All current limited submission opportunities can be viewed at research.psu.edu/limitedsubs.
The Office of the Vice President for Research announces the launch of the DE‐FOA‐0001956 DOE EERE: Machine Learning for Geothermal Energy competition. The internal submission deadline is Friday, August 3, 2018.
The U.S. Department of Energy’s Geothermal Technology Office (GTO) Machine Learning for Geothermal Energy funding opportunity announcement (FOA) supports projects that will develop new analytical tools for finding and developing geothermal resources and establish the practice of machine learning in geothermal operations. The rapidly advancing field of Machine Learning (ML) offers substantial opportunities for technology advancement and cost reduction throughout the geothermal project lifecycle, from resource exploration to power plant operations.
Under this funding opportunity, GTO is interested in two topic areas:
- Topic 1: Machine Learning for Geothermal Exploration – GTO seeks projects that advance geothermal exploration through the application of machine learning techniques to geological, geophysical, geochemical, borehole, and other relevant datasets. Of particular interest to GTO are projects that will identify data acquisition targets and build community datasets for future work.
- Topic 2: Advanced Analytics for Efficiency and Automation in Geothermal Operations – GTO seeks projects that apply advanced analytics to power plant and other operator datasets, with the goal of improving operations and resource management.
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