Thank you for signing up to receive updates on the Open Energy Outlook (OEO) project, which is examining energy technology and policy pathways to achieve deep decarbonization in the United States using open source tools and data.
We've been working hard with the continued goal of issuing our first report in Spring 2022. We wanted to provide a few updates on the modeling effort.
Tools for Energy Model Optimization and Analysis (Temoa) is being used to perform the energy systems analysis. With regard to our open source, Temoa-compatible input database, our representation of the electric, residential, commercial, and transportation sectors is largely complete. These sectors are documented in jupyter notebooks, which are available in our GitHub repo. They can be rendered online by clicking the Launch MyBinder badge at the top of the README file and then navigating to the database_documentation folder. (Note that mybinder takes several minutes to load.)
We're currently working to complete the industrial and fuel supply representations. The industrial sector team has developed an energy supply-demand balance across a range of industrial subsectors, and we're now working to populate the database with specific technologies. In fuel supply, we have a representation of crude oil supply, and are working to update our representation of natural gas, coal, and biomass. We hope to have both sectors complete by the end of the year.
Given the key role of variable renewables and storage under low or net-zero emissions scenarios, high temporal resolution is a critical model feature in order to properly capture dispatch issues. We've been investigating the tradeoff between temporal resolution and computational performance. After tuning the code and solver, we can now myopically solve (i.e., one time period at a time) the current version of the 9-region database with 24-representative days (~15 hours of wall clock time), and can easily solve an electric-only version of the database with 48 representative days (~4 hours wall clock time). We've been doing runs on an old-ish computer cluster, and are planning to do further performance testing through the Pittsburgh Supercomputing Center.
Online Resources and Outreach
Our project website (openenergyoutlook.org) contains general information about the project. The website also includes a blog that we plan to use to communicate about specific modeling issues. Our GitHub repo contains much of the dynamic content, including all of the input data. The README file on GitHub provides a walk-through of the repo contents. We’re also starting to use twitter to communicate more frequent updates on the project via our handle @oeo_energy. If you’d like to provide feedback, please send an email to openenergyoutlook@....
We hope that the open source model and input database can help others perform their own analysis. We also welcome feedback and contributions from the broader community! Please get in touch with us directly or submit an issue in our Github repository. In order to acknowledge and track community contributions, we have this acknowledgements document in the GitHub repo.
That's all for now. We know you receive a lot of email, so we’ll be communicating less frequent, more substantive updates.