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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Biomass Harmonization and SAR Analysis with the Multi-mission Algorithm and Analysis Platform (MAAP)

The Multi‐mission Algorithm and Analysis Platform (MAAP) is a collaborative effort between NASA and the European Space Agency (ESA) to support above ground biomass (AGB) research in an open science framework. MAAP brings together relevant data, algorithms, and computing capabilities in a common cloud environment to address the challenges of sharing and processing data from field, airborne and satellite measurements. MAAP was publicly released in October 2021, providing computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of data. MAAP has allowed scientists from both North America and Europe to collaborate on the generation and analysis/visualization of data derived from multiple, discipline-adjacent missions in an open, collaborative environment that has reached beyond traditional scientific investigation. MAAP has been used to support multiple scientific activities. To date, existing LiDAR data from multiple platforms has been calibrated with field measurements and combined for more comprehensive and accurate estimates of above ground biomass AGB; these LiDAR platforms include airborne (e.g. LVIS), the International Space Station (NASA’s Global Ecosystem Dynamics Investigation (GEDI), and satellites (e.g. ICESat-2). The current challenge is to effectively and seamlessly combine the aforementioned LiDAR-based data with new data sources such as P-band RADAR from ESA’s upcoming BIOMASS mission, existing ESA Sentinel-1 C-band SAR, and the 30 PB/yr of high cadence global coverage L-band SAR data from the upcoming NASA-ISRO SAR (NISAR) mission. Recent analysis using MAAP merged ICESat-2 and optical data (Harmonized Landsat Sentinel) produced the most comprehensively precise estimate of boreal-wide AGB to date. Another effort using MAAP is the production and open distribution of global comparisons of AGB map estimates, including from ICESat-2 and GEDI, to bolster stakeholder uptake for policy applications. These map estimates will feed into the Intergovernmental Panel on Climate Change (IPCC) database, likely aiding the next Global Carbon Stocktake of the UNFCCC. Furthermore, the biomass retrieval intercomparison exercise BRIX-2 could benefit from the MAAP providing standardized test cases (based on airborne campaign and spaceborne data) allowing the community to develop and apply retrieval algorithms based on these test cases, while forthcoming SAR data training curricula could also use the MAAP as a teaching and learning platform. The MAAP is meeting the challenges inherent in international, open science collaboration and large scale computing with a platform that is entirely open source and cloud native, using open standards for data access, manipulation, protocols, and formats. The MAAP data system consists of a dedicated data store whose data is indexed in an online catalog conforming to established metadata, application programmatic interfaces (APIs), and service interface standards, using an implementation of the open sourced NASA Common Metadata Repository. Federation of user identities allows users from either NASA or ESA to access and consume services from the other using a unified metadata catalog for the data utilized across the ESA and NASA MAAP platforms. Similarly, we are exploring how to increase interoperability to achieve a common approach to packaging, orchestrating and executing algorithms, with interoperable access to data for subsetting, fast browse, and cloud-optimized access, all using interoperable standards such as those from the Open Geospatial Consortium (OGC). Designed for interoperability, ESA and NASA utilize a common architecture for the software platform. It provides a cloud-based algorithm development environment (ADE) that enables scientists to develop algorithms collaboratively with access to the MAAP data catalog as well as other data archives. MAAP provides an Eclipse Che-based ADE supporting both Python and R languages, popular in this biomass community. Algorithms developed and containerized within the ADE can be deployed to run to thousands of computational nodes in the MAAP’s data processing system (DPS), dramatically speeding up processing and giving scientists a rapid, iterative turnaround of results. NASA’s implementation of the DPS is based on the Hybrid Science Data System (HySDS) framework, used by NASA flight projects to produce Earth science standard products.

cloud computing↗
DOE OSTI2020

Multi-Stage and Multi-Timescale Robust Co-Optimization Planning for Reliable and Sustainable Power Systems. Final Report

In this project, Clarkson University, in collaboration with Southern Methodist University and University of Pittsburgh, conducted the research to model, design, and implement a sophisticated generation and transmission co-optimization planning decision tool, called Multi-stage and Multi-timescale robust Co-Optimization Planning (MMCOP). The MMCOP decision tool intends to facilitate generation and transmission co-optimization planning of emerging power systems, while mitigating risks and uncertainties in both short-term operation dynamics and long-term policy and technology changes. Long-term power system planning aims at optimizing asset utilization by investing in a proper mix of various generation technologies and transmission lines to supply the future load growth. In particular, the Clean Power Plan (CPP), which is designed to combat climate change and reduce carbon emissions by setting a national limit on carbon pollution from power plants, may dramatically change the landscape of the power industry by further promoting clean energy and phasing out emissions-intensive generation technologies. In addition, novel non-wire alternatives (e.g., demand response (DR), distributed generation (DG), energy efficiency (EE), and smart grid technologies) and the computational complexity for large-scale systems significantly complicate the system planning procedure even further. However, existing conventional planning approaches neglect short-term variability and uncertainty of renewable energy, hourly chronological operation details, and physical nonlinear characteristics of the alternating current transmission network. As a result, existing conventional planning approaches may not work properly, and power systems reliability could be in jeopardy. In observing the limitations of existing conventional planning approaches and addressing new challenges of emerging power systems, the main scope of this project to develop co-optimization planning models within a multi-stage and multi-timescale framework. In particular, random contingencies, key uncertainty factors, and AC power flows are included to derive expansion plans while considering both long-term reliability and short-term flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Impact of Dynamic Storage Capacity Valuation in Capacity Expansion Models: Preprint

This paper looks at the impact of dynamic storage capacity valuation in capacity expansion models (CEMs), which are tools commonly used by power system planners, policymakers, and other stakeholders to inform decisions regarding the buildout of the electric grid. The objective of this analysis is to demonstrate the impact with a CEM of moving from a static storage capacity value (CV) to a curve-fitted approximation that captures the interactions between storage duration, PV penetrations, and storage penetration. We fit and then use those curves to calculate the battery storage CV as a function of the storage duration, storage penetration, and PV penetration. We use the Regional Energy Deployment System (ReEDS) model developed at the National Renewable Energy Laboratory (NREL) to show the impact of this improved storage capacity valuation on deployment. We also provide a curve fit equation for use by other modeling teams. This exogenous, but dynamic, approach is meant to be a first step in improving the representation of storage in CEMs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

State Technical Assistance - New Mexico Energy and Conservation Management Division Report [Slides]

The New Mexico Energy and Conservation Management Division (ECMD) sought technical assistance to enhance their ability to evaluate program impacts using the Low-Income Energy Affordability Data (LEAD) tool. NLR assisted ECMD in leveraging the LEAD tool to calculate and analyze energy burden across electric utility service areas, enabling them to assess program outcomes more effectively. To meet ECMD's goals, NLR developed a customized methodology to calculate utility-specific energy burden metrics using census tract data and available utility service area information from the Energy Information Administration (EIA). While acknowledging some limitations in the EIA dataset, NLR estimated the percentage of households within each service territory and incorporated relevant filters such as income, housing characteristics, and other demographics from the LEAD tool. The analysis provided ECMD with a new capability to evaluate program success based on energy savings, reductions in energy burden, and other performance indicators. The data and methodology also support discussions with utilities to improve the accuracy of service territory datasets. ECMD can use the outputs to track program effectiveness and plan future initiatives. NLR offered the possibility of follow-on work, including capacity-building for ECMD to repeat the analysis independently and the option to refine the analysis with updated service.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2005

Formal Safety Certification of Aerospace Software

In principle, formal methods offer many advantages for aerospace software development: they can help to achieve ultra-high reliability, and they can be used to provide evidence of the reliability claims which can then be subjected to external scrutiny. However, despite years of research and many advances in the underlying formalisms of specification, semantics, and logic, formal methods are not much used in practice. In our opinion this is related to three major shortcomings. First, the application of formal methods is still expensive because they are labor- and knowledge-intensive. Second, they are difficult to scale up to complex systems because they are based on deep mathematical insights about the behavior of the systems (t.e., they rely on the "heroic proof"). Third, the proofs can be difficult to interpret, and typically stand in isolation from the original code. In this paper, we describe a tool for formally demonstrating safety-relevant aspects of aerospace software, which largely circumvents these problems. We focus on safely properties because it has been observed that safety violations such as out-of-bounds memory accesses or use of uninitialized variables constitute the majority of the errors found in the aerospace domain. In our approach, safety means that the program will not violate a set of rules that can range for the simple memory access rules to high-level flight rules. These different safety properties are formalized as different safety policies in Hoare logic, which are then used by a verification condition generator along with the code and logical annotations in order to derive formal safety conditions; these are then proven using an automated theorem prover. Our certification system is currently integrated into a model-based code generation toolset that generates the annotations together with the code. However, this automated formal certification technology is not exclusively constrained to our code generator and could, in principle, also be integrated with other code generators such as RealTime Workshop or even applied to legacy code. Our approach circumvents the historical problems with formal methods by increasing the degree of automation on all levels. The restriction to safety policies (as opposed to arbitrary functional behavior) results in simpler proof problems that can generally be solved by fully automatic theorem proves. An automated linking mechanism between the safety conditions and the code provides some of the traceability mandated by process standards such as DO-178B. An automated explanation mechanism uses semantic markup added by the verification condition generator to produce natural-language explanations of the safety conditions and thus supports their interpretation in relation to the code. It shows an automatically generated certification browser that lets users inspect the (generated) code along with the safety conditions (including textual explanations), and uses hyperlinks to automate tracing between the two levels. Here, the explanations reflect the logical structure of the safety obligation but the mechanism can in principle be customized using different sets of domain concepts. The interface also provides some limited control over the certification process itself. Our long-term goal is a seamless integration of certification, code generation, and manual coding that results in a "certified pipeline" in which specifications are automatically transformed into executable code, together with the supporting artifacts necessary for achieving and demonstrating the high level of assurance needed in the aerospace domain.

Denney, Ewen↗
DOE OSTI2022

FORCE Development Status Update: Vertical Integration and Benchmarking of System Dynamics

Recent efforts to establish effective models for grid energy analysis, especially given the increase in variable renewable energy (VRE) sources and the economic challenges faced by traditional nuclear energy, have generated new technological considerations. One effort to improve the economic viability of nuclear power involves investigating integrated energy systems (IES) which include secondary energy systems that introduce flexibility and secondary market possibilities to existing and perceived future nuclear energy generation technologies. To analyze the technical and economic potential of IES, the Framework for Optimization of Resources and Economics (FORCE) tool suite was developed through a collaboration among national laboratories. Within the FORCE tool suite, the Holistic Energy Resource Optimization Network (HERON) provides algorithms for analyzing the long-term viability of potential IES technologies, while HYBRID provides algorithms and models to achieve high-resolution analysis of coupling physics over a short time period. Continued maturing of the FORCE tool suite requires further interconnections between the various tools in the suite in order to ensure consistent analysis. Analyses performed by applying HYBRID to transient process modeling should be easily harvestable as inputs to HERON analyses. The first item in this status update is a demonstration of an automated data pipeline for loading data from HYBRID into HERON analyses. Application of HYBRID results to HERON, as part of using the FORCE tool suite, relies on robust modeling assumptions for the various models included in HYBRID. The second result of this status update is the benchmarking and validation of cost and operational data, with a particular focus on natural gas energy generators. These generators are benchmarked with a focus on contrasting them with proposed thermal energy storage (TES) technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Tariff Considerations for Micro-Grids in Sub-Saharan Africa

This report examines some of the key drivers and considerations policymakers and decision makers face when deciding if and how to regulate electricity tariffs for micro-grids. Presenting a range of tariff options, from mandating some variety of national (uniform) tariff to allowing micro-grid developers and operators to set fully cost-reflective tariffs, it examines various benefits and drawbacks of each. In addition, the report and explores various types of cross-subsidies and other transitional forms of regulation that may offer a regulatory middle ground that can help balance the often competing goals of providing price control on electricity service in the name of social good while still providing a means for investors to ensure high enough returns on their investment to attract the necessary capital financing to the market. Using the REopt tool developed by the U.S. Department of Energy's National Renewable Energy Laboratory to inform their study, the authors modeled a few representative micro-grid systems and the resultant levelized cost of electricity, lending context and scale to the consideration of these tariff questions. This simple analysis provides an estimate of the gap between current tariff regimes and the tariffs that would be necessary for developers to recover costs and attract investment, offering further insight into the potential scale of subsidies or other grants that may be required to enable micro-grid development under current regulatory structures. It explores potential options for addressing this gap while trying to balance This report examines some of the key drivers and considerations policymakers and decision makers face when deciding if and how to regulate electricity tariffs for micro-grids. Presenting a range of tariff options, from mandating some variety of national (uniform) tariff to allowing micro-grid developers and operators to set fully cost-reflective tariffs, it examines various benefits and drawbacks of each. In addition, the report and explores various types of cross-subsidies and other transitional forms of regulation that may offer a regulatory middle ground that can help balance the often competing goals of providing price control on electricity service in the name of social good while still providing a means for investors to ensure high enough returns on their investment to attract the necessary capital financing to the market. Using the REopt tool developed by the U.S. Department of Energy's National Renewable Energy Laboratory to inform their study, the authors modeled a few representative micro-grid systems and the resultant levelized cost of electricity, lending context and scale to the consideration of these tariff questions. This simple analysis provides an estimate of the gap between current tariff regimes and the tariffs that would be necessary for developers to recover costs and attract investment, offering further insight into the potential scale of subsidies or other grants that may be required to enable micro-grid development under current regulatory structures. It explores potential options for addressing this gap while trying to balance stakeholder needs, from subsidized national tariffs to lightly regulated cost-reflective tariffs to more of a compromise approach, such as different standards of regulation based on the size of a micro-grid.takeholder needs, from subsidized national tariffs to lightly regulated cost-reflective tariffs to more of a compromise approach, such as different standards of regulation based on the size of a micro-grid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2011

COMFEN 3.0 - Evolution of an Early Design Tool for Commercial Facades and Fenestration Systems

Achieving a net-zero energy building cannot be done solely by improving the efficiency of the engineering systems. It also requires consideration of the essential nature of the building including factors such as architectural form, massing, orientation and enclosure. Making informed decisions about the fundamental character of a building requires assessment of the effects of the complex interaction of these factors on the resulting performance of the building. The complexity of these interactions necessitates the use of modeling and simulation tools to dynamically analyze the effects of the relationships, yet decisions about the building fundamentals are often made in the earliest stages of design, before a `building? exists to model. To address these issues, Lawrence Berkeley National Laboratory (LBNL) has developed an early-design energy modeling tool (COMFEN) specifically to help make informed decisions about building facade fundamentals by considering the design of the building envelope, orientation and massing on building performance. COMFEN focuses on the concept of a ?space? or ?room? and uses the EnergyPlus, and RadianceTM engines and a simple, graphic user interface to allow the user to explore the effects of changing key early-design input variables on energy consumption, peak energy demand, and thermal and visual comfort. Comparative results are rapidly presented in a variety of graphic and tabular formats to help users move toward optimal facade and fenestration design choices.While COMFEN 1.0 utilized an ExcelTM-based user interface, COMFEN 3.0 has been reworked to include a simple, more intuitive, yet powerful Graphic User Interface (GUI), a broader range of libraries for associated system and component choices and deliver a wider range of graphic outputs and options. This paper (and presentation) outlines the objectives in developing and further refining COMFEN, the mechanics of the program, and plans for future development.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Intersections of Disadvantaged Communities and Renewable Energy Potential: Data Set and Analysis to Inform Equitable Investment Prioritization in the United States

Renewable energy development can bolster local economies through job creation, local tax revenues, and reduced energy costs; however, communities most in need of economic development and employment opportunities often see lower levels of renewable energy deployment. We sought to identify areas where disadvantaged community indicators and high generation potential from cost-effective renewable energy opportunities intersect and deployment could lead to economic development and job creation. This presentation will highlight several of our findings. This research and the associated county-level data set are intended to inform national- and state-level energy-related assistance programs, economic development efforts, and infrastructure programs seeking to prioritize investments in disadvantaged communities.

community energy planning↗
DOE OSTI2019

CSP Systems Analysis - Final Project Report

The CSP Systems Analysis project was a three-year effort supporting the Concentrating Solar Power (CSP) Subprogram within the Solar Energy Technologies Office of the U.S. Department of Energy (DOE). The goal of the CSP Systems Analysis project was to provide timely and accurate CSP cost data to the DOE and predict performance and cost for emerging technologies that may impact research directions and industry investment. The project consisted of six, mostly independent tasks. Major accomplishments over the three-year period of performance were as follows. The NREL team maintained current cost estimates for CSP technologies by annual updates to the cost input parameters within NREL's System Advisor Model (SAM). SAM is a performance and cost simulation software that includes technology models for the primary CSP technologies. During the period from 2016 to 2018, the estimated cost within SAM's default CSP molten-salt power tower technology dropped from 13.0 to 11.1 cent/kWh (real dollars without incentives). Power cycle models for the supercritical carbon dioxide (sCO2) Brayton Cycle were developed and made an option within SAM's molten-salt power tower model. These models were subsequently used to evaluate the cost reduction potential of alternative salts. The partial-cooling model was found to provide the greatest cost-reduction potential due to its combination of efficiency and temperature differential across the turbine and thermal energy storage (TES) system. These studies were documented in two journal articles. NREL's optical modeling software SolTrace and SolarPILOT were made more versatile and released as open-source software to the CSP community. These tools help researchers and developers to model and optimize the optical performance of CSP collector systems. The new features were highlighted in a recorded webinar that can be accessed from the NREL SAM website. New models for solar-thermal systems, that is, applications for solar industrial process heat, were developed, validated, and installed within SAM. The analysis includes a 2018 review of linear collectors in the market that are tailored for solar process heat applications. In 2018 the NREL team also developed an annual simulation for a direct steam generation system integrated with a latent-heat TES system. This analysis was submitted for journal publication. The NREL team continued to support the exchange of information and development of CSP guidelines within the international CSP community of SolarPACES. Much of the work under this project was presented at SolarPACES, including the development of a modeling checklist to help CSP stakeholders standardize the models used for estimating CSP performance and cost. The CSP Systems Analysis project also supported DOE requests for tracking and reporting programmatic targets for the CSP Subprogram.

14 SOLAR ENERGY↗
DOE OSTI2023

Data-driven modeling of municipal water system responses to hydroclimate extremes

Sustainable western US municipal water system (MWS) management depends on quantifying the impacts of supply and demand dynamics on system infrastructure reliability and vulnerability. Systems modeling can replicate the interactions but extensive parameterization, high complexity, and long development cycles present barriers to widespread adoption. To address these challenges, we develop the Machine Learning Water Systems Model (ML-WSM) – a novel application of data-driven modeling for MWS management. We apply the ML-WSM framework to the Salt Lake City, Utah water system, where we benchmark prediction performance on the seasonal response of reservoir levels, groundwater withdrawal, and imported water requests to climate anomalies at a daily resolution against an existing systems model. The ML-WSM accurately predicts the seasonal dynamics of all components; especially during supply-limiting conditions (KGE > 0.88, PBias < ±3%). Extreme wet conditions challenged model skill but the ML-WSM communicated the appropriate seasonal trends and relationships to component thresholds (e.g., reservoir dead pool). The model correctly classified nearly all instances of vulnerability (83%) and peak severity (100%), encouraging its use as a guidance tool that complements systems models for evaluating the influences of climate on MWS performance.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

LANL Regular Employee Population and Demographics, FY15-21

This document summarizes an effort to compile and analyze the LANL regular employee population’s demographic attributes and trends between FY15-FY21 using MicroStrategy, a web-based data analytics and visualization tool. LANL’s HR Division collected and prepared data for the Weapons Program’s annual reporting activities for the 2017 through 2023 NNSA Stockpile Stewardship and Management Plan (SSMP). Los Alamos workforce data represent the fiscal year-end snapshot of the permanent employee population who are categorized by the Common Occupational Classification System (COCS). This work enables further analyses, including trends for all workforce attributes presented in the SSMPs as well as a definition of a crosswalk between COCS categorization and the internal laboratory job classification hierarchy. Data for other sites and the federal workforce, as shown in the SSMPs, are included and corresponding figures can be visualized within the MicroStrategy tool. A portable, Excel-based version of the tool was developed and shared with the multi-site workforce working group. This summary highlights selected aspects of the LANL regular workforce. The data analyses and visualizations communicate insights within three major themes regarding permanent LANL employees: 1) demographic transformation, 2) attrition, and 3) skills. Regarding demographic transformation, and consistent with the general trend across the enterprise, early career regular employees are the fastest growing group, with growth ranging between 12-34% year-to-year over the seven-year period analyzed. The data also reflect effects of internal and external factors on attrition; the large spike in separations in FY18 aligns with the contract transition from LANS to Triad and the dip in attrition between FY20-FY21 is likely a result of the global pandemic. The population of regular employees in general management, engineer, and operator COCS categories have the fastest growth rates amongst all the occupational categories. The MicroStrategy and Excel tools provide additional details and trends.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

High Throughput, High Precision Hot Testing Tool for HBLED Wafer Level Testing

The Socrates research effort developed an in depth understanding and demonstrated in a prototype tool new precise methods for teh characterization of color characteristics and flux from individual LEDs for the production of uniform quality lighting. This effort was focused on improving the color quality and consistency of solid state lighting and potentially reducing characterization costs for all LED product types. The patented laser hot testing method was demonstrated to be far more accurate than all current state of the art color and flux characterization methods in use by the solid state lighting industry today. A seperately patented LED grouping method (statistical binning) was demonstrated to be a useful approach to improving utilization of entire lots of large color and flux distributions of manufactured LEDs for high quality color solid-state lighting. At the conclusion of the research in late 2015 the solid-state lighting industry was however generally satisfied with its existing production methods for high quality color products for the small segment of customers that demand it, albeit with added costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

SOLAr Critical Infrastructure Energization (SOLACE): Leveraging Distributed Energy Resources to Provide Local Power

This document is a technical report based on a large-scale DOE-funded project conducted between 2019 and 2022. The project, called SOLAr Critical infrastructure Energization (SOLACE), is aimed at leveraging distributed energy resources (DERs) to provide local power to communities, feeders, or other regions. The project included a particular focus on high-value critical loads such as municipal water supply, telecommunication hubs, and disaster shelters. The key developments of the project were: (1) A comprehensive pre-event power system analysis methodology that identifies and characterizes the viable local power options. (2) A DMS-based example control system for activating and operating the local power solution during a time of crisis. (3) Grid-forming inverter technology to enable isolated local power operation and black-starting. (4) Cyber-security considerations for isolated systems when wider-area communication may be offline. This report describes the overall process that identifies and assesses the viable DER-based local power solutions for a given facility, region, or community. The report documents the process, including the key analysis steps, tools required, data requirements, and recommended pass/fail criteria for each step. It also provides a sample implementation of this process through a test case. Finally, it provides details of how a viable pre-event plan can be selected and activated at go-time when an event has occurred.

14 SOLAR ENERGY↗
DOE OSTI2025

Data Centers and Digital Assurance Workshop 3 – Mitigations for Digital Assurance Risks

The third session of the TADA (Technical Assistance for Digital Assurance) Data Centers Cohort, held on November 18, 2025, focused on developing mitigation strategies for digital assurance risks identified in previous workshops. Hosted by Idaho National Laboratory (INL) and ScottMadden, the session emphasized the application of Cyber-Informed Engineering (CIE) to data center infrastructure, particularly at the utility–data center interface. Participants revisited and ranked key digital assurance risks, including architecture and interface weaknesses, governance gaps, and AI-enabled threats. The workshop introduced the 12 principles of CIE, advocating for consequence-focused design, engineered controls, and secure information architecture to proactively reduce cyber-physical vulnerabilities. These principles were applied to critical data center systems such as power distribution, UPS, cooling, SCADA/BMS, and grid-forming batteries. The session also addressed governance challenges at the interconnection boundary, highlighting the need for clear roles in telemetry sharing, firmware management, and trip settings. Special attention was given to emerging risks from behind-the-meter (BTM) generation, including reverse-power flow and the integration of small modular reactors (SMRs), which shift data centers from large loads to complex generation nodes. Participants explored how interconnection agreements can serve as enforceable instruments for digital assurance, and reviewed gaps in current standards such as NERC CIP, IEC 62443, and IEEE 1547. The workshop concluded with pathways to standardization, including model agreement language, state-level programs, and expanded NERC guidance. INL also presented tools and frameworks for secure procurement and supplier risk management, reinforcing the need for integrated engineering and policy solutions to secure the evolving data center–grid ecosystem. Session 3 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Status on the Development of a Modeling and Simulation Framework for the Economic Assessment of Nuclear Hybrid Energy Systems

An effort to design and build a modeling and simulation framework to assess the economic viability of Nuclear Hybrid Energy Systems (NHES) was undertaken in fiscal year 2015 (FY15). The purpose of this report is to document the various tasks associated with the development of such a framework and to provide a status on its progress. Several tasks have been accomplished. First, starting from a simulation strategy, a rigorous mathematical formulation has been achieved in which the economic optimization of a Nuclear Hybrid Energy System is presented as a constrained robust (under uncertainty) optimization problem. Some possible algorithms for the solution of the optimization problem are presented. A variation of the Simultaneous Perturbation Stochastic Approximation algorithm has been implemented in RAVEN and preliminary tests have been performed. The development of the software infrastructure to support the simulation of the whole NHES has also moved forward. The coupling between RAVEN and an implementation of the Modelica language (OpenModelica) has been implemented, migrated under several operating systems and tested using an adapted model of a desalination plant. In particular, this exercise was focused on testing the coupling of the different code systems; testing parallel, computationally expensive simulations on the INL cluster; and providing a proof of concept for the possibility of using surrogate models to represent the different NHES subsystems. Another important step was the porting of the RAVEN code under the Windows™ operating system. This accomplishment makes RAVEN compatible with the development environment that is being used for dynamic simulation of NHES components. A very simplified model of a NHES on the electric market has been built in RAVEN to confirm expectations on the analysis capability of RAVEN to provide insight into system economics and to test the capability of RAVEN to identify limit surfaces even for stochastic constraints. This capability will be needed in the future to enforce the stochastic constraints on the electric demand coverage from the NHES. The development team gained experience with many of the tools that are currently envisioned for use in the economic analysis of NHES and completed several important steps. Given the complexity of the project, preference has been given to a structural approach in which several independent efforts have been used to build the cornerstone of the simulation framework. While this is good approach in establishing such a complex framework, it may delay reaching more complete results on the performance of analyzed system configurations. The integration of the previously reported exergy analysis approach was initially proposed as part of this milestone. However, in reality, the exergy-based apportioning of cost will take place only in a second stage of the implementation since it will be used to properly allocate cost among the different NHES subsystems. Therefore, exergy does not appear at the level of the main drivers in the analysis framework; the latter development of the base framework is the focus of this report.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Assessing Alignment Between a Top-Down LCA Model and a Bottom-Up Supply Chain Model for Data Gap Identification and Prioritization

This work presents a method for evaluating the alignment between the results of bottom-up and top-down models and using the evaluation to enhance the bottom-up model and underlying data set. Disaggregation is used to enhance the embodied energy results of top-down models, which are then compared to bottom-up model results. Using the disaggregated top-down results makes it possible to identify specific data gaps and deficiencies within the bottom-up model and its data set. The top-down results will also provide information around which data gaps in the bottom-up model are contributing the most error to the results; in this way, data gaps can be identified as either critical or non-critical, and the effort needed to acquire and add data can be prioritized. Although the proposed method could be applied to any physical quantity or environmental impact that can be quantified with both bottom-up models (typically in physical units) and top-down models (typically in monetary units), embodied energy is the focus of this work. The disaggregated energy baseline is calculated from the throughput vector x, which gives the total economic activity required from each sector to provide a final demand. Using the direct requirements matrix, each element in x is disaggregated into a vector of inputs to the corresponding sector. Energy data from the interventions matrix B is then used to convert the monetary flows of the disaggregated x into physical energy flows. For each energy flow, the origin sector, the destination sector, and the energy carrier type will all be known. These energetic flows are analogous but not identical to direct energy inputs that would appear in a unit process used in life cycle analysis and other bottom-up methods, and thus can be used to evaluate the alignment between the top-down results and the results of a bottom-up model. To demonstrate and further develop the proposed method, embodied energy for chemicals assessed in the 2015 U.S. DOE bandwidth study on energy use within the chemical sector will be calculated using a top-down and a bottom-up model. The Materials Flows through Industry (MFI) modeling tool developed at the National Renewable Energy Laboratory is used as the bottom-up model, and the U.S. EEIO model, recently published by the U.S. Environmental Protection Agency, is used as the top-down model. U.S. EEIO and MFI results will be evaluated to determine how well the model results align. Where the two models are not in good alignment, the disaggregation method described above will be applied to the top-down model to generate a more detailed set of results that will aid in identifying data gaps in the MFI database. Using only MFI, data gaps can be identified in terms of which sectors have few or no unit processes in the database, but no information is available regarding the impact of the missing data on MFI results. The disaggregated top-down results will provide this information on which gaps in the MFI data are critical and have a significant impact on the results, and which are less important.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Chicago Energy Efficiency Planning and Analysis and Integrated Retrofit Strategy Validation in Single-Family Homes

In June 2020, the project team comprised of Elevate and the National Renewable Energy Laboratory (NREL), with advisory roles from the City of Chicago and Commonwealth Edison, initiated a three-year project with the U.S. Department of Energy to inform communitywide energy planning at a local scale and validate advanced retrofit packages that achieve at least 50% energy savings in existing homes. The project team has characterized Chicago’s single-family and 2-4 unit housing stock and energy use using the ResStock™ modeling tool, and with that information developed advanced whole home energy retrofit packages for single family and 2-4 unit homes that can reduce energy use by at least 50% and support climate, air quality, and other goals. This report presents an analysis of the technical potential of applying these retrofit packages at a City-wide scale, and a roadmap for rapidly scaling up retrofit programs to improve Chicago’s housing stock and target investments in the neighborhoods that need it most. The main goals of the analysis are to: 1) develop a Chicago-specific single-family and 2-4 unit building retrofit prioritization strategy; 2) identify opportunities for beneficial electrification in communities and home types that stand to benefit most; and 3) assess costs and savings potential for retrofit investments at a household and city scale, in terms of energy use, bill impacts, carbon emissions, and other outcomes.

14 SOLAR ENERGY↗