Project Background¶
The project grew out of frustration with how difficult it is to make use of public data about the US electricity system. In our own climate activism and policy work we found that many non-profit organizations, academic researchers, grassroots climate activists, energy journalists, smaller businesses, and even members of the public sector were scraping together the same data repeatedly, for one campaign or project at a time, without accumulating shared, reusable resources. We decided to try and create a platform that would serve the many folks who have a stake in our electricity and climate policies, but may not have the financial resources to obtain commercially integrated data.
Our energy systems affect everyone, and they are changing rapidly. We hope this shared resource will improve the efficiency, quality, accessibility and transparency of research & analysis related to US energy systems.
These ideas have been explored in more depth in papers from Stefan Pfenninger at ETH Zürich and some of the other organizers of the European Open Energy Modeling Initiative and Open Power System Data project.
Reading¶
The importance of open data and software: Is energy research lagging behind? (Energy Policy, 2017) Open community modeling frameworks have become common in many scientific disciplines, but not yet in energy. Why is that, and what are the consequences?
Opening the black box of energy modeling: Strategies and lessons learned (Energy Strategy Reviews, 2018). A closer look at the benefits available from using shared, open energy system models, including less duplicated effort, more transparency, and better research reproducibility.
Open Power System Data: Frictionless Data for Open Power System Modeling (Applied Energy, 2019). An explanation of the motivation and process behind the European OPSD project, which is analogous to our PUDL project, also making use of Frictionless Data Packages.
Open Data for Electricity Modeling (BWMi, 2018). A white paper exploring the legal and technical issues surrounding the use of public data for academic energy system modeling. Primarily focused on the EU, but more generally applicable. Based on a BWMi hosted workshop Catalyst took part in during September, 2018.
We also want to bring best practices from the world of software engineering and data science to energy research and advocacy communities. These papers by Greg Wilson and some of the other organizers of the Software and Data Carpentries are good accessible introductions, aimed primarily at an academic audience:
Best practices for scientific computing (PLOS Biology, 2014)
Good enough practices in scientific computing (PLOS Computational Biology, 2017)