Thanks for signing up to PY_WRAM. I figured it may be good to have a post so people could Introduce themselves if they wish.
I suppose I should start . My name is David McCracken, I am based in Glasgow, Scotland and I am the team leader of one energy analytics team of SSE Renewables (at least at present as I will be moving to BP in Septemberš) .
I am a keen user of Python but despite me starting this forum I still consider myself a novice ( although I am getting better) .
My name is Marta Gil and I work at Vortex FdC (Barcelona). I have been using python for three years almost every day, and I am absolutely in love with xarray.
I have no formal education on using python (just stack overflow and trial and error), so I am sure many of the things I do could be improved and better generalized. This is why I think a forum like this is a great idea, and I am looking forward to see where it leads us.
I am Gerard Castro and I am based in Barcelona, where I am working at Vortex FdC as well. There, I am mainly focused on the seasonal forecasting project, and also interested/working in ML & DL applications to WRA & modelling. Self-taught in python as well (+/- aligned with PCPP-32-101: still there is pretty room for improvement), I mostly use xarray, numpy and pandas in my day-to-day work.
Iām Andy Clifton from enviConnect in Stuttgart, Germany. Weāre using Python for most of our data processing work. I also lead the digitalisation working group that weāre spinning up for IEA Wind Task 52 on wind lidar.
Iām keen to see how others are using python in wind energy and find out what is really needed - providing solutions that are useful is how weāll help people give up Excel
I am Gohar Shoukat. I am currently residing in Dublin, Ireland and have a background in Marine Renewables. I work with Python and lead the digitisation of the tools used in the offshore wind design engineering.
Iām Bjarke Tobias Olsen from Copenhagen, Denmark. I have a background in meteorology and have been using Python for about 10 years. Iām working as a researcher in the Resource Assessment and Meteorology section at DTU Wind, where I am involved in the development of several Python-based open-source and commercial packages: WindKit, PyWAsP, PyWake, and more.
We use Python for most things and have benefited greatly from many of the open-source tools and communities in the Pythonsphere. This is especially true with the emergence of xarray and the development around it and the pangeo community.
I think itās really cool what David has started here and I canāt wait to start exchanging ideas/methods
Hi everyone,
Iām Laura Hume-Wright, working in scientific consultancy at Met Office in the UK. Iāve been a python user for only a few years so on the steep bit of the eternal learning curve. Python (and R) are central to a lot of what we do, and the Office supports various public libraries as it moves towards a more open-source structure.
Hi everyone, my name is Olivia Tomkins, I am working in the offshore wind yield team at Shell, based in the Netherlands. Iām afraid I am just a beginner at python, only beginning to make anything useful myself but very keen to try to get more experience and learn from communities such as this!
Thank you for setting this up!
Hi Iām Adam Ibrahim, I work at a startup developing a wind energy harvester out of Glasgow. I use python for wind resource assessments and find it really helpful. Having a forum I can come to with problems is really going to be helpful.
Iām Miguel Fernandes and work as a scientific programmer for the WindFarmer software in DNV based in Lisbon, Portugal. One of my goals is to help WindFarmer integrate in complex and custom workflows which typically means working with python, iām also looking forward to learning from the community. Thanks for the initiative.
Iām Giorgio Crasto, Iām currently on vacation but Iām supposed to start a new job related with WRA in September.
Iāve been coding mainly in Fortran, Matlab, C/C++, Python. My programs have been more focused on pre and post processing of CFD calculations, data mangement like time-series of measurements or assets values, download/upload of data, etc.
My experience in Python was of 1.5 years in a project for pattern recognition of electrical loads in households and classification of consumers/prosumers in a grid ⦠and ERA5 data grabbing.
Iām Yoshiaki Sakagami from Brazil and work as a professor of meteorology in a technical school here (IFSC). I use python in my classes as a tool for processing all meteorological data. My research is related to wind resource assessment and the boundary layer in wind farms (effects of turbulence, wind profile and atmospheric stability).
I think if we could develop in this space a type of tutorial, or guidelines or structure the contents as a short course it could be great. I will be glad to contribute to it.
I donāt have a full idea of what I suggested. Maybe, we can create a new topic here and ask for everyoneās suggestions. I was just thinking how all the contents could be better organized/categorized, so we can find them more easily.
Hi All,
Iām Oriol and Iāve been working in the wind resource field for 15 years. Iāve used many programming languages but nowadays python is becomming very very usefull and used due to it being so powerfull with many libraries and compatibility to typical met data. So hope this place will become very usefull and fully open source oriented.
Iām also hoping we can define a standar zarr files for WRA softwares.
See you!
Iām Neil Davis and I work at DTU Wind as the Technical Lead for Wind Resource Assessment Applications. In my group, we are working on the windkit and PyWAsP (Launching soon) packages, as well as the backend of the Global Wind Atlas, Global Atlas of Siting Parameters, and New European Wind Atlas. We also are working on a web front-end for CorRES.
We use XArray pretty extensively, as well as a lot of geospatial packages, like rioxarray, geopandas, shapely, and pyproj across all of our projects. For our web tools, we are using TiTiler a lot for serving the āslippy mapsā shown on the websites, and are using FastAPI for most of the API systems. We have also started switching from NetCDF and GeoTiff to Zarr for most of our datasets and seeing great gains in performance.
Thanks for those who took the initiative in putting this together, and I look forward to sharing and learning about the ways Python is used in this community.
These sound great Neil, that is all my favourite packages
I have been using TiTiler myself recently - actually for viewing the Global Wind Atlas data in my own āappā but more as a bit of a learning exercise for myself about how to view a large data set (Geotiff/COG) in a Plotly-DASH app.
I am in the process of writing a bit of a tutorial on this but you probably have a lot more experience on this. I will stick it up here when i am done, would be excellent to get your thoughts and some details on how you are running it for GWA & NEWA - i would be really interested in this.