gridstatus VS PyPSA

It’s a wide range of sources but basically the different Independent System Operators in the US and the Energy Information Agency (EIA) All of our data scrappers are open source: https://github.com/kmax12/gridstatus

I did not create this, just found it. I think the creator can be reached via GitHub: https://github.com/kmax12/gridstatus

Long-term trends clearly demonstrate the energy grid’s transition to renewable energy sources.

However, renewables like solar and wind come with unique challenges due to their intermittent nature. They are more variable, harder to forecast, have location constraints, and can benefit from battery storage. These factors lead to a more dynamic grid than before.

For instance, several regions in the country provide five-minute updates on their energy generation mix, enabling near real-time observations of renewable energy effects throughout the day

For example, numerous regions across the country provide updates on their energy generation mix at five-minute intervals, allowing for close to real time observations of these effect of renewables throughout the day.

To help those involved in the energy transition, I created an open-source project called Grid Status (https://github.com/kmax12/gridstatus) that provides fuel mix, wholesale pricing, load, load forecasts, and more.

Additionally, I've developed real-time visualizations to make this data more accessible and easier to comprehend: https://www.gridstatus.io

I hope making this data more accessible and understandable will accelerate the transition away from fossil fuels.

Here's the project: https://github.com/kmax12/isodata. Let me know if you're interested in collaborating!

This study about the European grid quantifies all this. If you want to go deeper into how they get these numbers, you'll need to read about PyPSA or other grid modelling tools. It's all open source and well documented.

You need to know how energy models work, and I invite you to read about them. Check out PyPSA for instance (paper, Source code)). That would answer both points above and more. For instance, you need to know that they are based on real weather and consumption data, so they account for natural variability. They know the cost of producing synfuels, and they optimize around it to find the cheapest system overall given the input technologies and assumptions. These calculations would be impossible to do by hand.