Machine Learning for Geothermal Energy | DE FOA 0001956

Opportunity Information: Apply for DE FOA 0001956

The Department of Energy (DOE), through its Geothermal Technology Office (GTO) and administered by the Golden Field Office, released a discretionary funding opportunity titled "Machine Learning for Geothermal Energy" (Funding Opportunity Number DE-FOA-0001956). The core aim is to accelerate geothermal resource discovery, development, and day-to-day operations by funding projects that create practical, new analytics and machine learning (ML) capabilities tailored to geothermal needs. The FOA is built around the idea that modern ML methods can reduce cost and risk across the entire geothermal project lifecycle, from early exploration decisions through power plant operations and long-term resource management, while also helping normalize the use of ML as a routine toolset within the geothermal industry.

The FOA is organized into two main technical topic areas. Topic 1, "Machine Learning for Geothermal Exploration," targets the earlier stages of geothermal development where uncertainty is high and data can be scattered or incomplete. DOE is looking for projects that apply ML to exploration-relevant datasets such as geological, geophysical, geochemical, borehole, and other related data streams. A notable emphasis in this topic is not just on building models, but on strengthening the underlying data ecosystem: applicants are encouraged to identify high-value data acquisition targets and to help develop community datasets that can be reused by others in future geothermal exploration work. In practical terms, this means proposals that improve how exploration data is compiled, labeled, integrated, and shared, and that use ML to extract actionable insights like prospect screening, resource characterization, and targeting decisions.

Topic 2, "Advanced Analytics for Efficiency and Automation in Geothermal Operations," focuses on improving performance once a geothermal resource is being produced or a facility is operating. DOE is seeking advanced analytics approaches that can be applied to power plant and other operator datasets to improve operational efficiency, reduce downtime, automate monitoring and decision-support tasks, and strengthen overall resource management. This topic is oriented toward real operational value: better forecasting, anomaly detection, optimization of plant parameters, maintenance planning, and improved management of reservoirs and production systems, all using data-driven methods that can be adopted by operators.

Funding under this FOA is expected to be awarded as cooperative agreements, which generally means DOE expects substantial involvement during the project (for example, technical coordination, milestone review, and active program management). The award ceiling listed is $700,000 per award, with an anticipated total of about 6 awards. Eligibility is described as unrestricted, meaning the opportunity is open to a broad range of applicant types, subject to any additional eligibility clarifications included in the full FOA text. The funding activity category is Energy, and the CFDA number provided is 81.087.

Key dates listed for this opportunity include a creation date of July 19, 2018. Concept papers were due on August 23, 2018 at 5:00 pm Eastern Time, and the original closing date for the FOA was November 1, 2018. Applications were required to be submitted through the EERE eXCHANGE portal (https://eere-exchange.energy.gov), which enforces hard submission deadlines by automatically disabling the Apply and Submit buttons at the deadline time. DOE directs applicants to consult the FOA materials on eXCHANGE, including the DE-FOA-0001956 Machine Learning FAQ Log, for official questions and answers and other submission guidance.

The announcement also spells out how DOE handles technical submission issues. If an applicant encounters problems before the deadline, they are expected to contact the eXCHANGE helpdesk (exchangehelp@hq.doe.gov) for assistance. If technical difficulties cause a late submission, the applicant must still contact the helpdesk, and DOE indicates it will only accept late applications when the issues were beyond the applicant's control, the applicant contacted the helpdesk for support, and the application is successfully submitted through eXCHANGE within 24 hours of the posted deadline. This policy is meant to keep deadlines consistent across all applicants while still allowing a narrow exception for documented, system-related failures.

• The Department of Energy, Golden Field Office in the energy sector is offering a public funding opportunity titled "Machine Learning for Geothermal Energy" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 81.087.
• This funding opportunity was created on Jul 19, 2018.
• Applicants must submit their applications by Nov 01, 2018 Concept Papers Due 08/23/2018, 5pm ET through EERE Exchange at https://eere-Exchange.energy.gov. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
• Each selected applicant is eligible to receive up to $700,000.00 in funding.
• The number of recipients for this funding is limited to 6 candidate(s).
• Eligible applicants include: Unrestricted (i.e., open to any type of entity above), subject to any clarification in text field entitled Additional Information on Eligibility.

Apply for DE FOA 0001956

[Watch] Creating a grant proposal using the step-by-step wizard inside the applicant portal: