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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evaluation of DED and LPBF Fe-based Alloys Process Application Envelopes based on Performance, Process Economics, Supply Chain Risks, and Reactor-specific Targeted Components

The U.S. Department of Energy (DOE), Office of Nuclear Energy (NE), Advanced Materials and Manufacturing Technologies (AMMT) program aims to develop extreme-environment materials solutions for use in the deployment of advanced nuclear reactors and the sustainment of the current fleet. To achieve this objective, a combination of experiment, a computational tool, and machine learning (ML) for the design of materials is adopted for the maturation of materials for nuclear technology. Through advanced manufacturing techniques such as laser powder bed fusion (LPBF) and laser powder direct energy deposition (LP-DED), components with complex geometries can be fabricated with reduced time and effort. Such advanced manufacturing methods can also provide the opportunity to improve materials performance through optimized microstructures and mechanical properties. However, existing engineering alloys are not always well suited for fabrication with additive manufacturing (AM), as their compositions have been tuned to optimize fabrication via conventional methods. Thus, similar alloys with modified compositions that are better suited for AM can be studied for improved performance. Over the past three years, the AMMT teams from Argonne National Laboratory (ANL) and Pacific Northwest National Laboratory (PNNL) studied various known Fe-based alloys by evaluating their initial printability using LPBF, and an AMMT-developed down-selection and decision matrix reduced the number of alloys to be studied from six to three in fiscal year (FY) 2024. Additionally, in FY 2024, for parallel evaluation, these three alloys were studied using LPDED. While LPBF is better for small- to medium-sized components with high detail and internal features, LP-DED combines a material feed system to place the powder onto the exact spot where the laser will melt the material. This AM method can be easily scaled to extremely large components and provides high build rate speeds compared to those of conventional LPBF systems. Additionally, DED is a better choice for complex geometries and compositional gradients.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Representing the Future Role of Hydropower and Pumped Storage Hydropower (PSH) in Electricity Planning Tools

Existing tools for long-term electric sector planning struggle to represent hydropower's nuanced site-specific technical and operating characteristics, which depend on technical specifications as well as water management practices and regulations. As a result, long-term planning models and tools insufficiently characterize hydropower value and incentives, and they cannot fully represent the role hydropower can play in a future electricity system that could include a high penetration of variable wind and solar generation, battery storage, and other low-carbon technologies. This presentation demonstrates the culmination of a multi-year effort to enhance hydropower representations in electricity planning models at the National Renewable Energy Laboratory (NREL), as part of the U.S. Department of Energy (USDOE) HydroWIRES Initiative. New modeling techniques are demonstrated using the NREL Regional Energy Deployment System (ReEDS), an open-access electric sector capacity expansion model used extensively in a wide range of technology deployment and integration analysis, including the 2016 USDOE Hydropower Vision. ReEDS uses a least-cost optimization approach to understand investment and operation of electricity generation, storage, and transmission technologies under future scenarios of electricity technology innovation, demand, policy, and other sectoral drivers. ReEDS was modified to better represent value and opportunities for both pumped storage hydropower (PSH) and hydropower systems without pumping. We incorporated a new national closed-loop PSH resource and cost assessment to explore new PSH deployment opportunities and added plant-level data to better represent the existing PSH fleet. New upgrade pathways enable opportunities for enhanced hydropower flexibility by adding pumps, upgrading dispatchability, increasing capacity, or increasing energy availability. The model was also modified to better represent the value of long-duration energy storage beyond diurnal time scales, allowing both hydropower and PSH to better balance energy supply and demand variations in high-renewable systems. These new features are demonstrated under reference and high-renewable futures and a range of sensitivity scenarios to understand which hydropower and PSH deployment and upgrade opportunities are the most attractive. These scenarios indicate potential for new closed-loop PSH deployment and for hydropower flexibility improvements to have important impacts on long-term electricity system emissions and economic outcomes. Increasing flexibility of the existing hydropower fleet can reduce the need to invest in new flexible grid technologies and help achieve decarbonization goals. Systems with sufficient energy storage could also be valuable for balancing seasonal differences in renewable energy availability, particularly from solar energy. The methods developed for ReEDS and subsequent scenario results reveal important considerations for future hydropower and grid system planning, and all data and code is freely available in a public code repository for use throughout the hydropower industry.

capacity expansion↗
DOE OSTI2024

Review of Technical Photovoltaic Key Performance Indicators and the Importance of Data Quality Routines

Technical key performance indicators (KPIs) are important metrics used to assess and quantitatively summarize various aspects of photovoltaic (PV) systems, including long-term performance, economic viability, and carbon footprint. Herein, a group of experts of the International Energy Agency's Photovoltaic Power Systems Programme Task 13 collect and describ the most important technical KPIs used in the industry. Thereby, a set of best practices for reliably handling PV system data is presented and the impact of data quality and climatic variability on KPI calculation is investigated. Further, the effective use of technical KPIs allows triggering data-driven and informed decisions to optimize PV systems and providing a comprehensive overview of how PV systems operate across different conditions and climates. With the worldwide growth of the PV industry, more companies operate/own PV systems in different regions, where the climatic and seasonal profiles differ. This requires context-aware evaluation of KPIs, or the judicious application of multiple KPIs, to ensure that each asset is evaluated correctly. Beyond that, there is untapped potential in the utilization of KPIs through geospatial mapping and extrapolation of fleet KPIs. This study demonstrates that the uncertainty in KPI estimation is not well understood and depends on data quality, climatic variability, and system configuration.

14 SOLAR ENERGY↗
DOE OSTI2024

The Debate on Vehicle Triad: Examining the Utilization Patterns of Gasoline, Hybrid, and Electric Vehicles in Households

Light-duty vehicles contribute to approximately half of the transport sector's emissions, a sector challenging to decarbonize owing to the autocentric nature of many American cities. The U.S. Department of Transportation's blueprint outlines three key decarbonization strategies: increasing convenience, improving efficiency, and transitioning to zero-emission vehicles. Among these, the adoption of Electric Vehicles (EVs) offers a promising opportunity to reduce emissions from light-duty vehicles, which are predominantly gasoline-powered. Although substantial literature identifies and addresses factors influencing EV adoption, understanding their utilization within households who own vehicles with mixed fuel types is crucial for accurately assessing their environmental benefits. This paper addresses two key questions: (a) Are EVs utilized more, equally, or less than gasoline vehicles (GVs) and (b) What factors influence mileage utilization patterns in households with multiple vehicle fuel types, accounting for substitution and complementary effects? Analysis of 2022 National Household Travel Survey (NHTS) data indicates that EVs are utilized more than GVs within households that own multiple mixed fuel fleets. Findings reveal that households with a higher number of younger individuals and multiple workers use EVs more extensively, and those with older adults and larger households with multiple vehicles tend to use GVs more. Rural households have higher use of hybrid vehicles (HVs). The study identifies a substitution effect between EVs and GVs, while complementary relationship between HVs and EVs, suggesting nuances in vehicle utilization patterns. This nuanced understanding of vehicle utilization patterns informs the development of targeted policies and infrastructure investments to optimize household transportation efficiency.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Real time operation of high-capacity electric vehicle ridesharing fleets

We study the feasibility of using electric vehicles in online, high-capacity ridepooling systems. Prior work has shown that online algorithms perform well for centrally-controlled, high-capacity ridepool systems. First, we propose a mixed integer linear program to expand past algorithms on ridepooling to electric vehicle fleets with the objective of scheduling vehicle charging to maintain sufficient fleet sizes at various times of day. Then we show a faster, scalable algorithm with similar performance that is practical for full-scale systems. Furthermore, our contributions reinforce the importance of having knowledge and estimates of future demand even when operating in the online setting.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Digital Transformation for the Existing Fleet: Where to Start?

To remain economically viable in today’s electricity marketplace, nuclear power plants are replacing old analog equipment with modern digital tools. Having information available in an electronic format allows most work processes to become more efficient by automating simple, time-consuming tasks. However, with thousands of routine work processes performed every day, it can be difficult for the plants to know where to begin. We partnered with a nuclear utility to develop a novel assessment tool that measures seven health indicators for each work process performed, providing a rapid digital status report of the plant. The assessment tool is inexpensive and user-friendly, administered remotely, and automatically customized to each employee. Data from 167 employees representing different perspectives were analyzed to identify optimal candidates for digital initiatives that yield the highest payback for increased process efficiencies. We ranked by a priority index to ensure that processes with a good combination of time savings and digital opportunity were at the top. The focus was on determining a maximum investment to ensure that the cost savings from these initiatives are positive over a specified period. We identified potential cost savings of $2.6m, $1.3m and $1.2m for our top priority processes. By using our novel assessment tool to determine the digital status of the plant’s work processes, they were provided with a starting point for target candidates that would most benefit from a digital initiative. Our analysis helps stakeholders understand the financial impact of digital initiatives and identify maximum investment amounts when seeking technical solutions.

assessment↗
DOE OSTI2023

Grid-Integrated Production of Fischer-Tropsch Synfuels from Nuclear Power

Idaho National Laboratory (INL) investigates the relative economic profitability of an integrated energy system (IES) coupling an NPP with a synfuel production process at selected case study locations across the United States. In the synfuel IES, a high-temperature steam electrolysis (HTSE) plant is thermally and electrically coupled with an NPP to produce zero-carbon hydrogen. The synthetic fuel is produced from this H 2 combined with a CO 2 supply using the reverse water gas shift process followed by the Fischer-Tropsch (FT) reaction. This analysis considers a system in which the CO 2 is sourced from regional CO 2 emitters via the construction and operation of pipeline-based CO 2 supply networks. Locating the FT plant at the same site as the NPP and HTSE plants enables the NPP to provide zero-carbon heat and power to the HTSE plant and zero-carbon power to the FT plant as well as avoid the requirement for long-distance H 2 product transport from the HTSE plant to the FT plant. Hydrogen storage is used to enable the NPP to dispatch power to the electrical grid (instead of the HTSE plant) when grid demand increases, thus enabling the FT plant to continue to operate in a steady-state production mode. The ability to cease hydrogen production for several hours within each day enables the NPP to provide power to the grid to balance the electricity market during peak periods and maximize revenues for the nuclear synfuel IES. The FT process design considered has a 99% carbon conversion efficiency. The use of nuclear energy and nuclear energy-derived hydrogen enables synfuel production to achieve this high level of carbon utilization. Additionally, the life-cycle carbon emissions of the nuclear-based synfuel production process are very low, with WTW emissions of approximately 25 gCO 2 e/MJ, including steam credits (generated from FT process excess heat), and approximately 7 gCO 2 e/MJ, if steam credits are excluded. This compares favorably with the WTW emissions of 90.5 gCO 2 e/MJ for a compression-ignition, direct injection (CIDI) vehicle with a fuel economy of 31.6 miles per gallon gasoline equivalent (MPGGE), using low-sulfur diesel produced using conventional petroleum production and refining processes. Several NPPs in various regions of the U.S. are considered as case study analyses. Supply locations and transportation via pipeline of the CO 2 feedstock to the NPP site are analyzed through the National Energy Technology Laboratory (NETL) CO 2 Transport Cost model. The team finds that the amount of CO 2 generated by different sectors is sufficient for the synfuel production process at all locations considered. The CO 2 transportation costs are functions of the distance of the source to the NPP location, the CO 2 capture cost at the source, and the quantity of CO 2 transported. Historical electricity prices for the NPP case study locations are collected and analyzed. Monthly average prices, price range, and duration of negative-price periods vary among these locations. For each location, an auto-regressive moving average (ARMA) model is trained on historical electricity price data. ARMA validation is done to ensure the synthetic price distributions represent one of historical prices with high fidelity. Synthetic time series from these ARMA models are used in a coupled dispatch and system optimization in the Holistic Energy Resource Optimization Network (HERON) to compute the differential net present value (NPV) of the IES. The team finds that this econometric is positive, ranging from $14M–1.3bn (2020) depending on the location. The optimal synfuel IES configuration to obtain this increase in NPV often maximizes the size of the synfuel production process with regards to the size of the NPP. However, the team shows that the NPP still plays a stabilizing role for the grid: In periods of high prices and high loads, more electricity from the NPP is sent to the grid. A high variability of electricity prices and extreme maximum prices tend to drive up electricity production. While it requires significant investment, the synfuel IES could increase the economic profitability for the existing fleet of LWRs across the country while still maintaining the grid stabilizer role of NPPs. During its lifetime, the main costs for the nuclear synfuel IES are the carbon feedstock transportation costs, followed by the capital expenses (CAPEX) and operation and maintenance (O&M) costs while the revenue comes first from the IRA H 2 production tax credit (PTC) and then from the sales of synfuel products. The profitability of the synfuel IES is most sensitive to the value of the hydrogen PTC and the synfuel products as well as the cost of the carbon feedstock, highlighting the importance of governmental incentives regarding hydrogen, carbon emissions, and synfuel in driving the deployment of future nuclear synfuel IESs.

08 HYDROGEN↗
DOE OSTI2021

Dynamic Simulation of a Sub-Critical Coal Fired Power Plant

In order to address the demanding operating conditions for remaining coal-fired power plants, a dynamic model and a suite of tools have been developed for studying load cycling and to find optimization opportunities. A sub-critical steam cycle power plant was modeled in a flow-sheet modeling tool, APROS™. The model represented the firing system, economizer, evaporator, superheat, and reheat systems. Four loads from 100% TMCR to 25% TMCR were calibrated and tested such that low-to-high cycling could be studied. The model was run through various load cycles; one of which is presented here. This modeling is a prototype for general use in developing cutting edge controls products and for maximizing economic, low-emissions, and efficient operation of the existing coal power fleet.

Braun, Timothy↗
DOE OSTI2022

Westinghouse advanced fuel management strategies leveraging high enrichment and high burnup fuel to optimize PWR economics

In the US, nuclear power plants have been focused on increasing electricity generation for over three decades via longer operating cycles, reduced number of outages and duration, and the implementation of power up-rates. The potential for zero-carbon emission credits and other carbon-reduction initiatives further makes nuclear power utilities to focus on increasing generation capability. Longer operating cycles provide increased energy generation and enable economic savings to nuclear utilities when the increase in fuel loading required to achieve the extended cycle energy target and resulting increase in total fuel cost is offset by the savings from outage avoidance and reduced replacement power costs. For the current licensed limits of 5 w/o {sup 235}U enrichment and 62 GWd/tU peak pin burnup, higher power density PWR plants, which are prevalent in the PWR fleet, require an excessively penalizing fraction of feed fuel assemblies to operate for the extended cycle duration, with inevitably poor fuel use and fuel cycle economics that cannot be counterbalanced by the savings on outage cost avoidance. To overcome this barrier, the nuclear industry is pursuing development of high enrichment/high burnup fuel technology ({sup 235}U enrichment up to 8 w/o and peak pin burnup up to 75 GWd/tU) which increases fuel energy generation capability and can enable high power density plants to achieve positive economics on 24-month cycle of operation. This paper presents advanced fuel management strategies developed by Westinghouse to enable transition of PWR reactors from 18-month to 24-month cycle of operation, with and without a core thermal power uprate, which are then used as basis to assess the economics of a direct transition from 18 to 24-month cycles with high enrichment/high burnup fuel. The results show that these fuel management strategies, especially if coupled with thermal power up-rates, present the opportunity for substantial economic benefits to utilities. The systematic review of fuel management strategies presented can provide an illustrative reference for decision makers as they consider how to maximize nuclear energy generation economically. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Enabling a Physical Twin for Control Methods Evaluation

Advanced nuclear reactors play an important role in the energy future of the United States and the rest of the world. They are designed and operated based on a different model than that of the current operating fleet, thus enabling deployment in remote locations and allowing for safe semi-autonomous or autonomous operations. Such characteristics require the development of a new reactor control paradigm. A significant factor in the development of control technologies and methods is integration of the various technologies and methods with each other and with hardware (both reactor system hardware and control hardware). A recent workshop on control of advanced reactors identified the lack of a flexible, expandable software/hardware infrastructure to enable such integration as a key gap. A previous phase of the current effort involved developing and demonstrating the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) platform, which is capable of integrating autonomous-control-enabling technologies and methods, without the constraints imposed by existing software solutions. This platform will enable advanced reactor developers to deploy and test any developed technologies and methods by employing a common framework, and to couple them with their own models and hardware. The present phase of this effort entails using the Microreactor Automated Control System (MACS) platform, which was developed by the U.S. Department of Energy (DOE) Microreactor Program, to serve as a control method testbed. MACS can be used by advanced reactor developers to integrate their control related research activities with any reactor system. For the present effort, MACS was customized to mirror Idaho National Laboratory (INL)’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and COMMAND was leveraged to enable MACS to emulate the physics of MARVEL, thus positioning MACS as a physical twin of MARVEL.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Demand Driven Cycamore Archetypes

Future nuclear fuel cycle options may present advantages over today’s once-through fuel cycle. Nuclear fuel cycle simulation tools assess the performance of those fuel cycles as well as the dynamics of long-term technology transitions. In many nuclear fuel cycle simulation tools, it has historically been the responsibility of the user to manually define facility deployment schemes and all facility parameters. While this is straightforward in simple fuel cycles, transitions from one fuel cycle to another can be more complex. In particular, deployment schemes for supportive fuel cycle facilities beyond the reactor become complex if the analyst desires to avoid gaps in the nuclear fuel and power supply chain during those transition scenarios. As nuclear fuel cycle analysis approaches questions regarding the feasibility and performance of the deployment schemes and technology choices during technology transition, automation of this historically manual process is necessary. The main objective of this work was to develop and demonstrate Cyclus automation capabilities toward key nuclear fuel cycle transition scenarios. While deploying reactors to meet power demand is trivial, and existed in the earliest versions of CYCLUS, automated, predictive deployment and decommissioning of other facilities is more complex. These include mining, milling, enrichment, fuel fabrication, reprocessing, and others. For example, a balanced closed fuel cycle may require ensuring that there is enough fast reactor fuel for their operation and may drive deployment of a fleet of light water reactors. This concern comprises the main challenge that drove the project effort. The Demand-Driven Cycamore Archetype project (NEUP-FY16-10512) aimed to develop CYCAMORE demand-driven deployment capabilities and thereby automate transition scenario definition. The developed software package, d3ploy, in the form of a CYCLUS Institution agent, deploys Facilities to meet the front-end and back-end demands of the fuel cycle. The University of South Carolina and the University of Illinois applied multiple algorithmic approaches to this challenge. This project developed an in situ demand-driven development schedule calculation through non-optimizing, deterministic-optimizing, and stochastic-optimizing algorithms as CYCLUS archetypes and demonstrated these new archetypes in program-supporting fuel cycle transition scenarios. Both objectives were achieved. This report documents the results and deliverables obtained toward these achievements in detail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

CSP Plant Optimization Study for the California Power Market (“CalCSP”) (Final Technical Report)

Concentrating Solar Power (CSP) with thermal energy storage offers a unique and strategic opportunity to support California’s clean energy transition. Unlike photovoltaic (PV) systems, CSP with thermal storage can generate electricity after sunset and during periods of high demand, making it a valuable complement to intermittent renewable resources. CSP also provides synchronous, inertia-contributing generation, long-duration storage, and flexible dispatch—capabilities increasingly important as thermal plants retire. This report summarizes the findings of the CSP Plant Optimization Study for the California Power Market or “CalCSP study,” which evaluated the technical, economic, environmental, and policy factors that influence the deployment of CSP technologies in California. The CalCSP study was conducted to assess how CSP can contribute to California’s long-term decarbonization goals while enhancing grid reliability, supporting local economic development, and making efficient use of land and transmission resources. It draws on detailed modeling of CSP performance and costs, site suitability analysis, policy reviews, and stakeholder engagement across utilities, regulators, developers, and community organizations. The analysis focuses on mature molten-salt tower technology and incorporates lessons learned from the global CSP fleet, distinguishing today’s CSP from earlier first-of-a-kind projects in the U.S. The findings support a more prominent role for CSP in California’s evolving clean energy landscape. With strategic planning, targeted policy support, and continued cost improvements, CSP can complement PV and batteries to deliver reliable, around-the-clock clean electricity—especially in areas with high solar resource and constrained grid capacity.

14 SOLAR ENERGY↗
DOE OSTI2022

Cognitive Aging as a Human Factor: Effects of Age on Human Performance

Nuclear power plant (NPP) control room operators must make ongoing computations and decisions that maximize production and ensure safety, which places a high cognitive burden on the operators. How cognitions such as attention, visuospatial ability, and working memory interact with socio-technical systems to achieve optimal operations is well studied. However, there is an absence of research that examines how cognitive functioning within the NPP control room environment is moderated by developmental aging processes. This is of critical importance because different types of cognitive actions are known to develop and peak at different times across the adult life span, and it is becoming increasingly clear that there is no age at which all cognitive faculties operate at maximum capacity. Thus, given that NPPs are experiencing an aging workforce, it is vital to identify how mission critical cognitions change with age. This paper reviews implications of aging on reactor operators in the current and new fleet. We highlight lessons that can be learned from state-of-the-art human factors research that considers aging, lessons from the large cognitive aging literature, and lessons from aging workers in other industries that use sophisticated socio-technical systems, such as aviation. We also consider the important subject of aging effects versus expertise and present preliminary data that support the premise that age of operator is linked to effective and efficient operations but that this relationship may be moderated by level of operations expertise. In conclusion, we apply these lessons to future considerations for aging research in current nuclear operations and with the advent of advanced modernized control rooms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
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

Analysis of Truck Platooning on Rural Highways

An analysis by the National Laboratory of the Rockies on truck platooning technology used on Ohio highways found that truck platooning operated for 40% of driving distances, showcasing its potential to enhance freight efficiency and safety. While energy savings were evident, further optimization of gap distances and operational consistency is needed to fully evaluate fuel savings benefits across diverse driving conditions. While more study is needed, advanced connected and automated vehicle technologies such as platooning demonstrate significant promise for transforming commercial vehicle efficiency and operations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Packetized Energy Management: Coordinating Transmission and Distribution (Final Report)

The project Packetized Energy Management (PEM): Coordinating Transmission and Distribution was part of the ARPA-E NODES program from 2015 to 2023. The high-level goal of the project was to develop and demonstrate novel, scalable, and impactful technologies related to the coordination of networked distributed energy resources (DERs). By demonstrating responsive means by which fleets of DERs could be coordinated to enhance grid operation and reliability, the U.S. could accelerate renewable integration and electrification efforts and meet decarbonization goals.

25 ENERGY STORAGE↗
DOE OSTI2020

Microsimulation of Energy and Flow Effects from Optimal Automated Driving in Mixed Traffic

In this paper we study the energy and traffic impact of a proposed Anticipative Cruise Controller in a PTV VISSIM microsimulation environment. We dissect our controller into two parts: 1. the unconnected mode, active when following a human-driven vehicle, and 2. the connected mode, active when following another automated vehicle equipped with connectivity. Probabilistic constraints balance safety considerations with inter-vehicle compactness, and vehicle constraints for acceleration capabilities are expressed through the use of powertrain maps. Emergent highway traffic scenarios are then modeled using time headway distributions from empirical traffic data. To study the impact of automation over a range of demands of free-flow to stop-and-go, we vary vehicle flux from low to high and vary automated vehicle penetration from low to high. When examining all-human driving scenarios, network capacity failed to meet demand in high-volume scenarios, such as rush-hour traffic. We further find that with connected automated vehicles introduced, network capacity was improved to support the high-volume scenarios. Finally, we examine energy efficiencies of the fleet for conventional, electric, and hybrid vehicles. We find that automated vehicles perform at a 10%-20% higher energy efficiency over human drivers when considering conventional powertrains, and find that automated vehicles perform at a 3%-9% higher energy efficiency over human drivers when considering electric and hybrid powertrains. Due to secondary effects of smoothing traffic flow and reducing unnecessary braking, energy benefits also apply to human-driven vehicles that interact with automated ones. Such simulated humans were found to drive up to 10% more energy-efficiently than they did in the baseline all-human scenario.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Demonstrating Load-Shaping Capabilities of Cost Minimizing Heat Pump Water Heater Controls with Varying Price Profiles

Increased penetration of photovoltaics and electrification of traditionally gas appliances are exacerbating existing challenges in cost-effectively balancing electricity grid supply and demand. Decarbonization without incurring expensive transmission and distribution system capacity increases requires shifting building loads from peak demand times to peak renewable production times. Grid operators are evaluating new ways of encouraging load shifting, including using time-varying price structures to provide a financial incentive. If devices incorporate price-responsive controls, a price profile could be designed to yield a wide variety of load curves as needed to optimize grid functionality. Heat pump water heaters (HPWHs) are an ideal device for price-responsive controls because the storage tank enables them to optimize the timing of electricity consumption without impacting hot water delivery service. This paper presents work demonstrating how price-responsive controls for HPWHs can provide different load profiles, as needed to stabilize the grid, in response to different price profiles. HPWH manufacturers now include web API and CTA-2045 communication capabilities which enable sending load shaping control signals. Pilot studies and preliminary programs have utilized these capabilities with uniform control strategies to reduce 4-9 PM electricity consumption. However, no studies have developed flexible controls capable of both a) responding to constantly varying price profiles and b) customizing logic to match the needs of each HPWH. Berkeley Lab's CalFlexHub project is pioneering price-driven load flexibility by developing and deploying cost-minimizing controls utilizing setpoint setting signals for fleets of HPWHs in response to varying price profiles. Control development is based on simulations using the Flexible Heat Pump Water Heater Performance Predictor which captures the control decisions of a residential, integrated HPWH manufacturer’s on-board controller. The proposed cost-reducing controls respond to constantly changing price profiles, providing the ability to change the price profile to generate load curves as needed to maintain grid stability. Preliminary simulations studying the load shaping capabilities of price-responsive controls on a fleet of 60 HPWHs have demonstrated an average of a) 135.4% increases in load during low-price periods, b) >36.8% reductions in electricity peak-price period, and c) 6.2% electricity cost savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗