Request for Proposals: Artificial Intelligence Infrastructure and Energy Generation on DOE Land at Savannah River Site
ID: RFP-AI-1Type: Solicitation
Overview

Buyer

ENERGY, DEPARTMENT OFENERGY, DEPARTMENT OFNNSA NON-MO CNTRCTNG OPS DIVALBUQUERQUE, NM, 87185, USA

NAICS

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (51821)

PSC

LEASE/RENTAL OF UNIMPROVED REAL PROPERTY (LAND) (X1PC)

Set Aside

No Set aside used (NONE)

Original Source

https://sam.gov/workspace/contract/opp/d953c4c0404549149be029dfa8518b15/view
Timeline
    Description

    The Department of Energy (DOE) is issuing a Request for Proposals (RFP) for a long-term lease of land at the Savannah River Site (SRS) in Aiken, South Carolina, aimed at developing Artificial Intelligence (AI) data centers and energy generation infrastructure. The initiative seeks proposals for integrated projects that include both AI data centers and energy generation, with a focus on innovative energy solutions and rapid development to enhance U.S. leadership in AI and energy sectors. This opportunity is critical for supporting economic competitiveness and national security, as selected entities will be responsible for all aspects of development, including environmental compliance and financial obligations. Interested parties can contact Jeff Hynds at NNSA_AI_Infrastructure@srs.gov for further information, with proposals due by the specified deadline.

    Point(s) of Contact
    Jeff Hynds
    NNSA_AI_Infrastructure@srs.gov
    Files
    Title
    Posted
    Appendix D - Offeror Cover Page .docx
    The provided document is a cover page for a Request for Proposals (RFP) titled "Artificial Intelligence Infrastructure and Energy Generation on DOE Land." This cover page serves as a template for offerors to submit their company information when responding to the RFP. It requires details such as the company name, point of contact, address, telephone, fax, email, and website. Additionally, it mandates the printed name, title, signature, and date of an authorized representative and signatory for the offeror. The document's purpose is to standardize the submission of essential administrative information from companies interested in proposing solutions related to AI infrastructure and energy generation on Department of Energy (DOE) land.
    Appendix E - Past Performance Reference Information Form.docx
    The "Artificial Intelligence Infrastructure and Energy Generation on DOE Land Request for Proposals" outlines a comprehensive Past Performance Reference Information Form. This form requires offerors to provide detailed information about past projects, including client contact, project location, energy generation type, land usage, nameplate capacity, project timeline, and a thorough description of design, construction, management, and operation. Financial aspects such as project financing, cost, and off-take agreements are also requested. Offerors must specify their role and activities, discuss work complexity, and provide safety performance statistics, including OSHA DART and TRC rates. The document emphasizes consistency of information across the proposal and allows for format amendments in the appendix if specific guidelines are followed.
    FINAL AI and Energy Infrastructure on SRS RFP (v04)_DOE.pdf
    The Department of Energy (DOE) is issuing a Request for Proposals (RFP) for the long-term lease of land at the Savannah River Site in Aiken, SC, to develop Artificial Intelligence (AI) data centers and energy generation infrastructure. This initiative aims to enhance U.S. leadership in AI and energy, supporting economic competitiveness and national security. Proposals can be for integrated AI data center and energy projects, phased projects, or energy infrastructure projects, all requiring new energy generation. The DOE seeks rapid development, innovative energy solutions, and collaboration opportunities. The property is offered "as-is/where-is," with selected entities responsible for all development, environmental compliance (including NEPA and NHPA), permitting, and financial obligations. Eligible offerors must be U.S.-organized, majority domestically-owned, and undergo foreign influence risk reviews.
    SRNL-L4300-2011-00011 (FINAL).pdf
    This document outlines a hypothetical site selection process for a small modular reactor using the Site Selection Modeling System (SSMS) program, detailed in a memo from Nancy Halverson to Jack Mayer. It describes the assumptions made for criteria, weighting, and scoring in Test #27, emphasizing that the results are hypothetical and for demonstration purposes only. The criteria for NuScale's reactor included 20 acres, above a 100-year floodplain, seismic stability, an 85-foot excavation depth, 4 million gallons per day (MGD) water requirement, and proximity to transmission lines, roads, rails, domestic water, and sanitary sewer systems. Exclusions encompassed buffered floodplains, threatened and endangered species areas, eagle nests, setasides, woodpecker nests/tracts, wetlands, waste sites, fault lines, and sinkholes. Weighting categories included minimizing ecology impact (15%), human health impact (25%—not factored in this test), favorable geoscience characteristics (25%), and favorable engineering characteristics (35%). Individual criteria scores for distances from various GIS features (e.g., wetlands, fault lines, power lines) and depth to groundwater were also detailed. The document notes that groundwater contamination plumes were not yet in the program, and high-scoring sites intersecting existing plumes could be removed manually. The report concludes by explaining how the SSMS identified top-scoring sites, including an anomaly where large, high-scoring areas were split between grid locations.
    SRS AI and Energy Infrastructure Sites KML file.docx
    The document instructs users on accessing a .kml (Keyhole Markup Language) file containing the coordinates for ten sites. Users must double-click an icon to launch the file, requiring compatible software on their computer to open it. Once opened, the file can be saved locally. This information is crucial for government RFPs, federal grants, and state/local RFPs that involve geographical data or site-specific project planning, ensuring all parties can access and utilize the provided location details.
    SRS AI Energy RFP QA Part 1.docx
    The AI and Energy Infrastructure FAQ (Revision 2) addresses key questions regarding proposals for data centers and energy generation on the Savannah River Site (SRS). It clarifies that while data center and energy consortiums can apply separately, proposals without power generation will not be considered, requiring clear linkages and timelines for integration. The document also details considerations for land lease fees, decommissioning bonds, and water withdrawal limits, noting that offerors must substantiate proposed lease rates and cover appraisal costs. It specifies water allocation among tenants, power sources for river water pumps, and guidelines for road alterations within the site. Additionally, the FAQ outlines requirements for interconnection information, interim power from the grid, and coordination between data center and SMR deployment timelines. Security clearances are not required for working at offeror facilities but specific badging and access protocols are enforced for site entry. Submission formatting guidelines are also provided, including acceptable font styles, sizes for tables and graphics, and inclusion of front matter in proposals.
    Similar Opportunities
    COMMERCIAL AI & ENERGY GENERATION INFRASTRUCTURE PROGRAM REQUEST FOR OFFER
    Buyer not available
    The Department of Energy (DOE) is soliciting proposals through a Request for Offer (RFO) for the Commercial AI & Energy Generation Infrastructure Program, aimed at leasing portions of the former Paducah Gaseous Diffusion Plant cleanup site in Western Kentucky. This initiative seeks to develop integrated AI data centers and energy generation infrastructure, encouraging innovative energy technologies, particularly nuclear and geothermal, while aligning with national priorities in AI and energy leadership. Interested parties are invited to participate in an industry day on December 18, 2025, to discuss the RFO and tour the site, with registration required by December 12, 2025. For further inquiries, contact Marcia D. Fultz at marcia.fultz@pppo.gov or call 859-219-4044.
    Partnerships for Transformational Artificial Intelligence Models
    Buyer not available
    The Department of Energy (DOE) is seeking input through a Request for Information (RFI) to establish a public-private consortium aimed at developing transformational artificial intelligence (AI) models for scientific applications. This initiative, mandated by Public Law 119-21, focuses on curating scientific data from the National Laboratories to create self-improving AI models that will enhance scientific discovery, energy solutions, and national security. The DOE invites participation from a diverse range of institutions, including businesses, think tanks, and research organizations, to collaborate on leveraging DOE data and expertise, with responses due by January 14, 2026. Interested parties should submit their responses electronically to AICommunityInput@science.doe.gov, including "Transformational Artificial Intelligence Models" in the subject line.
    Transformational AI Capabilities for National Security
    Buyer not available
    The Department of Energy's National Nuclear Security Administration (NNSA) is seeking information on Transformational Artificial Intelligence (AI) Capabilities for National Security through a Request for Information (RFI). This initiative aims to integrate advanced AI technologies into NNSA's nuclear weapons development and nonproliferation missions, enhancing operational efficiency and addressing evolving global threats. The RFI invites responses from a diverse range of entities, including businesses, research organizations, and universities, to gather insights on capabilities related to classified AI development, data curation, and partnership models. Interested parties must submit their responses by January 23, 2026, at 12:00 PM MST, and can direct inquiries to Clinton Rohloff or Stephanie M. Vigil via the provided contact information.
    Notice of Intent to Issue a Funding Opportunity from U.S. Department of Energy’s (DOE) High Performance Computing for Energy Innovation (HPC4EI) Initiative
    Buyer not available
    The U.S. Department of Energy (DOE) is set to issue a new solicitation under its High Performance Computing for Energy Innovation (HPC4EI) initiative, specifically targeting the High-Performance Computing for Manufacturing (HPC4Mfg) program. This initiative aims to provide U.S. manufacturers with access to DOE National Laboratory expertise and advanced supercomputing resources to tackle complex challenges in energy and materials, thereby enhancing efficiency, reducing costs, and strengthening supply chain resilience. Eligible participants include entities that manufacture or operate in the U.S. for commercial applications, as well as organizations that support these entities, with selected projects potentially receiving up to $400,000 in funding, contingent upon a minimum 20% cost share from industry partners. For further inquiries, interested parties can contact Aaron Fisher at fisher47@llnl.gov or by phone at 925-422-3950.
    Open Source Software: Unlocking Operational Efficiency in Nuclear Power Plants with DIAMOND
    Buyer not available
    The Department of Energy is seeking innovative solutions to enhance operational efficiency in nuclear power plants through the deployment of the DIAMOND software. This initiative aims to address the challenges of fragmented data management within the nuclear industry by integrating disparate data sources into a cohesive data warehouse, thereby facilitating advanced analytics and machine learning applications. The DIAMOND software introduces an ontology-based data model tailored for the nuclear domain, which streamlines data integration, reduces operational costs, and improves decision-making processes. Interested parties can contact Andrew Rankin at andrew.rankin@inl.gov for further information regarding this opportunity.
    OPEN-SOURCE SOFTWARE LICENSING OPPORTUNITY RAVEN: Comprehensive Uncertainty Quantification and Optimization for Complex Systems
    Buyer not available
    The Department of Energy, specifically the Battelle Energy Alliance at the Idaho National Laboratory (INL), is offering an open-source software licensing opportunity for RAVEN, a comprehensive framework designed for uncertainty quantification and optimization in complex systems. This initiative aims to provide access to advanced analytical tools that integrate statistical, data analysis, and AI techniques, particularly for applications in nuclear power plants and other complex environments. RAVEN, developed under the Light Water Reactor Sustainability program, is essential for modern risk evaluation and supports various analysis methods, including regression and data mining, while facilitating integration with third-party software. Interested parties can access the software at https://github.com/idaholab/raven and are encouraged to contact Andrew Rankin at andrew.rankin@inl.gov for further discussions on licensing opportunities and collaboration.
    INL Innovation Spotlight Cyber Resilient Trade-off Evaluation (CyRTE): Pioneering Strategy for Operational Technology Security
    Buyer not available
    The Department of Energy, through the Battelle Energy Alliance, is seeking innovative solutions for the Cyber Resilient Trade-off Evaluation (CyRTE), aimed at enhancing the security of Operational Technologies (OT) against cyber threats. This initiative focuses on developing a resilience-informed, AI-driven methodology to assess the impact of cybersecurity measures on the operational integrity of critical infrastructure systems, such as utilities and manufacturing. The CyRTE approach includes the creation of a unique "buzzer" tool for testing cyber-physical interactions and the use of digital twins for systemic evaluations, ensuring that cybersecurity implementations do not compromise system functionality. Interested parties can reach out to Andrew Rankin at andrew.rankin@inl.gov for further engagement and to explore potential licensing opportunities related to this technology.
    Grid Research Innovation and Development Center Technology Collaborations for US Power Electronics Industries
    Buyer not available
    The Department of Energy, through the Oak Ridge National Laboratory (ORNL), is inviting industry partners to engage in short-term collaborative projects aimed at advancing grid-integrated power electronics technologies under the Grid Research Innovation and Development Center (GRID-C). Participants are required to submit cost-shared proposals focusing on specific technology areas such as materials, embedded controllers, and grid architectures, with a mandatory 20% cost-share from industry participants. This initiative is crucial for enhancing the development and deployment of innovative, energy-efficient technologies for grid modernization, ultimately promoting U.S. competitiveness in clean energy and job creation. Interested parties should submit proposals electronically to GRIDCcollaborations@ornl.gov, with ongoing selection based on the availability of funding from the Department of Energy’s Transformer Resilience and Advanced Components Program.
    Open-Source Software: Unlocking Economic Insights into Nuclear-Renewable Integrated Energy Systems with HYBRID
    Buyer not available
    The Department of Energy is seeking to enhance economic insights into Nuclear-Renewable Integrated Energy Systems (N-R IES) through the open-source software known as HYBRID, developed by the Battelle Energy Alliance at the Idaho National Laboratory. The objective is to utilize the HYBRID simulation framework, which integrates stochastic analysis, probabilistic optimization, and high-fidelity physical modeling, to accurately assess the economic viability of N-R IES under varying conditions. This initiative is crucial for addressing the challenges posed by the integration of renewable energy sources into the electric grid, enabling better capacity planning and dispatch optimization for energy providers, as well as supporting academic research and policy decision-making. Interested parties can reach out to Andrew Rankin at andrew.rankin@inl.gov for further information, and the software is available for free download on its GitHub page.
    Expression of Interest - Commercial Extraction of Nickel from Radiologically Contaminated Nickel Ingots
    Buyer not available
    The Department of Energy (DOE) is seeking industry input through an Expression of Interest (EOI) for the commercial extraction of approximately 9,700 tons of radiologically contaminated nickel ingots stored at the Paducah Gaseous Diffusion Plant in Kentucky. The objective is to identify operationally mature technologies capable of selectively recovering high-purity elemental nickel from these ingots, which are contaminated with uranium, technetium, and other actinides, to support the National Energy framework and initiatives related to Artificial Intelligence (AI). Interested parties must submit a technical package detailing their process design and safety measures, as well as an economic/market package outlining financial viability, with both submissions due 90 days after the EOI issue date. For further information, contact Jennifer Stokes at EOI@pppo.gov.