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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Battery Storage for Resilience

As the capital costs of battery storage systems are decreasing, new opportunities to cost-effectively deploy the technology, often paired with renewable energy technologies, are emerging. At the same time, the duration and frequency of natural disasters is increasing. As a result, a growing number of institutions are deploying battery storage systems as a resilient energy solution because traditional back-up power solutions, like diesel generators, are not always sufficient, especially during longer-duration and larger-scale disasters. This fact sheet describes how battery storage, along with additional generation sources, can be used both to provide cost savings while grid-connected and to provide backup power when the grid goes down.

25 ENERGY STORAGE↗
DOE OSTI2023

Assessing Low-Temperature Geothermal Play Types: Relevant Data and Play Fairway Analysis Methods

The U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) is supporting the Geothermal Heating and Cooling Geospatial Datasets and Analysis project conducted by the National Renewable Energy Laboratory (NREL) as part of a broader effort to demonstrate the multi-faceted value of integrating geothermal power and geothermal heating and cooling (GHC) technologies into national decarbonization plans and community energy plans. Currently, there is a need to establish baseline low-temperature geothermal resource datasets and evaluate methods for deploying these technologies to provide the basis for supporting private sector investment. This project is focused on collecting baseline datasets, updating conceptual models, and creating Play Fairway Analysis (PFA) workflows for low-temperature (<150 degrees Celsius) geothermal resources of different geothermal play types (i.e., sedimentary basin, orogenic belts, and radiogenic geothermal play types) that could be used for geothermal heating and cooling (GHC), combined heat and power (CHP), and other geothermal direct uses (GDU) applications. Low-temperature geothermal resources are defined as reservoirs - natural or engineered - with temperatures <150 degrees Celsius. While the focus in the NREL effort is on GHC, resources at the upper end of this temperature range can also be used for small-scale power generation. This project does not include Ground Source Heat Pumps (GSHPs) technologies because they can be effectively developed almost anywhere. Low-temperature geothermal resources have not been studied as extensively as higher- to medium-temperature geothermal resources, but there is recent interest in improving understanding of these types of resources with an uptick of interest in geothermal technologies for decarbonizing heating and cooling systems. In addition, Enhanced Geothermal Systems (EGS) and other emerging technologies for exploiting petrothermal resources have opened the possibility of utilizing deep sedimentary basin systems, where porous media provide permeability and high temperatures can be reached at great depths. This project takes the approach of classifying low- temperature geothermal resources by geothermal play type (GPT). We defined and characterized three major classes of low-temperature GPT: sedimentary basins, orogenic systems, and radiogenic systems. We develop methodologies for evaluating and analyzing the potential for these resources building off the PFA approach to de-risking geothermal exploration and characterization. The proposed PFA approach for low-temperature geothermal resources includes: 1) identifying relevant data (e.g., datasets such bottom-hole temperatures from oil and gas wells, heat flow data, Quaternary faults and stress field data, geophysical data, etc.); 2) grouping and weighting of relevant datasets into PFA criteria (e.g., geological, risk, and economic criteria); 3) uncertainty quantification; 4) developing favorability or common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection; and 5) estimating electric power generation and heating potential at those locations using the GeoRePORT Resource Size Assessment Tool (RSAT). This project should facilitate future deployment of GHC, CHP, and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources. Increased deployment of GHC and GDU will help achieve national and local decarbonization goals.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Assessing Low-Temperature Geothermal Play Types: Relevant Data and Play Fairway Analysis Methods

This data catalog contains information on low temperature geothermal play types. The U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) supports the Geothermal Heating and Cooling Geospatial Datasets and Analysis project, conducted by the National Renewable Energy Laboratory (NREL). This project is part of a broader effort to demonstrate the multifaceted value of integrating geothermal power and geothermal heating and cooling technologies into national decarbonization strategies and community energy plans. There is a need to establish baseline low-temperature geothermal resource data sets and evaluate methods for deploying these technologies. This project aims to reduce exploration risk of low temperature geothermal systems by collecting baseline datasets that can be used for Play Fairway Analysis methodologies. This data catalog contains links to publicly available datasets from different sources that can be relevant for the low temperature geothermal systems. This submission contains data catalogs for Alaska, Hawaii, and the Conterminous United States, as well as a technical report on the methods used to classify and asses the geothermal play types.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Effective Communication of Energy Science and Technology

Although research, development, and deployment of advanced energy technologies are essential for the clean energy transition, communication about these technologies is equally important to their success. Energy is part of everyday life; therefore, changes in energy systems should be accepted by communities and industries. Yet details about energy generation, transmission, and environmental impacts are complex. The combination of commonality and complexity requires communications to use visualization, localization, narrative, and understandable terminology to reach a range of stakeholders. Collaboration between technology experts and communications professionals builds integrity and accessibility of energy information that enables community-based solutions for energy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Life Cycle Assessment for Closed-Loop Pumped Hydropower Energy Storage in the United States

The federal government has initiated an aggressive set of policies to achieve a net-zero carbon emission goal for the electricity sector by 2050. As a result, rapid growth in deployment of renewable energy technologies is expected. Most commercially mature technologies are temporally variable and do not provide grid inertia, while renewable technologies with high projected deployment have intermittent generation methods. Energy storage technologies are needed to both dispatch power on-demand and help provide the needed grid inertia. Pumped storage hydro (PSH) is a well-established technology that has gained renewed interest in recent years offering energy-balancing, grid stability, control of electrical network frequency, and large-scale storage capacity. For widespread adoption of PSH, more information is needed regarding its current life cycle environmental impacts. The objective of this study is to perform a full life cycle assessment (LCA) of new closed-loop PSH in the U.S. The functional unit for this study is 1 kWh of electrical power delivered to the grid and the base case project lifetime is 80 years. The life cycle inventory for this project accounts for all material and energy flows associated with the green-field construction, operation, maintenance, and decommissioning of a closed-loop PSH plant in the U.S. Collected data represents a range of potential PSH specifications and geographic locations coming from all prospective closed-loop PSH installations in the U.S. with data available. In addition, existing PSH installations are used to provide assumptions for inventory inputs. Results presented will include the global warming potential (GWP IPCC 100a) and Energy Return on Investment (EROI) from our base case (average PSH installation) as well as from scenario analyses and model sensitivity. These results will be compared to the impacts from existing PSH sites and alternate storage technologies. Methods align with the assumptions and guidelines put in place by previous PSH LCAs to ensure an accurate comparison with the results from this report.

ENERGY PLANNING, POLICY, AND ECONOMY,HYDRO ENERGY↗
DOE OSTI2025

Tale of Two Domains: Cyber - Physical

As devices and systems continue to modernize and adopt integrated circuits, the use of cyber technology to deploy an application is the expectation. This deployment through cyber assets brings new cyber risk and cybersecurity is the practice of managing this risk. Cyber-risk is constantly changing due to the speed of technology advancement and the changing quality of the adversary. Cyber-Informed Engineering (CIE) mitigates cyber-risk through engineering controls where as the traditional practice of cybersecurity mitigates cyber-risk through cybersecurity controls. By clearly defining the cyber-physical boundary, engineering controls and cybersecurity controls can clearly demonstrate their complementary nature to provide layered defenses and successfully mitigate cyber-risk through independent controls. In this paper, a layered model of device decomposition of the the cyber-physical boundary is presented to provide clarity where engineering controls are used to reduce cyber-risk within the physics, functional materials, electronic, or integrated circuit layers and where cybersecurity controls are used to reduce cyber-risk within the machine code and application layers. By implementing both traditional cybersecurity controls and engineering controls, a more holistic approach to cybersecurity is achieved in protecting modern devices and systems, as well as a clear awareness in identifying, documenting, and authorizing the system’s cybersecurity protection scheme is achieved.

42 - ENGINEERING↗
DOE OSTI2022

Ambassador Project (Final Report)

SEL, in collaboration with its partners, performed research, development and demonstration of a trust, data, and resource management software layer enabling multiple software applications from different suppliers to operate in a Software Defined Infrastructure. The Energy sector has successfully deployed Software Defined Networking (SDN) technology and is rapidly scaling deployments. One major benefit of SDN is the abstracted centralized nature of the orchestration and management of the network. This architecture enables end users to deploy new technology and capabilities as quickly as they perform firmware upgrades to field devices. When an end user needs to roll trucks to install new equipment, they simply deploy new software to run on top of this SD-Infrastructure. This has attracted many software companies to develop value added features and introduce new capabilities, which is all good for the industry but has also introduced new challenges, including how to manage trust between these software applications, how to manage the data integrity and access, and how to manage access to the network resources each of these software applications are demanding. Completion of this project developed and demonstrated a safe and reliable resource scheduler and cybersecurity trust management communication platform allowing multiple software applications to operate in a SD-Infrastructure resulting in the commercialization of a software eco-system and architecture that maintains interoperability, cybersecurity, and reliability where the end user can safely scale out their software to leverage the powerful benefits of SDN.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Rays for Roots - Integrating Backscatter X-Ray Phenotyping, Modeling and Genetics to Increase Carbon Sequestration and Switchgrass Resource Use (Final Report)

To increase carbon (C) deposition in the soil and enhance crop resource use efficiency, characterizing root form and function is essential. Several root and soil traits have been linked to increased root-to-soil C transfer. Technology that could provide high-resolution characterization of many of these traits in field conditions would revolutionize our ability to study and understand how to increase C sequestration. In this effort, we developed an initial early prototype backscatter X-ray system for non-destructive imaging of root traits. We collected initial backscatter X-ray data in field and lab settings and carried out early analysis of these data. Along with this prototype, we also developed a suite of root phenotyping approaches including advanced minirhizotron image analysis, soil core imaging, and mesocosm imaging. Minirhizotron (MR) tubes are clear tubes inserted into the soil in the field and used to image roots and the surrounding soil. Our team has developed deep learning-based methods that can segment roots from soil that can learn from imprecise image-level labels. The ability to learn or fine-tune our deep learning algorithms from image-level labels allows easier and faster application of these approaches to new locations and new plant species. We have successfully implemented and applied our MR analysis approaches to thousands of switchgrass MR images collected across geographical regions. An advantage of MR imaging is the ability to collect root and soil images over time. Our soil core analysis included collecting hundreds of soil core samples from harvested switchgrass fields and imaging these cores with both X-ray CT and backscatter X-ray imaging. Initial segmentation approaches for the X-ray CT images of these cores have been developed and applied. An advantage of soil core analysis is that it preserves the three-dimensional structures of the roots and soil in the core collected. Our group also developed photogrammetry-based mesocosm root imaging and phenotyping approaches. In this approach, a plant was grown in a large mesocosm with a three-dimensional grid of thin supporting lines inserted throughout the mesocosm. After the plant (and, correspondingly, the root architecture is grown and established) the soil media was removed and the supporting lines approximately preserved the three-dimensional root architecture. Then, we applied photogrammetry techniques to create a three-dimensional digital representation of the root architecture for which we developed analysis algorithms including skeletonization. We carried out our phenotyping development with powerful switchgrass resources and physiological and agroecosystem modeling to deliver novel technology. This project contributes to multiple ARPA-E missions including reduction of foreign imports of energy, reduction of energy-related emissions including greenhouse gases, and ensuring that the United States maintains a technological lead in developing and deploying advanced energy technology. Furthermore, the developed tools could transform public and private plant breeding and could be broadly applicable to other crops and, potentially, other application areas. Our team of engineers, plant and soil scientists, and modelers i) developed an early prototype backscatter X-ray platform that can operate in field conditions; ii) developed a suite of root phenotyping and characterization approaches as described above; iii) developed and carried out plant biology and physiology roots studies and; iv) developed and implemented mechanistic physiological modeling.

42 ENGINEERING↗
DOE OSTI2022

WBG-Enabled Current-Source Inverters for Integrated PM Motor Drives

This project takes advantage of the special capabilities of wide-bandgap (WBG) power semiconductor devices to develop innovative power electronics in the form of new current-source inverters (CSIs) that offer promising advantages over the dominant voltage-source inverter (VSI) topology. These CSIs, in turn, are extremely well-suited for integration into the housings of permanent magnet synchronous machines (PMSMs) to form integrated motor drives (IMDs). These new IMDs offer great promise for achieving major energy savings in a wide variety of applications that benefit from adjustable-speed control, including air conditioners, laundry appliances, industrial pumps/compressors, electric vehicles, and aerospace drives. WBG devices play a critical enabling role in these new IMDs because of their transformative features including much higher switching frequencies, lower losses, and compatibility with high operating temperatures. When incorporated into new CSI-based IMDs with PM machines, these WBG switches open the door to achieving major increases in power density, drive system efficiency, and fault tolerance, as well as substantial reductions in electromagnetic interference (EMI), manufacturing cost, and temperature-induced failures. The higher operating temperature capability of WBG devices compared to conventional silicon power devices is very appealing in IMD applications because the power electronics is mounted in close proximity to the motors which typically operate at temperatures well above the maximum limits of today’s silicon-based power electronics. This project has succeeded in designing, building, and testing multiple prototype versions of this CSI-IMD that have overcome many technical challenges in order to demonstrate the impressive performance improvements that can be achieved by the WBG-enabled CSI-IMD. The preliminary demo and bench-top versions of the current-source inverter developed during the first two years of the project were critical to laying the technical foundations for the 3 kW prototype CSI-IMD unit that was successfully built and tested during the third year. This prototype CSI-IMD unit was designed to fit within the housing envelope of the original permanent magnet (PM) synchronous machine in order to meet the demanding power density requirements that were set at the beginning of the project. All of the remaining performance objectives set for the prototype CSI-IMD unit including efficiency and electromagnetic interference (EMI) were also met. The last 18 months of the project were devoted to developing further enhancements of the WBG-enabled CSI-IMD technology that better prepare it for commercial production. More specifically, an upgraded version of the prototype CSI-IMD unit was developed that moved the power electronics into the same machine housing chamber as the motor, substantially raising the thermal demands on the power electronics. Tests with five different combinations of motor enclosure types and air cooling configurations were evaluated. Importantly, this work confirmed that the power electronics can deliver its full rated power and still operate well within its maximum temperature limits even for worst-case conditions when the housing is “totally-enclosed” without any openings for air to enter or exit the enclosure, and no blower/fan is provided to blow air over the outside surface of the enclosure. Reaching the full performance and energy-savings potential of this disruptive CSI-IMD motor drive technology is highly consistent with ARPA-E’s stated mission to “enhance the economic and energy security of the United States” while also supporting its commitment to “ensure that the U.S. maintains a technological lead in developing and deploying advanced energy technologies”. Follow-on projects are under way to explore the scalability of WBG-enabled CSI-IMD technology to 100 kW (peak) electric vehicle traction drives and fault-tolerant modular motor drives for future electrified aircraft propulsion applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

RADIANCE Executive Summary

Microgrids are gaining attention from organizations and cities because of their potential reliability and resilience benefits, especially in remote geographic areas: Microgrids can provide local power during emergencies, and they can reduce the costs of imported fuel by reducing overall fuel use. But the complexities and novelties of microgrid technologies are often barriers to deployment that require testing and validation to overcome. This report describes the testing, validation, and deployment of microgrid technologies in Cordova, Alaska, completed through the U.S. Department of Energy (DOE) Grid Modernization Laboratory Consortium (GMLC) project Resilient Alaskan Distribution system Improvements using Automation, Network analysis, Control, and Energy storage (RADIANCE).

ARIES↗
DOE OSTI2025

Vulcan Test Platform: Demonstrating the Data Center as a Flexible Grid Asset

Explosive data center demand is outpacing grid infrastructure development. AI workloads and hyperscale cloud growth are creating unprecedented power requirements, while traditional grid expansion faces multi-year development timelines, regulatory hurdles, and decarbonization challenges. Sidewalk Infrastructure Partners recognized this impending crisis years ago and founded Verrus to develop an innovative solution: data centers that function as grid assets rather than passive loads. The Verrus approach integrates proprietary grid-aware controls with battery energy storage systems (BESS) in a medium-voltage architecture that delivers three critical capabilities: Fast-responding demand flexibility that can service requests from the utility within 10 seconds, Uninterrupted transition to islanded operation during grid disturbances, Continuous uptime assurance while maintaining all customer service level commitments Through Verrus' strategic partnership with the National Renewable Energy Laboratory (NREL), we validated these capabilities on Vulcan, a 70 MW utility-scale test platform powered by NREL's ARIES Virtual Emulation Environment. This deployment-ready technology has successfully demonstrated that Verrus data centers can deliver meaningful grid services while maintaining mission-critical reliability. This technical report outlines the design, methodology, and results of this emulated deployment, demonstrating that data centers can play a pivotal role in enhancing grid flexibility and reliability, without sacrificing service level guarantees.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Development of Digital Twin-Informed Predictive Maintenance for Critical Components in Advanced Reactors

Small modular reactors (SMRs) and microreactors, along with other advanced reactor (AR) technologies, are key to the future of nuclear energy. For these systems to achieve low operating costs, high reliability, and flexibility across applications, their operation and maintenance must be optimized. Digital twin (DT) technology is one of the technologies that enables real-time (or faster than real-time) monitoring and prognosis of critical components which are vital for operational efficiency, low costs, and enhanced safety of ARs, accelerating their deployment. DT technology provides dynamic virtual representation of physical assets by integrating real-time data, physics-based models, and advanced analytics, which is critical to optimizing the performance of the entire energy system throughout the life cycle. DTs empower engineers and operators to virtually explore different scenarios, configurations, and control strategies, allowing for the identification of optimal solutions that maximize reactor efficiency, safety, and economics.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

National Smart Manufacturing Strategic Plan: To Facilitate More Rapid Development, Deployment and Adoption of Smart Manufacturing Technologies

Smart manufacturing technologies provide real-time data and insight to improve the productivity, efficiency, and competitiveness of U.S. manufacturing, creating the potential for new jobs in the manufacturing sector. These technologies can support U.S. manufacturers’ ability to increase throughput and energy efficiency, and decrease waste, defects, and costs. A wide range of manufacturing and industrial subsectors, particularly energy-intensive and energy-dependent industries, have the potential to benefit from smart manufacturing technologies. There are technical improvements still needed to reduce the costs and barriers (trained workforce and upskilling, software-hardware integration, cost, and technical barriers to deployment of advanced sensors, computing, and communication technologies for existing manufacturing assets) to the adoption of smart manufacturing technologies, especially to small and medium-sized manufacturers, and subsequently, increase the overall adoption rate of smart manufacturing technologies. This report outlines the Department of Energy’s (DOE) strategic plan to accelerate the development and implementation of smart manufacturing technologies in the United States and the actions DOE has taken to use these technologies in smart manufacturing for the United States. DOE’s plan to facilitate more rapid development, deployment and widespread adoption of smart manufacturing technologies derive from the 2018 Strategy for American Leadership in Advanced Manufacturing. The strategy outlines a vision for America’s leadership in advanced manufacturing including the development of intelligent manufacturing systems to optimize manufacturing facilities and support the manufacturing of transformative materials. DOE’s Clean Energy Smart Manufacturing Innovation Institute (CESMII), a Manufacturing USA Institute, focuses on accelerating the development and adoption of advanced sensors, controls, platforms, and models needed for smart manufacturing. The objective is to enhance U.S. manufacturing productivity and global competitiveness through the research and development of these technologies. Smart manufacturing has the potential to improve the overall performance, energy productivity, and efficiency of manufacturing, fostering the economic competitiveness of the manufacturing sector.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Integrated Methane Monitoring Platform Design (Final Report)

As the urgency for understanding methane emissions and the number of methane monitoring technologies being deployed have increased in the last two decades, there is an opportunity and a need to integrate the numerous disparate data sources to enable the detection, quantification, contextualization, and reporting of methane emissions along the oil and gas supply chain. Such an integration would enable emissions reductions through early detection of super emitters, data-driven mitigation strategies, and improved greenhouse gas inventories. The GTI Energy (“GTI”) project team (“the team”) worked with a multitude of industry experts, stakeholders, and subject matter experts (SMEs) to collect guidance, insights, and information to inform the requirements and subsequent engineering, design, deployment, and operations of an integrated methane monitoring platform (IMMP). This final report describes the results of the team’s effort to execute the Integrated Methane Monitoring Platform Design project, ultimately providing an engineering, design, deployment, and operating plan (EDDOP) for the IMMP. This final report summarizes and integrates the project tasks' results and outputs.

03 NATURAL GAS↗
DOE OSTI2023

The Feasibility of Direct CO2 Conversion Technologies on Impacting Mid-Century Climate Goals

Recent IPCC modeling suggests that to limit global warming below 2 degrees C, "unprecedented" reductions in CO2 emissions will be required during the 2030-2050 time frame. The direct conversion of CO2 to fuels and chemicals using renewable electricity has garnered interest as one route to draw down emissions with the ability to synthesize products at a significantly lower carbon footprint than conventional methods. However, most direct CO2 conversion pathways are only in the early stages of development and face technical and market hurdles prior to scale-up, bringing into question what role they may play in influencing global CO2 emissions within this critical two-decade window. In this perspective, we highlight low-temperature electrolysis as a promising technology for direct CO2 conversion, including discussion on the products that could most impact global emission levels, and importantly, offer insight into the timeline, required advancements, and specific technical targets needed to successfully scale and deploy these technologies at the commercial level.

chemicals↗
DOE OSTI2024

Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing

This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Is the Adoption of Electric Vehicles (EVs) and Solar Photovoltaics (PVs) Interdependent or Independent? An Integrated EVs-PVs Modeling Framework

Transportation and residential energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics or PVs) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market share for both EVs and PVs continue to grow, both these emerging technologies are deployed rather disjoint without considering the existence of potential similarities among users who own (or aspire to own) EVs and PVs. This might be due to lack of understanding of the behavioral interdependence in consumer preferences towards these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores EV and PV adoption behaviors. A structural equations model (SEM) is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive 'bundled' adoption of EVs and PVs could accelerate the adoption of both these sustainable technologies. The results highlights the need to consider transport and building energy efficient technology adoption behavior in a single integrated structure.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2021

Real Time - Optimal Power Flow Based Distributed Energy Resources Management System (DERMS) (CRADA Number CRD-20-16909 Final Report)

The integration of behind-the-meter distributed energy resources (DERs) into distribution systems brings transformative changes to power systems. This requires operators and planners to find solutions to modernize electric grids and to effectively manage DERs for grid services. NREL developed novel DER management algorithms (referred to as Real-Time Optimal Power Flow, RT-OPF) through U.S. Department of Energy (DOE)-funded efforts, including Advanced Research Projects Agency–Energy (ARPA-E) Network Optimized Distributed Energy Systems (NODES) funding. This cutting-edge control technology aims to modernize distribution systems with large amounts of DER integration, which will help utilities solve issues brought by renewable integration and build resilient and renewable-based electric grids nationwide. Utilidata worked with NREL to investigate the commercialization opportunity of this RT-OPF-based distributed energy resource management system (DERMS). In this project, NREL performs the technology transfer of the RT-OPF to Utilidata to help them fully understand the RT-OPF solution, to identify potential engineering hurdles, and to assess the expected commercial value of various RT-OPF use cases and deployment. The technology transfer work includes two major tasks. First, NREL performs an in-depth knowledge transfer of the entire RT-OPF solution to Utilidata to help them gain an extensive and detailed understanding of the complete RT-OPF solution. In this task, NREL provides exhaustive information (e.g., documentation, code packages, laboratory and field trial data, performance results) while conducting in-depth training sessions to provide a thorough explanation of the entire solution. NREL hosts meetings to present different topics related to the RT-OPF solution, and question-and-answer sessions are included in each meeting to better explain the RT-OPF-related work. Second, the RT-OPF simulations are performed in a laboratory environment. The main objectives of this task are to walk through with Utilidata engineers how to set up a simulation of RT-OPF, identifying each RT-OPF code block/component in operation, learning how these components interact with each other, and eventually running RT-OPF simulations under various system conditions. This task helps Utilidata engineers understand performance limitations and constraints while also quantifying the commercial value of the RT-OPF for different use cases. Based on these two tasks, Utilidata engineers should be able to define and prioritize the next steps of RT-OPF implementation with an eye toward commercial success and scalability of the solution. The next steps are expected to be part of a new project following the conclusion of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗