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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Dartmouth College |
| Country | United States |
| Start Date | Dec 01, 2024 |
| End Date | Nov 30, 2025 |
| Duration | 364 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2445015 |
The broader impact of this I-Corps project is the development of a software platform for building project developers in the clean energy or clean technology space. Project developers are in charge of planning a project, securing the necessary resources and supply chains, then executing the project's construction. Project developers must understand complex factors related to proposals such as social acceptance to visible infrastructure, environmental impact, geographical constraints, regulatory environments, supply chains, and financial performance estimates in order to deploy capital, making the site selection process a pain point in their workflow.
Clean energy companies would benefit from software that reduces their burden in finding optimal project sites, accelerating project deployment, and driving down development costs. This software includes optimizing future energy capacity under different decarbonization scenarios, comparing the future capacity with existing capacity to determine the degree of growth and demand which remains unsatisfied, and characterizing the expected profitability at each site using data from past energy projects.
This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a software platform to assist decision-makers in siting projects. The platform combines multiple model topologies to assess the financial and technical viability of deploying infrastructure in different geographies.
First, an open-source energy systems model, the National Renewable Energy Laboratory Regional Energy Deployment System (NREL REDS), is used to project future energy system supply and demand across the United States. This projection is done at the balancing authority spatial resolution, or 134 spatial regions across the lower 48 states. The platform then identifies high-potential zones using the NREL REDS, where current deployment is lower than what projections or current demand needs.
The platform supports companies in selecting cost-optimal locations for siting their infrastructure. This selection decision includes consideration of constraints of regulatory, geographical, or social barriers to deployment, as well as possible tax credits at the state and federal level.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Dartmouth College
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