the results
There are a few design rules how the excel file should look like, e.g.,
- a date/time series per sheet (it accepts most English and European formats) and as many number series as you want (always use a decimal point instead of comma here)
- one series has to have consecutive missing numbers at the end, this will be the target value
Other than that, it should just work.
Feel free to comment.
PS: The examples might be the best explanation - https://ausblick.cryptoport.net/examples
Re: Machine learning can boost the value of wind energy
#6I have been working in the same field, quite a few years in my own forecasting company and then later on as a side project. Not wanting to steal the thunder of Deepmind, but I feel should mention my site which is currently beta as in "works for a few electricity power load and supply forecasting scenarios" and quite well so. Also, it's out there, cheap and fast. https://ausblick.cryptoport.net Unfortunately, it's onl…
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Re: Machine learning can boost the value of wind energy
#7A demonstration of the astonishing value of a relatively small government program: weather observation and forecasting.
Re: Machine learning can boost the value of wind energy
#8I have been working in the same field, quite a few years in my own forecasting company and then later on as a side project. Not wanting to steal the thunder of Deepmind, but I feel should mention my site which is currently beta as in "works for a few electricity power load and supply forecasting scenarios" and quite well so. Also, it's out there, cheap and fast. https://ausblick.cryptoport.net Unfortunately, it's onl…
What prediction algorithm are you using for this? Not sure if it's mentioned elsewhere on the site
Re: Machine learning can boost the value of wind energy
#9Reminds me of some of the excellent advice in Bret Victor's essay about global warming:
http://worrydream.com/ClimateChange/
The investment is not only in the machinery, but in tools to model, observe, and predict efficiency.
Re: Machine learning can boost the value of wind energy
#10Is this a substantial improvement over existing neural network models? I’ve seen models that were being used to trade renewables on PJM’s market that seemed at least as good as these. And, similar models are currently being used to manage DERs in micro-grids. I don't mean to downplay these results. I’m not an expert. Just mentioning it in case someone at deepmind sees this and wants to reach out to PJM. I believe tho…
It is probably not. Their neural network to optimize their warehouse efficiency had 6 neurons. The neural network used here is probably pretty small too