Though federal agencies make high quality data on the U.S. energy system publicly available, the data is often shared in hard-to-use formats that cannot easily be linked with other data or incorporated into the state-of-the-art computational models often used by researchers.  The effort needed to prepare such data for academic analysis is a barrier to use in the energy systems research. The Catalyst Cooperative is a team of data scientists, led by Christina Gosnell, who are dedicated to making unwieldy energy datasets easily accessible for researchers.  Over the next two years, Catalyst Cooperative researchers plan to curate nine new energy-related datasets into their open source data library, including data on electricity generation, natural gas utilities, pipeline safety, electricity market contracts, and greenhouse gas emissions.  Grant funds also support efforts to make needed improvements to their platform to accommodate growth and improve user experience, to help researchers work with this data library, and to perform analysis related to a variety of important energy issues, including planned research on the thermal efficiencies and environmental attributes of power plants. The Boulder Housing Collective acts as the fiscal sponsor for Catalyst Cooperative.

This grant funds a study by scholars at the University of Maryland, College Park and the University of Wisconsin, Madison that will examine the impact of corporate venture capital investments on advancing innovation related to low-carbon and greenhouse gas mitigation technologies. Analyzing a comprehensive dataset of corporate investment in clean energy technology, the i3 Cleantech database, the research team will look at how venture capital investments affect the cost and performance of such technologies. In addition, the analysis will include detailed studies of investment in particular clean energy sectors, including energy storage, transportation, and precision agriculture aimed at capturing carbon dioxide gas from the atmosphere. Data will also be used to improve the representation of private investment in GCAM, an open source model linking climate change, energy systems, and socioeconomic factors.

There are more than 150 academic research centers located at universities across the United States exploring different dimensions of the energy system, all with different topic areas of focus, disciplinary emphases, and level of funding.  Funds from this grant support the creation of a collaboration network, the University Energy Institute Collaborative (UEIC), that will facilitate coordination among these academic research institutes, foster the exchange of ideas, and promote collaborative research. Grant funds will cover the costs of running the network’s subcommittees and communication activities, develop a web portal for members, and planning and holding two annual summits that will bring together center representatives in person. Funds will also go toward the design of a small, seed grant program that would support cross-institutional collaborative projects among UEIC members.

Climate change is already affecting how energy systems function, with higher temperatures and more intense storms making energy systems more vulnerable overall, leading to a rise in the number of power outages in recent decades. This is evident in numerous recent events, from hurricanes destroying power generation systems in Puerto Rico to California wildfires disrupting transmission lines to the February 2021 Texas blackout caused by extreme cold. This grant funds a multi-institutional research effort led by the Houston Advanced Research Center (HARC), in partnership with researchers at the University of Houston and Lehigh University, to begin advancing our understanding of how extreme weather events might impact the U.S. energy system. It will examine ERCOT, the Texas electricity grid, and researchers on this project will create an integrated modeling framework, called Pythias, that links together components of five separate models covering separate aspects of energy and climate systems: a power grid management model, a regional climate model, a regional water use and hydrology model, the open source GCAM model that links energy and climate change to socioeconomic factors, and an agent-based decision model to help game out how planners and other stakeholders might respond to changes in energy systems. The team will then use Pythias to model how ERCOT grid might respond to various plausible climate scenarios that could arise in the future.