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DOE OSTI2022

Westinghouse Accident Tolerant Fuel Phase 2B with Higher Enriched and Higher Burnup Add-On Project Final Technical Report Deliverable Volume 1

The Westinghouse Electric Company LLC (Westinghouse) accident tolerant fuel (ATF) program funded by Westinghouse and the US Department of Energy (DOE) utilized chromium (Cr) coated zirconium alloy cladding with doped UO 2 (ADOPT(TM)) and uranium silicide (U 3 Si 2 ) high density/high thermal conductivity fuel for its lead test rod (LTR) program with irradiation beginning in 2019. ADOPT is a Cr 2 O 3 +Al 2 O 3 doped UO 2 pellet with increased oxidation resistance and density, and increased resistance to fission gas release. Due to the issues with U 3 Si 2 fuel reaction in pressurized water reactor (PWR) environments, uranium nitride (U 15 N) has been substituted for U 3 Si 2 as a long-term fuel option. Cr coated cladding with ADOPT fuel is the near-term Westinghouse EnCore fuel product. The long-term EnCore ® fuel product is SiGA ® SiC/SiC composite cladding with high density/high thermal conductivity UN fuel. In 2020, the higher burnup and higher enriched and (HBHE) program was integrated into the ATF program. The objective of this expanded program is to extend ATF burnups to at least 75 MWd/kgU to economically facilitate 24-month cycles in PWRs. The ATF program now includes ADOPT fuel with enrichments >5% 235 U. Over the past several years, Westinghouse has tested the Cr coated zirconium (Zr) and silicon carbide (SiC) claddings in Westinghouse Churchill autoclaves and the Massachusetts Institute of Technology (MIT) reactor. Additionally, the Cr coated cladding has been tested in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) and in LTR programs at the Doel 4 and Bryon 2 commercial reactors. High temperature tests at the state-of-the-art Westinghouse facilities in Churchill, PA and at Karlsruhe Institute of Technology (KIT) have been carried out to determine the time and temperature limits for the Cr coated zirconium claddings. These tests indicate that Cr coated Zr cladding can take temperatures up to about 1500°C for short periods of time without becoming totally oxidized. The main issue is the formation of the Cr-Zr eutectic at 1333°C resulting in the migration of this eutectic inward with the formation of ZrCr 2 which rapidly oxidizes to ZrO 2 on the outside of the tube. The Cr coated Zr cladding also delays the bursting of the tube, reduces the burst area, and reduces hydriding and embrittlement of the Zr which is a major benefit for reducing fuel fragmentation, redistribution, and dispersal (FFRD), the major licensing issue faced by HBHE. The manufacturing parameters for the SiC have been found to have a significant effect on the corrosion rate of the SiC in light water reactor (LWR) conditions and significant improvements have been made in the yield, quality, and oxidation resistance of the SiC cladding by identifying and tightening manufacturing process parameters. Current autoclave results for SiC composite claddings indicate that a corrosion rate of fewer than 2 micrometers per year can be achieved which meets corrosion requirements under normal operating conditions. High temperature steam oxidation tests at the state-of-the-art Westinghouse facilities in Churchill, PA and at Karlsruhe Institute of Technology (KIT) have been carried and determined that SiC cladding can withstand temperatures up to about 1800°C to 1900°C before excessive corrosion reactions begin, and that the SiC will not balloon and burst. ADOPT fuel pellets were incorporated into the Westinghouse ATF program because of their increased density and oxidation resistance. A topical report supporting the use of ADOPT pellets has been submitted to the NRC and will be approved shortly. ADOPT pellets have been a product in Europe for over 15 years. The additives work to make larger grain sizes which appear to reduce fission gas release during transients as well as increase the density of the pellet. Fuel rod and assembly design in preparation for the lead test rod (LTR) and lead test assembly (LTA) programs is underway as well as licensing efforts with the Nuclear Regulatory Commission (NRC). Finally, accident analyses coupled with economic evaluations for both operating savings as well as fuel savings have been initiated. Modular Accident Analysis Program 5 (MAAP5) calculations indicate that both Cr coated cladding and SiC composite cladding can increase the time to fuel rod loss of geometry for up to two hours longer than current Zr based cladding in a station blackout scenario. This additional time is due to the much higher oxidation resistance of the SiC and Cr coated cladding. These two hours can be used to implement additional response options instituted through the Diverse and Flexible Mitigation Capability (FLEX) program by reactor operators. Both ATF cladding options also reduce hydrogen production which dramatically reduces primary system and containment pressure and the risk of fission product release beyond containment in the unlikely event of an accident. The lower pressure in the system allows more time to feed cooling water to the core, resulting in the avoidance of fuel melting. The coping time is extended indefinitely if the modest water flow provided by FLEX continues. Experimental work on methods to rapidly fabricate SiC composite structures with high density and reduce the fabrication price of SiC fibers while maintaining a high level of performance is needed. Methods for mitigating or stopping the Cr-Zr eutectic are also needed to further improve the oxidation resistance of Cr coated Zr. Minimal (<1%) swelling of U 3 Si 2 and subsequent fission gas release has been demonstrated up to 20 MWd/kgU. Irradiation experiments with U 3 Si 2 fuel in ATR to determine these properties at 40 MWd/kgU were completed but post irradiation examinations were not done since U 3 Si 2 has been replaced by UN. UN has three issues that are being addressed. The first is increasing the oxidation resistance so that there is not excessive reaction up to ~1500°C. While UN increases the pellet density and additives to the UN postponed the temperature at which rapid oxidation occurred by ~100°C to 200°C, this is not enough, and pellet coating options are now being pursued. The second is developing a method to manufacture that does not require the multi-step process of UF 6 to UO 2 to UC to UN. Efforts are underway looking at UF 6 to UN 2 to UN and UF 6 to UF 4 to UN 2 to UN reactions. Finally, an economically acceptable process for potentially enriching the 15 N content of the nitrogen used to make UN to >95% 15N was identified though not experimentally validated. In addition to the work supported by the DOE, research and testing activities are being carried on in a world-wide effort funded by many countries such as Sweden, United Kingdom, Belgium, Netherlands, Spain, Germany, Japan, and France. This work is being facilitated through the Westinghouse led Collaboration for Advanced Research on Accident Tolerant Fuel (CARAT) program. Annual meetings were organized in 2018 and 2019 by Westinghouse as a venue for presentation of this work and to provide for the cross-fertilization of ideas among the many outstanding researchers in the ATF area. No meetings were held in 2020 and 2021 due to the COVID-19 related restrictions on traveling and gatherings. Since SiC, coated cladding, and high-density fuel options are not currently used in the nuclear industry; support from the government and industry members is needed to further the significant effort of setting new standards. The same is true for the Nuclear Regulatory Commission (NRC) which must review and approve the commercial use of these new fuels since all current regulations are oriented toward Zr/UO 2 fuel. Several meetings have been held with the NRC to generate a fast-track approach to licensing ATF using a combination of atomic modeling, in-rod sensors, and in-reactor testing. This approach was memorialized in an “Accelerated Fuel Qualification White Paper” prepared by the Accelerated Fuel Qualification Working Group lead by General Atomics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Westinghouse Accident Tolerant Fuel Phase 2B with Higher Enriched and Higher Burnup Add-On Project Final Technical Report Deliverable Volume 2

The Westinghouse Electric Company LLC (Westinghouse) accident tolerant fuel (ATF) program funded by Westinghouse and the US Department of Energy (DOE) utilized chromium (Cr) coated zirconium alloy cladding with doped UO 2 (ADOPT(TM)) and uranium silicide (U 3 Si 2 ) high density/high thermal conductivity fuel for its lead test rod (LTR) program with irradiation beginning in 2019. ADOPT is a Cr 2 O 3 +Al 2 O 3 doped UO 2 pellet with increased oxidation resistance and density, and increased resistance to fission gas release. Due to the issues with U 3 Si 2 fuel reaction in pressurized water reactor (PWR) environments, uranium nitride (U 15 N) has been substituted for U 3 Si 2 as a long-term fuel option. Cr coated cladding with ADOPT fuel is the near-term Westinghouse EnCore ® fuel product. The long-term EnCore fuel product is SiGA ® SiC/SiC composite cladding with high density/high thermal conductivity UN fuel. In 2020, the higher burnup and higher enriched and (HBHE) program was integrated into the ATF program. The objective of this expanded program is to extend ATF burnups to at least 75 MWd/kgU to economically facilitate 24-month cycles in PWRs. The ATF program now includes ADOPT fuel with enrichments >5% 235 U. Over the past several years, Westinghouse has tested the Cr coated zirconium (Zr) and silicon carbide (SiC) claddings in Westinghouse Churchill autoclaves and the Massachusetts Institute of Technology (MIT) reactor. Additionally, the Cr coated cladding has been tested in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) and in LTR programs at the Doel 4 and Bryon 2 commercial reactors. High temperature tests at the state-of-the-art Westinghouse facilities in Churchill, PA and at Karlsruhe Institute of Technology (KIT) have been carried out to determine the time and temperature limits for the Cr coated zirconium claddings. These tests indicate that Cr coated Zr cladding can take temperatures up to about 1500°C for short periods of time without becoming totally oxidized. The main issue is the formation of the Cr-Zr eutectic at 1333°C resulting in the migration of this eutectic inward with the formation of ZrCr 2 which rapidly oxidizes to ZrO 2 on the outside of the tube. The Cr coated Zr cladding also delays the bursting of the tube, reduces the burst area, and reduces hydriding and embrittlement of the Zr which is a major benefit for reducing fuel fragmentation, redistribution, and dispersal (FFRD), the major licensing issue faced by HBHE. The manufacturing parameters for the SiC have been found to have a significant effect on the corrosion rate of the SiC in light water reactor (LWR) conditions and significant improvements have been made in the yield, quality, and oxidation resistance of the SiC cladding by identifying and tightening manufacturing process parameters. Current autoclave results for SiC composite claddings indicate that a corrosion rate of fewer than 2 micrometers per year can be achieved which meets corrosion requirements under normal operating conditions. High temperature steam oxidation tests at the state-of-the-art Westinghouse facilities in Churchill, PA and at Karlsruhe Institute of Technology (KIT) have been carried and determined that SiC cladding can withstand temperatures up to about 1800°C to 1900°C before excessive corrosion reactions begin, and that the SiC will not balloon and burst. ADOPT fuel pellets were incorporated into the Westinghouse ATF program because of their increased density and oxidation resistance. A topical report supporting the use of ADOPT pellets has been submitted to the NRC and will be approved shortly. ADOPT pellets have been a product in Europe for over 15 years. The additives work to make larger grain sizes which appear to reduce fission gas release during transients as well as increase the density of the pellet. Fuel rod and assembly design in preparation for the lead test rod (LTR) and lead test assembly (LTA) programs is underway as well as licensing efforts with the Nuclear Regulatory Commission (NRC). Finally, accident analyses coupled with economic evaluations for both operating savings as well as fuel savings have been initiated. Modular Accident Analysis Program 5 (MAAP5) calculations indicate that both Cr coated cladding and SiC composite cladding can increase the time to fuel rod loss of geometry for up to two hours longer than current Zr based cladding in a station blackout scenario. This additional time is due to the much higher oxidation resistance of the SiC and Cr coated cladding. These two hours can be used to implement additional response options instituted through the Diverse and Flexible Mitigation Capability (FLEX) program by reactor operators. Both ATF cladding options also reduce hydrogen production which dramatically reduces primary system and containment pressure and the risk of fission product release beyond containment in the unlikely event of an accident. The lower pressure in the system allows more time to feed cooling water to the core, resulting in the avoidance of fuel melting. The coping time is extended indefinitely if the modest water flow provided by FLEX continues. Experimental work on methods to rapidly fabricate SiC composite structures with high density and reduce the fabrication price of SiC fibers while maintaining a high level of performance is needed. Methods for mitigating or stopping the Cr-Zr eutectic are also needed to further improve the oxidation resistance of Cr coated Zr. Minimal (<1%) swelling of U 3 Si 2 and subsequent fission gas release has been demonstrated up to 20 MWd/kgU. Irradiation experiments with U 3 Si 2 fuel in ATR to determine these properties at 40 MWd/kgU were completed but post irradiation examinations were not done since U 3 Si 2 has been replaced by UN. UN has three issues that are being addressed. The first is increasing the oxidation resistance so that there is not excessive reaction up to ~1500°C. While UN increases the pellet density and additives to the UN postponed the temperature at which rapid oxidation occurred by ~100°C to 200°C, this is not enough, and pellet coating options are now being pursued. The second is developing a method to manufacture that does not require the multi-step process of UF 6 to UO 2 to UC to UN. Efforts are underway looking at UF 6 to UN 2 to UN and UF 6 to UF 4 to UN 2 to UN reactions. Finally, an economically acceptable process for potentially enriching the 15 N content of the nitrogen used to make UN to >95% 15 N was identified though not experimentally validated. In addition to the work supported by the DOE, research and testing activities are being carried on in a world-wide effort funded by many countries such as Sweden, United Kingdom, Belgium, Netherlands, Spain, Germany, Japan, and France. This work is being facilitated through the Westinghouse led Collaboration for Advanced Research on Accident Tolerant Fuel (CARAT) program. Annual meetings were organized in 2018 and 2019 by Westinghouse as a venue for presentation of this work and to provide for the cross-fertilization of ideas among the many outstanding researchers in the ATF area. No meetings were held in 2020 and 2021 due to the COVID-19 related restrictions on traveling and gatherings. Since SiC, coated cladding, and high-density fuel options are not currently used in the nuclear industry; support from the government and industry members is needed to further the significant effort of setting new standards. The same is true for the Nuclear Regulatory Commission (NRC) which must review and approve the commercial use of these new fuels since all current regulations are oriented toward Zr/UO 2 fuel. Several meetings have been held with the NRC to generate a fast-track approach to licensing ATF using a combination of atomic modeling, in-rod sensors, and in-reactor testing. This approach was memorialized in an “Accelerated Fuel Qualification White Paper” prepared by the Accelerated Fuel Qualification Working Group lead by General Atomics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Ethanol Blends: Providing a Renewable Fuel Choice

Today, more than 21 million vehicles on U.S. roads are flexible-fuel vehicles (FFVs). These vehicles can operate on either gasoline or blends of gasoline and ethanol up to E85 (a gasoline-ethanol blend containing 51% to 83% ethanol). As a renewable fuel, ethanol offers significant advantages. It is produced predominantly in the United States, made from home-grown feedstocks, and burns cleaner than gasoline.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

DSO+T: Expanded Study Results DSO+T Study: Volume 5

The Distribution System Operator with Transactive (DSO+T) study investigates the engineering and economic performance of a transactive energy retail market coordinating a high penetration of customer-side flexible energy assets. The study seeks to answer whether such an implementation is cost effective for customers, recovers sufficient revenue for DSOs, and is equally applicable and beneficial to a range of flexible asset types, renewable generation scenarios, and market assumptions. This report volume provides a detailed set of results for the DSO+T study extending results presented in Volumes 1, 2, and 4. The engineering and economic performance of the transactive energy scheme is presented for two separate flexible asset deployments: flexible loads (HVAC units and residential water heaters) and behind-the-meter batteries. The results of each transactive case are compared to a business-as-usual case. These cases are subject to two different renewable generation scenarios, a moderate renewable generation scenario, representative of current levels of renewable generation deployment, and a future high renewables scenario, including the increased deployment of rooftop solar photovoltaic and electric vehicles. The transactive coordination scheme is shown to produce effective and stable control and decrease peak loads 9–15%. The resulting annual demand flexibility provides net economic savings of $3.3–5.0B per year for a region the size of Texas. Detailed analysis shows that net benefits were seen for a range of distribution system operator, customer, and flexible asset types. Both participating customer (with transactive flexible assets) and nonparticipating customers (with nonflexible assets) see reductions in annual utility bills and net annual energy expenses in the range of 10–16%.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

LOCOMOTIVES - Comprehensive Impact and Cost Assessment Framework of Carbon Lowering Approaches for the US Rail Freight System

The goal of this project is to develop a tool to aid railroads and other stakeholders assess and approach the decarbonization of freight rail operations by identifying new, viable low-carbon energy storage and conversion systems for future locomotive systems and how they should be deployed on the existing US freight rail network. In the first quarter, the project focused on collecting data, establishing a simulation workflow, and engaging industry through the creation of the Industry Advisory Board (IAB). In the second quarter, the project focused on selecting fuel pathways and powertrain technologies, setting performance targets, conducting a techno-economic analyses, and developing the simulation framework that would serve as the backbone of the future toolhead. The third quarter involved developing an industry-oriented interactive dashboard powered by a five-step sequential framework, as well as holding industry advisory board meetings as per the initial technology-to-market plan. In the remaining project quarters, the NUFRIEND dashboard were fine-tuned with the help of IAB member feedback and in-depth scenario analyses were conducted to support the techno-economic analysis of energy sources. Additionally, dashboard documentation, project insights, and open-source code on GitHub were prepared and released. Throughout the project, the team completed testing and analysis of all model components, integrated all initial test scenarios, and conducted stakeholder engagement. Lower-carbon drop-in fuels can be deployed as admixtures and are considered uniform across the network at a desired penetration rate, while hydrogen and battery-electric technology deployment poses a more complex problem as they require significant investments to be made in the siting of refueling/charging facilities and the replacement of locomotive fleets. Thus, strategies for locating and sizing refueling/charging facilities on a railroad’s network to meet their energy demands were developed to inform deployment decisions. To address this challenge, the Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework presents a five-step sequential framework to select O-D paths, locate facilities, reroute flows, size facilities, and evaluate the deployment for alternative energy sources that require locomotive powertrains to be converted and new refueling infrastructure to be deployed. The NUFRIEND Framework is an industry-oriented tool for simulating the deployment of new energy technologies across the US freight rail network. The framework provides a comprehensive network-level optimization and scenario simulation tool for decarbonizing the freight rail sector, addressing the uncertainties surrounding technological developments by supporting sensitivity analyses for different operational and technological parameters through a transparent and flexible input module. It offers practical alternatives to diesel locomotives and can be applied for any railroad considering the specific network structure and freight demand, outputting evaluation metrics for the associated emissions and costs relative to diesel operations. A number of relevant simulation scenarios were run and analyzed for key insights on the value of different alternative technologies for freight rail decarbonization. The project developments and findings have been presented at numerous conferences and events.

08 HYDROGEN↗

DOE OSTI2026

Artificial Intelligence-Driven Management of Sustainable Energy Resources: Visibility, Operation, and Control

The rapid global transition toward sustainable energy resources (SERs) is reshaping how modern power systems are observed, optimized, and controlled. While SERs have significantly advanced decarbonization, their weather dependence, variability, and inverter-dominated characteristics challenge traditional, centralized, and deterministic grid operation. At the same time, the proliferation of high-resolution data from inverters, smart meters, and sensors offers unprecedented visibility into system dynamics. Yet, it also exceeds the analytical capability of conventional model-based approaches. Artificial intelligence (AI) provides a new foundation for addressing these challenges by bridging physical laws with data-driven learning, enabling accurate state awareness, adaptive operation, and coordinated control across distributed assets. This article examines how AI transforms the management of SER-rich power systems along three critical dimensions: 1) enhancing visibility by inferring behind-the-meter (BTM) activities, assessing SER flexibility, and reconstructing system states from sparse or noisy measurements; 2) improving operation through AI-enhanced SER service provision, volt/var control (VVC), and dynamic operating envelopes (DOE) for efficiency and security; and 3) advancing control by embedding learning-based intelligence into inverter coordination, voltage and frequency regulation, and long-term dispatch. Together, these developments reveal how AI can convert the variability of SERs from an operational challenge into a source of flexibility, resilience, and intelligence, paving the way toward sustainable, adaptive, and self-optimizing power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Exploring Grid-Interactive Efficient Building Strategies for Laboratories Through Energy Modeling

Laboratories are often overlooked in demand flexibility research due to constraints on their operations as mission critical facilities, despite the major role they play in an organization's emissions. Laboratories consume 3-4 times more energy than a typical office building and are commonly the largest energy users on any campus. Consequently, most laboratories in the United States are significant contributors to their organization's carbon footprint if their energy needs are met through the combustion of fossil fuels. As part of the initiative to decarbonize laboratories, this report documents an analysis on specifically grid-interactive efficient building (GEB) opportunities for reducing energy costs and emissions associated with laboratory operations. The goal of this initiative was to provide a case study and guidance on how to use OpenStudio and REopt as modeling tools for GEB technologies and strategies in laboratory environments across different climate zones in the United States. The analysis found that efficiency-based GEB strategies had the most significant impact on laboratory operations, while load-shedding and load-shifting GEB strategies produced smaller results. The culmination of these approaches applied across all five climate zones generated on average: 1) 28% energy cost savings and 30% greenhouse gas (GHG) emissions reductions, and 2) 4% enhanced energy cost savings under a time-of-use (TOU) pricing schedule compared to traditional pricing schemes. Grid-interactive efficiency building measures were found to produce the greatest energy savings in both electricity and natural gas, particularly in regions with high electrical loads, such as warm climates for cooling. Laboratories that had high levels of natural gas consumption, meanwhile, experienced the greatest emission reductions. The report concludes with an analysis on the opportunities for flexible loads in lab spaces and how small-scale measures in addition to opaque pricing structures for peak demand could become barriers to demand flexibility planning. The report also explores how electrifying laboratory buildings with heat pumps could reduce energy costs and GHG emissions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Using probabilistic solar power forecasts to inform flexible ramp product procurement for the California ISO

How can independent system operators (ISOs) take advantage of probabilistic solar forecasts to lower generation costs and improve reliability of power systems? We discuss one three-step approach for doing so, focusing on how such forecasts might help the California Independent System Operator (CAISO) prepare unexpected net load ramps, where net load equals gross demand minus wind and solar production. First, we enhance an existing solar forecasting system to provide well-calibrated hours-ahead probabilistic forecasts. We then relate the degree of uncertainty reflected in the forecasted prediction intervals (independent variables) to error distributions for net load ramp forecasts for the CAISO real-time market (dependent variable) using machine learning and quantile regression. Projected ramp forecast errors conditioned on solar uncertainty are translated into flexible ramp requirements that therefore reflect real-time meteorological and solar conditions, improving on typical ISO procedures. Detailed descriptions are provided on the quantile regression and kth-nearest neighbor categorization methods for accomplishing that translation. Finally, a multiple time-scale look-ahead market simulation model is applied to a 118-bus IEEE Reliability Test System, modified to represent the CAISO generation mix and demand distributions. The model runs quantify how solar-conditioned ramp requirements can, first, decrease operating costs by reducing requirements compared to often conservative unconditional methods and, second, decrease generation scarcity events and consequently improve reliability by increasing flexibility requirements at times when unconditional forecast-based requirements understate actual ramp uncertainty. Solar-conditioned ramp requirements are found to reduce generation operating costs by about 2% for the test system (which would be equivalent to over $\$100$ million per year for a CAISO-size system).

14 SOLAR ENERGY↗

DOE OSTI2020

A Robust Hierarchical Dispatch Scheme for Active Distribution Networks Considering Home Thermal Flexibility

Distribution networks are changing from passive absorbers of electric energy to active distribution networks (ADNs) capable of operating and participating in electricity markets. In the context of residential microgrids, which is a type of ADNs, aggregated home heating, ventilation and air-conditioning (HVAC) loads present a key opportunity to drive operational and economic objectives, facilitate high renewable energy penetration, and enhance both system resiliency and flexibility. A robust, hierarchical dispatch scheme is developed and presented in this paper, which connects an upper level multi-phase distribution optimal power flow (DOPF) to a lower level model predictive control (MPC)-based HVAC fleet controller. The approach is tested and verified on a modified IEEE 13 bus system in an intraday market application. The results demonstrate that the proposed hierarchical dispatch scheme is able to drive both economic and operational objectives for the ADN operator.

Rooks, Cody D.↗

DOE OSTI2021

Community-scale interaction of energy efficiency and demand flexibility in residential buildings

Demand-side management (DSM) strategies, including energy efficiency (EE) and demand flexibility (DF), contribute to cost-effective operation of the electricity grid. From a system-level perspective, such programs reduce costs, enhance reliability, and reduce network issues. Similarly, DSM programs help participating customers reduce utility bills while maintaining occupant comfort. Understanding the relationship between EE and DF is key to realizing the full potential of DSM programs. In this study, we modeled an all-electric residential community based on a 498-home community that is planned for construction in Fort Collins, Colorado in the United States. We used this community model to study the relationship between different EE measures, including building envelope upgrades and smart appliances, and DF enabled by a home energy management system (HEMS) responding to a time-varying tariff. Various EE levels in the homes – code-minimum, zero energy ready, and even higher levels of envelope efficiency – were simulated. DF is enabled by the HEMS, which coordinates behind-the-meter resources, including flexible building loads, PV, and home battery systems, to minimize utility bills while maintaining occupant comfort. When comparing to the code-minimum homes, EE upgrades alone reduce HVAC energy use during peak hours by up to 50% and the HVAC utility bill by up to $312/year. With the addition of HEMS, the average daily peak demand can be reduced by up to 0.58 MW or 1.2 kW/home in the higher envelope efficiency homes. The combination of EE upgrades, HEMS, and home battery systems is expected to save homeowners up to $590/year while increasing community load flexibility. However, HEMS and home battery systems are less effective in increasing the DF in the more efficient homes due to the lower load.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services

closed-loop validation↗

DOE OSTI2025

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services

14 SOLAR ENERGY↗

DOE OSTI2024

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services: Preprint

closed-loop validation↗

DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗

DOE OSTI2020

Electrolytically Assisted Surface Decontamination (EASD{sup TM}) for POCO Operations - 20282

NNL in collaboration with C-Tech Innovation Ltd and Sellafield Ltd has been exploring innovative technologies to enable a significant reduction of radiological hazards within facilities during the Post Operational Clean Out (POCO) phase of a nuclear plant's life cycle. Reducing the hazard by effectively decontaminating plants in-situ during POCO delivers huge cost reductions for future decommissioning operations. These cost reduction benefits are realized by reducing the number and complexity of remote operations as well as lowering the long-term waste disposal costs. Whilst chemical decontamination can achieve the desired level of decontamination, applying aggressive chemical reagents is hazardous, potentially difficult to control and requires there to be complimentary effluent treatment and waste routes. This work has aimed to develop flexible and controllable decontamination processes which could be operated without the additional complexity and issues associated with chemical decontamination. The processes needed to be relatively fast and effective to minimize the time operators would spend in an active area. In addition, there was a driver to produce decontamination methodologies which generated a secondary waste compatible with current routes and which takes advantage of current waste capacity. The strategy therefore was to come up with a solution that works with, rather than against, the science and engineering behind process plants at Sellafield. Electrolytically Assisted Surface Decontamination (EASD{sup TM}) is an innovative electrochemical decontamination process (developed by NNL and C-Tech Innovation Ltd) that can remove activity from contaminated metal in very short time periods. Application of the patented electric waveform to the surface when treating contaminated metal with nitric acid has been shown to significantly enhance the decontamination performance. When compared to proposed baseline washout procedures at Sellafield, the only change to the process is the applied electrical waveform which is temporary and controllable. The current causes dissolution of the metal surface being decontaminated which leads to activity transferring from the plant item into the nitric acid effluent stream. This innovation has the potential to transform the POCO process and allow a nitric acid based washout approach to deliver POCO quickly and cost effectively within the existing infrastructure. Several devices have now been designed that incorporate this EASD{sup TM} technology and enable the decontamination process to be applied to a range items commonly identified as being contaminated during nuclear decommissioning programmes such as pipework, tanks and hotspots of walls/floors. Inactive and active laboratory-scale testing has been completed using both simulated and 'real-life' contaminated (low level waste) metallic items retrieved from different nuclear sites. Active trials demonstrated that contaminated items could be treated to free release levels within minutes. Engineering scale tests are currently being performed, with guidance from Sellafield's system engineers and plant managers, to provide the necessary re-assurance the designed devices could be successfully deployed in an on-plant scenario. The final stage of this development work is to carry out an active demonstration of the decontamination technology on Thorp at Sellafield. This paper aims to highlight progress made to date with the EASD{sup TM} technology and, more specifically, the development of an in-situ decontamination device for deployment within radioactive pipework. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

A systematic feature extraction and selection framework for data-driven whole-building automated fault detection and diagnostics in commercial buildings

In data-driven automated fault detection and diagnostics (AFDD) modeling for building energy systems, feature engineering is a critical process of extracting information from high-dimensional and noisy sensor measurement and turning it into informative and representative inputs or features for data-driven modeling. However, few studies specifically discuss the feature engineering, especially the interactions between feature extraction and feature selection in whole-building AFDD. We developed a systematic feature extraction and selection framework for whole-building AFDD. In this framework, features are aggressively extracted from raw sensor data using statistical feature extraction techniques with various window sizes and statistics. With many features extracted, a hybrid feature selection algorithm that combines the filter and wrapper method then selects the best feature set. The framework considers diversity in the duration of fault behavior among fault types in whole-building AFDD, thus achieving high model generalization. We implemented our developed framework in a virtual testbed calibrated with measured data from Oak Ridge National Laboratory's Flexible Research Platform designed to mimic the operation of a typical small commercial building. The AFDD model is trained by the simulation data generated from the virtual testbed. The results show that (1) the developed framework improves the generalization of the AFDD model by 10.7% compared with literature-reported feature extraction and selection methods and (2) features with diverse window sizes and statistics are selected, providing insight into physical systems beyond the current understanding of buildings and faults and improving the detection and diagnostics of multiple fault types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Leveraging concentrating solar power plant dispatchability: A review of the impacts of global market structures and policy

Concentrating solar power (CSP) integrated with thermal energy storage delivers flexible and dispatchable power, which is an increasingly valuable quality as electricity systems integrate growing penetrations of variable renewable energy. Valuing and compensating CSP's dispatchability and flexibility requires electricity market structures and policies that appropriately remunerate generation during high-value portions of the day. In this paper, we review previous analyses of CSP economics and deployment, and we find that continued CSP growth will require valuation mechanisms that appropriately compensate for CSP's flexibility during both plant design and plant operation. We then review market structures that drive CSP operations and dispatch in jurisdictions where CSP is being developed, with perspectives from Spain, Chile, Australia, Morocco, South Africa, the United States, China, and the United Arab Emirates (Dubai). Despite broad agreement that CSP's dispatchability provides value to electricity grids, countries' policies for remunerating and leveraging such dispatchability varies widely. As deployment of CSP and variable renewable energy grows, it will be increasingly important to redesign current integration policies to signal the delivery of CSP's grid services more appropriately.

14 SOLAR ENERGY↗

DOE OSTI2026

Avoidance of disruptions on KSTAR due to vertical displacement events via novel real-time stability assessment

Disruption avoidance via the DECAF approach has been achieved on KSTAR using a novel real-time vertical stability assessment and a multiactuator feedback control strategy. The development of disruption avoidance strategies with reactor-relevant reliability is an urgent activity, enabling future fusion power plants. The stability metric employed is based on a new formulation of a vertical force gradient balance metric evaluated across the poloidal cross section of the plasma, with parameters tuned using historical data. Evaluation of this metric on a validation set of 400 recent KSTAR shots indicates >82% of Vertical displacement events can be avoided via feedback control. Essential to its calculation is the two-dimensional toroidal current density distribution in the plasma. Measurement of this profile faster than fully-converged equilibrium reconstructions can deliver is found to improve forecaster performance and is achieved with a surrogate model that takes as input magnetic diagnostic measurements and outputs the current profile on a basis comprising the top principal components of historical current profiles (from past equilibrium reconstructions). This method solves the non-uniqueness problem typically faced when reconstructing current profiles directly from diagnostics, while improving computational time and accuracy. On average, profiles produced by this model reach coefficients of determination of >0.99 with respect to those from equilibrium reconstructions. The avoidance actuators employed include poloidal field coils and an electron cyclotron current drive system. The multiactuator approach, as shown in this first demonstration, allows disruption avoidance while minimizing impact to operational performance. This ability, along with its flexibility and speed, makes this new approach an attractive option for avoiding these types of disruptions in reactors.

Tobin, Matthew [Columbia Univ., New York, NY (Unit↗