Do-a-thon: Comparison of VRES input generation models

Proposal for:
Do-a-thon

Session Title
Comparison of VRES input generation models

Session Description
We all need VRES generation profiles in our energy systems models, and there are many available models to help us generate them. Many are being developed by openmod’ers! I think it’s time we spoke about the pros and cons of each model, compared them against each other, and, if enough common ground can be found, think about the possibility of merging similar functionalities. We can also spend some time discussing “best practices” when generating VRES profiles for use in energy system analyses.

Examples of Models I have in mind are:

  • Atlite for wind, PV, and hydro generation
  • gsee for PV
  • vwf for wind
  • windpowerlib for Wind
  • PVLib for PV
  • SAM for…everything
  • Also the simulation code for wind and PV which I wrote for my PhD thesis will be put on GitHub in the next week or so

If anyone else has other models in mind, then I think we should also consider them as well.

Anyhow, for this do-a-thon short introductions could be given for each model by those who are familiar with them. Afterward, we could compare the models against each other by performing some on-the-spot simulations, and perhaps also rate them against measured generation data. If anyone has open validation data they would like to share, this would be greatly appreciated (I will bring some). I can also bring weather extracts from MERRA2, ERA5, and COSMO for us to play around with.

Would you like to be responsible for this Session?
Yes

Do you need any special infrastructure for this Session?
Projector

Do you have any recommendations who could be part of this Session?
I mention those which I know have had a hand in the development of some of the models I mentioned above. Apologies if I forgot someone.

3 Likes

Hey Severin,

I think it is a good idea.
I am not able to attend the workshop in January, but could assist you with some thoughts.
I am myself culpable because I created such a tool (https://github.com/tum-ens/renewable-timeseries). When I started, I was not aware of any tool that would assess any shape of regions and provide its potential and representative time series, so I created my own tool and published it in GitHub.
However, I tried to include some correction based on the Global wind Atlas, to match IRENA full-load hours if needed, and to use historical time series / EMHIRES for the regression.
I realized quite late that I could use PVLib to avoid dealing with the physics with solar radiation… but it was instructive nonetheless.
Now that I have done that, I realize that there is not such a thing as the perfect time series. If you use reanalysis data, you will necessarily deviate from measured data (either from power plants or even weather stations, in some regions of the world there is a non-negligible bias and/or time delay). And if you only rely on measured data, you cannot get a full coverage. If you do a regression to match historical generation time series, you might not be able to estimate how the time series should look like if new sites for power plants are added in your region… So there will always be a certain variety in tools. But we definitely should consolidate what exists, and make it visible so that others do not have to reinvent the wheel.

Cheers,
Kais