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Commonwealth Fusion Systems (CFS) is working to risk-retire aspects of technologies related to Fusion Energy System (FES) blanket technology. CFS is actively investigating the molten salt LiF-BeF 2 (FLiBe), a novel blanket material, for fusion energy machines.
The Marpi Landfill (“Marpi” or “the landfill”), located on the northern end of the island of Saipan in the Commonwealth of the Northern Mariana Islands (CNMI), is powered by a single on-site diesel generator that only operates when the landfill is open and staffed. The project team, composed of representatives of the Department of Public Works and the Office of Planning and Development (OPD), aspires to provide the Marpi Landfill with 24-hour power availability despite its remote location to increase the use of sustainable energy and to ensure environmentally compliant landfill operations. This is consistent with the sustainable development goals documented in the 2021–2030 Comprehensive Sustainable Development Plan (OPD 2021), including Goal #12 (ensure environmentally compliant waste management facilities) and Goal #7 (renewable energy deployment). Further, the CNMI has a 20% target for renewable energy consumption by 2030, as documented in the 2021–2030 Comprehensive Sustainable Development Plan (OPD 2021) and the renewable portfolio standard (Public Law 18-62). To accomplish these goals, the Federal Emergency Management Agency, through its Interagency Reimbursable Work Agreement with the U.S. Department of Energy, funded a feasibility study and follow-up study in 2023–2024 to assess and prioritize power supply options for the landfill. This report combines the results from both feasibility studies.
ICE 2.0 Phase 2 Final Report In 2021, Berkeley Lab and Resource Innovations, Inc. launched the “ICE Calculator 2 Initiative” – a national study to refresh the underlying data and enhance the functionality of the ICE Calculator. The Initiative involves Berkeley Lab contracting with sponsoring utilities to administer identical, updated and comprehensive interruption cost surveys to statistically representative samples of each utility’s customers. Berkeley Lab and Resource Innovations then pool the survey results across the utilities and use them to update the analytical engines that drive the ICE Calculator. The ICE Calculator 2 Initiative is being conducted in phases. Each phase involves the administration of interruption cost surveys to the customers of sponsoring utilities, followed by an update to the ICE Calculator based on analysis of the pooled survey results. This report describes the activities and findings from Phase 1 and 2 of the ICE Calculator 2 Initiative. Phase 1 was sponsored by eight utilities: American Electric Power, Commonwealth Edison, Dominion Energy, Duke Energy, DTE Electric, Exelon, National Grid, and Puget Sound Energy. Phase 2 was sponsored by six utilities: Empire District Electric Company, Evergy Missouri, Pacific Gas & Electric, San Diego Gas & Electric, Southern California Edison, and Union Electric. Phase 1 and 2 involved 15 customer interruption cost survey activities representing a total of 30 electricity distribution service territories. ICE Calculator Version 2.0 and 2.2 Comparison This memorandum describes–at a high-level–the improvements in interruption cost estimates for the version 2.2 of the ICE Calculator (released February 2026) compared to version 2.0 (released in April 2025). Version 2.2 of the ICE Calculator corresponds to Phase 2 of the initiative, while version 2.0 corresponds to Phase 1. The improvements in version 2.2 result from both a significant increase in the number of customer responses that have been collected and the identification of seven additional factors that help estimate customer interruption costs.
The overarching motivation of this project is to provide stakeholder-engaged research and education to enable a clean, equitable, and resilient energy transition. Presently, low-income communities and people of color are disproportionately burdened by environmental harm, while also being routinely left out of planning processes and benefits from infrastructure improvements. The Energy Transition Institute (ETI) addresses these issues in three ways: community engagement, educating diverse future leaders, and cutting-edge research. As municipalities across the Commonwealth plan their transition to a climate-friendly energy system, research from ETI will advance technical and social understanding of heating electrification, energy storage, demand flexibility, reliability and resiliency of power distribution infrastructure, with attention to equity. This will benefit surrounding communities, cities and towns across Massachusetts, and the global research community
We are reporting on the modeling of fusion alpha particle transport in the planned ARC fusion device being designed by the CFS (Commonwealth Fusion Systems: https://cfs.energy). The ARC tokamak is designed to operate in a burning-plasma regime characterized by a substantial population of fusion-born alpha particles. Alfvén eigenmode (AE) stability is assessed both analytically and numerically, incorporating alpha-particle drive, ion Landau, and radiative damping from thermal species and collisional damping from trapped electrons. Regions of unstable and near-threshold AE activity are mapped across ARC’s operational parameter space. Linear stability analysis with NOVA indicates multiple, often marginally unstable AEs, extending to toroidal mode numbers up to n= 30. The present report focuses on the ARC flat-top operating point prior to the sawtooth event. Alpha-particle transport on timescales exceeding the neoclassical slowing-down time is assessed using the NUBEAM module [1][2] of the TRANSP code [3], employing transport coefficients derived from the RBQ quasilinear modeling (cf. Appendix B). These global simulations identify favorable and unfavorable operating regimes with respect to alpha confinement, pressure redistribution, and overall alpha-heating efficiency. We also evaluate additional transport mechanisms—including neoclassical tearing mode (TM)–induced stochasticity, sawtooth-driven redistribution, and toroidal-field ripple using the kick model (cf. Appendix C) which makes use of the guiding-center code ORBIT, see Section 5. The kick model is integrated into TRANSP to enable self-consistent predictions of alpha-driven current formation and sustainment within the ARC scenario. Sensitivity scans are performed over the mode frequency, rational-surface alignment, island width, mode amplitude, and proximity of the limiter to the plasma. Our study provides an initial, physics-based guidance for machine design, operational planning, and equilibrium control, ensuring adequate alpha confinement and robust self-heating performance in ARC. Our simulations mostly targeted worst case scenarios, e.g. for TMs and sawteeth. Overall, we expect benign effects for the ARC scenario investigated in this work on fusion alpha confinement and losses in the presence of AEs, tearing modes and sawteeth. This report addresses three thrusts identified at the outset. The first thrust focuses on analytic estimates of the parametric dependencies of EP relaxation based on local AE stability simulations (Section 3). The second thrust involves global evaluations of AE stability using the NOVA, RBQ, and NUBEAM codes (Section 4). Finally, we investigate alpha-particle transport driven by low-frequency instabilities associated with sawteeth and tearing modes (Section 5).
This report summarizes the U.S. DOE and national laboratories equity summit that was held on February 5, 2024, and focused on grid planning and operations. The objectives of the summit were to connect DOE and lab researchers working on grid-related equity issues, share information on current and planned grid-related equity projects and initiatives, and inspire and educate participants by hearing from our panelists about solutions and challenges to integrating equity in grid planning and operations. The summit included two panels of industry leaders. The first was a state and community perspectives panel that included representatives from a state public utility commission (Oregon Public Utility Commission), a state energy office (Washington Department of Commerce), a state utility consumer advocate (Connecticut Consumer Counsel), and industry consultants (Elevated Engagement and ArkSpring Consulting). Panelists shared successes they have seen, critical challenges related to equity and grid planning and operations, and other considerations. The second panel addressed utility perspectives and included representatives from two utilities (Commonwealth Edison and Tacoma Power), the National Rural Electric Cooperative (NRECA), and a former utility employee and legal consultant. Panelists discussed the role of the utility concerning equity, the most significant technical and data modeling needs and opportunities, and the role the labs could help advance equity in grid planning and operations. There was also a session on partner organization presentations. Argonne National Laboratory made a short presentation on the Grid Modernization Laboratory Consortium (GMLC) project they are leading on equity-informed power system planning. NARUC, NASEO, and the Clean Energy States Alliance, as partners of the GMLC project also shared updates on relevant activities and resources. During the summit, there were two rounds of lightning presentations by national labs and DOE highlighting research that addresses equity and grid planning and operations (Tables 5 and 6 and slides in the Appendix). The goal of the lightning rounds was to share information between participants to encourage collaboration and leverage ongoing research at labs and DOE. The summit included two interactive exercises where summit participants shared their perspectives on relevant equity projects and initiatives (Table 2), key challenges regarding equity and grid planning and operations (Table 3), and promising innovations or progress (Table 4). At the end of the session, participants were asked to share essential insights from the event (Table 7) and an action they plan to take as a result of the event. Participants agreed that the event was useful in helping them share and learn from each other. The project team plans to use the information from the summit as a starting point to help inform future research and technical assistance. In 2026, another Equity Summit will be held (virtually or in person) as part of the same project to help raise awareness and disseminate research and resources completed during the project's duration.
Mineral mapping from satellite images provides valuable insights into subsurface mineral alteration for geothermal exploration. In previous studies, eight fundamental algorithms were used for mineral mapping utilizing USGS spectra, a collection of reflectance spectra containing samples of minerals, rocks, and soils created by the USGS. We used an ASD FieldSpec 4 Hi-RES NG portable spectrometer to collect spectra for analyzing ASTER images of the Coso Geothermal Field. Then, we established the ground-truth information and the spectral library by analyzing 97 samples. Samples collected from the field were analyzed using the CSIRO TSG (The Spectral Geologist of the Commonwealth Scientific and Industrial Research Organization). Based on the mineralogy study, multiple high-purity spectra of geothermal alteration minerals were selected from collected data, including alunite, chalcedony, hematite, kaolinite, and opal. Eight mineral spectral target detection algorithms were applied to the preprocessed satellite data with a proposed local spectral library. We measured the highest overall accuracy of 87% for alunite, 95% for opal, 83% for chalcedony, 60% for hematite, and 96% for kaolinite out of these eight algorithms. Three, four, five, and eight algorithms were fused to extract mineral alteration with the obtained target detection results. The results prove that the fusion of algorithms gives better results than using individual ones. In conclusion, this paper discusses the significance of evaluating different mapping algorithms. It proposes a robust fusion approach to extract mineral maps as an indicator for geothermal exploration.
When utilizing these data from Kennaook Cape Grim please acknowledge the Australian Bureau of Meteorology and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) for their long-term and continued support of the Kennaook Cape Grim Baseline Air Pollution Monitoring Station. In addition, please contact the Lead Scientists responsible for the collection of these data sets (melita.keywood@csiro.au, ruhi.humphries@csiro.au and Erin.dunne@csiro.au) to discuss collaboration and authorship opportunities.
When utilizing these data from Kennaook Cape Grim please acknowledge the Australian Bureau of Meteorology and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) for their long-term and continued support of the Kennaook Cape Grim Baseline Air Pollution Monitoring Station. In addition, please contact the Lead Scientists responsible for the collection of these data sets (melita.keywood@csiro.au, ruhi.humphries@csiro.au and Erin.dunne@csiro.au) to discuss collaboration and authorship opportunities.
When utilizing these data from Kennaook Cape Grim please acknowledge the Australian Bureau of Meteorology and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) for their long-term and continued support of the Kennaook Cape Grim Baseline Air Pollution Monitoring Station. In addition, please contact the Lead Scientists responsible for the collection of these data sets (stuart.baly@bom.gov.au, melita.keywood@csiro.au, ruhi.humphries@csiro.au and Erin.dunne@csiro.au) to discuss collaboration and authorship opportunities.
When utilizing these data from Kennaook Cape Grim please acknowledge the Australian Bureau of Meteorology and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) for their long-term and continued support of the Kennaook Cape Grim Baseline Air Pollution Monitoring Station. In addition, please contact the Lead Scientists responsible for the collection of these data sets (melita.keywood@csiro.au, ruhi.humphries@csiro.au and Erin.dunne@csiro.au) to discuss collaboration and authorship opportunities.
This profile provides a snapshot of the energy landscape of the Commonwealth of Puerto Rico - a U.S. territory located about 60 miles east of the Dominican Republic and directly west of the U.S. Virgin Islands.
This profile provides a snapshot of the energy landscape of the Commonwealth of Dominica, an island nation located southeast of Guadeloupe and northwest of Martinique in the Lesser Antilles.
The State Energy Program (SEP) Operations Manual is a reference tool for the SEP network of states and program officials within the U.S. Department of Energy. "States," when referred to in the manual, includes the 50 states, the District of Columbia, and the U.S. territories: American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, Puerto Rico, and the U.S. Virgin Islands. This manual contains information needed to administer the State Energy Program.
This report provides the outcome of the International Symposium on Clusters and Nanomaterials (ISCAN2019) held at the historic Jefferson hotel in Richmond, Virginia from November 3rd to 7th, 2019. This quadrennial symposium, founded in 1982, was hosted by Virginia Commonwealth University (VCU) and supported by VCU, the Office of Basic Energy Sciences of the Department of Energy, and Army Research Office. The ACS Energy Letters provided for three poster awards. ISCAN2019 focused on the roles that clusters and nanomaterials play in addressing the outstanding challenges and opportunities in clean and sustainable energy and medicine, two of the most important problems facing science and society.
The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify if the software is reliable (or unreliable) while still leveraging the strength of the existing methods.
The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify software reliability (or unreliability) while still leveraging the strength of the existing methods.
Since 2019, the National Renewable Energy Laboratory (NREL) and Elevate have collaborated to identify pathways to deep energy retrofits in Chicago's housing stock, document equity implications and co-benefits of this transition, and validate the findings by implementing retrofits in real Chicago homes. This document summarizes our analysis process to model advanced retrofit packages that lead to greater than 50% energy savings in Chicago homes. Based on these findings, we have also developed a roadmap with the City to guide implementation, and are deploying the recommended retrofit packages in real Chicago homes to realize these energy savings. This work was developed in collaboration with two key stakeholders - the City of Chicago and Commonwealth Edison (ComEd) - and funded by the U.S. Department of Energy (DOE). NREL's Residential Buildings team maintains the best-in-class ResStock™ energy model of the U.S. residential building stock. For this work, we calibrated ResStock to Chicago's unique local housing stock to accurately simulate energy use in Chicago homes both for current conditions and with various retrofit scenarios. We simulated a wide range of potential building retrofits covering all aspects of residential energy use and then grouped these into packages based on energy and utility bill savings. ResStock can model diverse building types and housing characteristics, so we're able to observe the range of outcomes that might occur when these upgrades are deployed across the entire housing stock. We can then estimate potential energy savings from an advanced retrofit program on Chicago's housing stock by comparing the modeled energy use before versus after a retrofit. This novel version of ResStock, calibrated to Chicago with data from Elevate, can help City officials, ComEd, and other partners plan for community-scale decarbonization via residential retrofits. Specifically, this work contributes the following project goals: Develop a building retrofit prioritization strategy for Chicago single-family and 2- to 4-unit buildings; Identify neighborhoods and home types that have the highest potential for savings from electrification; and Assess the impact of advanced building retrofits on energy use, utility bills, and CO2 emissions at the city and building level. Although this study is specific to Chicago, its methods and learnings are applicable across the United States. These findings are especially notable for heat pumps and electrification retrofits in cold climates.