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

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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Battery Energy Storage Scenario Analyses Using the Lithium-Ion Battery Resource Assessment (LIBRA) Model

Meeting aggressive carbon emission goals will entail widespread deployment of renewable sources of electricity. Because these sources are variable, there is a need to develop scalable energy storage technologies. The U.S. Department of Energy is supporting efforts to increase U.S. manufacturing and recycling capabilities for LIBs and to decrease costs of stationary storage batteries. Many factors influence the domestic manufacturing and cost of stationary storage batteries, including availability of critical raw materials (lithium, cobalt, and nickel), competition from various demand sectors (consumer electronics, vehicles, and battery energy storage), resource recovery (recycling), government policies, and learning in the industry, among other factors. Understanding how these factors interact and identifying synergies and bottlenecks is important for developing effective strategies for the LIB stationary energy storage system. We developed the Lithium-Ion Battery Resource Analysis (LIBRA) model as a tool to help stakeholders better understand the following types of questions: What are the roles of R&D, industrial learning, and scaling of demand in lowering the cost of battery energy storage system production? How do the intersections between the EV and stationary storage sectors affect the battery supply chain? For various stationary storage and EV penetration scenarios, what volumes of critical materials might be required and what role can resource recovery play? What does expected demand for both EVs and stationary storage portend for mineral resources and overall mineral scarcity? The LIBRA model is developed using a System dynamics (SD) modeling approach to represent interactions across the segments of the battery materials supply chain. System dynamics models can capture the complex interactions and feedback between the various system components that influence supply and demand. The LIBRA model is comprised of several interacting modules that represent specific portions of the LIB supply chain. The model tracks the buildout of the domestic LIB industry over time (2020 - 2050) and in the context of competing demands for raw materials, recycling, and markets for LIBs. The LIBRA model represents major systemic feedback loops and delays across the supply chain. This report provides a complete documentation for the LIBRA model, including model assumptions, data, scenario analysis results, and sensitivity analysis of the model's input space.

25 ENERGY STORAGE↗
DOE OSTI2024

Near Net Shape Workshop Report

In 2021, President Biden issued Executive Order (EO) 14017, spurring the federal government to build more secure and diverse U.S. supply chains, including energy supply chains, to ensure economic prosperity and national security (White House 2021). In response to EO 14017, the U.S. Department of Energy (DOE) published America’s Strategy to Secure the Supply Chain for a Robust Clean Energy Transition (Igogo 2022) to outline the challenges and opportunities facing the energy supply chain along with key strategies to secure America’s position as a clean energy superpower in the years and decades to come. The expansion of domestic manufacturing capabilities is identified as one of the common risks and vulnerabilities for which DOE should develop comprehensive strategies to secure supply chains for the clean energy transition. The report states that “examples of manufacturing capabilities of concern include … large iron and steel castings for wind turbines, hydropower turbines, and nuclear reactor components.”

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Emerging Technologies Review: Water Reuse Systems for Cooling Tower Applications

This report explores the concept of water reuse systems for cooling tower water makeup, specifically focusing on the use of alternative water sources, and the viability of these systems for Air Force installations and operations. Cooling is a critical requirement for DAF operations, and alternative water supplies that enable cooling tower use during a disruption of utility-supplied water increase Air Force resilience. The components of a water reuse system for cooling towers include alternative water supplies, storage, treatment, and distribution in addition to the cooling tower itself. Alternative water sources are not derived from fresh surface water or groundwater and can provide a redundant water supply to utility supply or to fresh water produced on site.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Heterogeneous Integration Technologies for High-temperature, High-density, Low-profile Power Modules of Wide Bandgap Devices in Electric Drive Applications (Final Technical Report)

The goal of this project is to develop packaging technologies for making high-temperature, high-density, and low-profile wide-bandgap (WBG) power electronics modules for electric drives. These modules are aimed at enabling the DOE’s University Consortium to reach its 2025 inverter targets of ≥ 100 kW/L and ≤ 2.7 $/kW. The specific objectives are to: design and fabricate SiC half-bridge power modules with double-sided cooling and parasitic inductances < 5 nH, heat flux density > 400 W/cm 2 , and working junction temperature of 200 o C; design, fabricate, and deliver a gate driver with double-sided cooled modules for the construction of a 100 kW/L inverter at Oak Ridge National Lab; and design and prototype intelligent gate drivers with integrated current sensor and a low-profile DC-DC power supply with air-core transformer for testing power modules at 200 o C junction temperature. We followed an iterative technical approach of design, simulation, fabrication, and testing of various versions of modules, current sensors, and power supply. The state-of-the-art silicon carbide devices rated at 1.2 kV and 149 A were packaged by sintered-silver bonding on an aluminum nitride direct-bond-copper substrate for high thermal conductivity, high working temperature, and high joint reliability. Porous silver posts were used to interconnect the device’s source pads to the other direct-bond-copper substrate for low mechanical stresses, ease of manufacturing, and double-sided cooling. A current sensor based on package parasitic inductance was developed to measure switching current. A dynamic feedback scheme was developed to compensate the effect of parasitic resistance and temperature variation. A constant-current class-E dc-dc converter with air-core transformer was developed. Air-core transformer was used due to the unavailability of magnetic core at high temperatures. Gate driver and power supply were integrated with the double-side cooled, high temperature SiC power modules for testing the modules at 200 o C junction temperature. Double-pulse and continuous testing of the integrated technologies validated the design and fabrication of the three component technologies. Throughout the project, we overcame the challenge for design verification caused by low prototyping yield, which then helped train the graduate students, the future workforce, to learn the engineering know-how for low-cost manufacturing of reliable products. Below is a summary of the major accomplishments of this project: development of a prototyping process for fabricating double-side cooled (1200 V, 149 A) SiC phase-leg modules capable of working to 200 o C Tj; simulation and experimental verification of the improvement of thermo-mechanical reliability of the double-side cooled SiC phase-leg module by using rigid encapsulant; design and experimental validation of a current sensor based on package parasitic inductance and a compensation solution for eliminating the effect of parasitic resistance; design and experimental validation of a low-profile power supply with six-output air-core transformer for gate driver; functional demonstration of a SiC phase-leg module integrated with its gate driver, current sensor, and an air-core power supply at 200 o C Tj in a double-pulse switching test setup and Buck converter continuous test setup; successful completion of six PhD and two MS students who are or will work at Apple Inc., Tesla Inc., Wolfspeed Inc., Microchip Inc., Monolithic Power Systems Inc., and LG Magna Inc.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Woody Feedstock 2022 State of Technology Report

The U.S. Department of Energy promotes production of advanced liquid transportation fuels from lignocellulosic biomass by funding fundamental and applied research that advances the state of technology (SOT). As part of its involvement in this mission, Idaho National Laboratory completes an annual SOT report for n th -plant and 1 st -plant woody biomass feedstock logistics. The purpose of the SOT is to provide the status of feedstock supply system technology development for woody biomass to biofuels relative to technical targets and cost goals from specific design cases, based on data and experimental results. Conventional feedstock supply systems need to be modified to meet the demands of conversion pathways, specifically to have the ability to adjust the quality of the raw biomass materials. Advanced systems incorporate innovative methods of material handling, preprocessing and supply chain configuration. In advanced designs, variability of the raw biomass can be reduced to produce feedstocks of a uniform format, moving toward biomass commoditization. Against this backdrop, the 2022 Woody SOT for low-ash woody feedstocks utilizes feedstock fractionation by incorporating technologies that can separate the biomass into its anatomical fractions (wood, bark, needle, and extrinsic ash) to reduce impurities and attempt to maximize the retention of usable fractions that satisfy downstream quality considerations. By using a series of air classification steps, this strategy can reduce the extrinsic ash in forest residues, separate out a majority of the incoming needles (which can be supplied to alternate markets), and maximize the retention of whitewood in the usable fraction. The fractionated forest residues are then mixed with clean-pine chips in a 50-50 blend to prepare the feedstock for the desired conversion pathway. The n th -plant analysis estimated the delivered cost for the feedstock at $\$$69.23/dry ton (2016$\$$) which represents a $\$$6.64/dry ton decrease compared to the cost estimate of the 2021 Woody SOT supply system for low-ash woody feedstocks. The quality requirements in the 2022 Woody SOT were identical to those of the 2021 Woody SOT at = 1.00 wt % ash and = 50.51 wt% carbon. The cost savings derive primarily from reductions in dry matter losses during air classification. The GHG emissions for the n th -plant analysis were estimated at 178.39 kg CO2e/dry ton compared to 178.71 kg CO 2 e/dry ton in the 2021 Woody SOT, a decrease of 0.32 kg CO2e/dry ton. The small change stems from an increase in emissions attributed to preprocessing and slightly larger savings in emissions from transportation. In the 1 st -plant analysis of the 2022 Woody SOT system, the average throughput was estimated to be approximately 2,128 dry tons/day or 96.51% of the name plate capacity. During the simulation the daily throughput ranged from 1,090 dry tons/day to 2,200 dry tons/day, or 49.43% to 99.75% of the daily nameplate capacity. After the year of operation 722,403 tons of processed feedstock were produced in total without regard to quality considerations (99.64% of the annual nameplate capacity). The variability in throughput was primarily caused by equipment failures in the system. Regular failures, downtime caused by routine maintenance per manufacturer guidelines, contributed to a majority 62.50% of failures and 62.60% of downtime. Failures due to wear were the other cause of disruption within the system, impacting the rotary shear and orbital screen and accounting for 37.50% of the failures and 37.40% of the total downtime. Ultimately the system was on stream for 87.84% during the simulation period, which is only 2.16 percentage points below the nth-plant assumption for on-stream time. The production cost of the system averaged $\$$71.66/dry ton. The costs ranged from a minimum of $\$$71.23/dry ton to a maximum of $\$$2,115.30/dry ton. When dry matter losses (disposed low-quality fractions as well as other losses such as in grinders) were considered the costs increased to an average of $\$$75.11/dry ton with a minimum of $\$$74.69/dry ton and a maximum of $\$$2,136.86/dry ton...

09 BIOMASS FUELS↗
DOE OSTI2025

DOE Challenges and Opportunities Associated with Accountable Nuclear Material Needs for Development and Commercialization of Fusion Nuclear Energy

Fusion energy represents a transformative opportunity to deliver a safe, plentiful, and carbon-free source of reliable primary power. In recent years, fusion research and development have accelerated significantly, particularly within the US, driven by decades of foundational public investment. Notably, in 2024 the US Department of Energy (DOE) established a comprehensive Fusion Energy Strategy aimed at collaborating with industry partners to enable the deployment of fusion power plants and grid integration by the 2030s. This strategy is chiefly implemented through the DOE Office of Science (SC) Fusion Energy Sciences program. This project was initiated to identify potential approaches for the Office of Environment, Safety, and Health (NA-ESH-12) within DOE’s National Nuclear Security Administration to begin engagement with the fusion community on future accountable material needs. The goal of the project is to inform and influence the supply of and demand for accountable nuclear materials as fusion energy is developed and commercialized. NA-ESH-12 must proactively engage with the fusion community regarding the production and management of accountable nuclear materials. Given the complexity and scale of materials required for research, pilot projects, and eventual commercial reactors, early coordination is vital. The project’s objective is to provide insights that will shape the supply and demand landscape for critical nuclear materials, ensuring that DOE is prepared to effectively support fusion energy development and commercialization. In FY 2025, an initial limited review was conducted to identify the status of the fusion energy community’s progress toward full-scale energy production and the need for accountable nuclear material. This included communications with SC, NA-ESH-12, Savannah River National Laboratory, and Oak Ridge National Laboratory, and attending the Rutgers University–sponsored Supply Chain Workshop: Scaling the Fusion Industry and the International Atomic Energy Agency’s Ninth DEMO Programme Workshop. The review to date indicates that the amounts of tritium, lithium-6, and deuterium required by the fusion industry will be dependent on fuel type, breeding technology, blankets, and R&D improvements. One concern is that the commercial sector does not have a sufficient supply chain to meet the demand for development and commercialization for fusion energy production. The supply and demand estimates for these materials should be routinely reviewed as fusion technologies mature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Sensitivity Analysis of Drivers Water Shortage in the Los Angeles Region During Drought

The code and detailed step-by-step instructions for generating the model output data, processing results, and analysis and plotting are provided at https://github.com/IMMM-SFA/Ferencz_et_al_2026_ER_Water. The PyArtes model is a python adaptation of the Artes model. PyArtes uses many of the same input data and optimization model architecture as Artes. Documentation for the PyArtes model is provided in the Supplement to the paper. The primary data product are simulated monthly water shortages for indoor and outdoor demand under a large ensemble of drought scenarios (>13,000). The droughts are hypothetical and are not based on historical time series data of supply sources - though historical data did help inform ranges explored for supply parameters. Demands are informed by recent 2017-2021 water supply data. Demands used for the model can be accessed at https://github.com/IMMM-SFA/Ferencz_et_al_2026_ER_Water. Simulations resolve demand for over 90 water providers in the study region. The results report 36 months of water shortage data for each indoor and outdoor demand node. The study also developed a multilayer perceptron (MLP) neural network trained on a subset of the simulated shortage ensemble to emulate worst annual water shortage for a given set of parameter multipliers -- provided the parameter values fall within the ranges sampled in the ensemble. Emulated water shortages for synthetic ensembles are in the MLP-generated shortages folder. The MLP model was used to generate larger ensembles to support Sobol analysis that would have been extremely computationally expensive to simulate. Datasets provided in this repository*: Simulated shortages. These results are used for the analysis for Figures 5, 8, and 9 in the paper, and also to train the MLP emulator. .zip file containing outputs for the 13,312 scenario ensemble. Separate .csv files for indoor and outdoor shortage for each scenario. Rows = demand ids (~100), Columns = months (36) Units = acre-feet/month of shortage (shortage = monthly demand - supply). 1 acft = 1233.48 m^3 .csv files of aggregated shortages derived from the 13,312 ensemble Rows = scenarios (13,312), Columns = demand ids (~100) Units = acre-feet/year (either worst annual shortage or total shortage over the 3-year drought) .csv file of the parameter multipliers scenarios for the ensemble .csv file of the parameter ranges and baseline values the multipliers were applied to MLP-generated shortages. These results are used for Figures 4, 6, and 7 in the paper. mwd higher folder: scenario ensembles, emulated worst year total shortages (acft), and Sobol results Emulated shortages. Rows = scenarios, columns = demand ids, units acft Sobol results. Rows = demand ids, columns Sobol (S1, ST, or 95% confidence interval) value for each parameter mwd lower folder: scenario ensembles, emulated worst year total shortages (acft), and Sobol results same organization as mwd higher MLP performance: performance metrics (R^2, RMSE, BIAS, MAPE) for the testing subset (20% or 2,662 scenarios) and simulated vs emulated worst year shortage (acre-feet/year) for every demand node, MWD wholesale regions, and the entire study region (LAC). Supporting data for figures. Figure plotting scripts in the associated GitHub repo. These files support analysis and visualization. Geospatial Data used for plotting simulated water shortages and Sobol results. Dictionary of full names for demand nodes in the model and estimates of water supply by source type informed by Artes input files and California Urban Water Management Planning data: https://water.ca.gov/Programs/Water-Use-And-Efficiency/Urban-Water-Use-Efficiency/Urban-Water-Management-Plans *Readme files provided for each folder.

drought↗
DOE OSTI2020

Method and apparatus for temperature and voltage management control

A method and apparatus for managing processing power determine a supply voltage to supply to a processing unit, such as a central processing unit (CPU) or graphics processing unit (GPU), based on temperature inversion based voltage, frequency, temperature (VFT) data. The temperature inversion based VFT data includes supply voltages and corresponding operating temperatures that cause the processing unit's transistors to operate in a temperature inversion region. In one example, the temperature inversion based VFT data includes lower supply voltages and corresponding higher temperatures in a temperature inversion region of a processing unit. The temperature inversion based VFT data is based on an operating frequency of the processing unit. The apparatus and method adjust a supply voltage to the processing unit based on the temperature inversion based VFT data.

42 ENGINEERING↗
DOE OSTI2021

Circuit for providing variable waveform excitation

A circuit for testing an electronic component, such as a transformer, includes at least two power supplies and at least two H bridge circuits. A first H bridge circuit is conductively coupled in parallel to a first power supply. A second H bridge circuit is conductively coupled in parallel to a second power supply. The second H bridge circuit includes one or more anti-series diodes for preventing current from the first power supply from passing through the second H bridge circuit to the second power supply. The first H bridge circuit and the second H bridge circuit are configured to conductively couple to the electronic component for providing a voltage with a predefined waveform to the electronic component.

Beddingfield, Richard B.↗
DOE OSTI2024

Tuning circuitry for a wireless power system

A wireless power supply power supply including first tuning circuitry coupled directly to a transmitter, the first tuning circuitry including an LCC configuration. The wireless power supply may include second tuning circuitry coupled directly to switching circuitry (e.g., an inverter) of the power supply, where the second tuning circuitry may be operable to direct power from the switching circuitry to the first tuning circuitry for supply to the transmitter, and where the second tuning circuitry includes a reactance operable to establish inductive operation of the switching circuitry at the switching frequency of the switching circuitry.

Pries, Jason L.↗
DOE OSTI2026

Foreign Entity of Concern Requirements in the One Big Beautiful Bill Act

The One Big Beautiful Bill Act (OBBB), enacted July 4, 2025, makes billions of dollars in federal energy tax credits conditional on supply chain independence from China and other foreign entities of concern. The OBBB simultaneously creates powerful economic incentives to reshore energy supply chains to the United States and allied nations. Through such incentives, the OBBB elevates digital assurance and supply chain verification from voluntary best practices into critical capabilities for demonstrating tax credit eligibility. The OBBB uses tax credit eligibility requirements to simultaneously address national security concerns regarding foreign supply chain dependencies and incentivize domestic energy manufacturing. This brief details how organizations should operationalize these requirements through baseline compliance audits, interim documentation systems, supply chain diversification strategies, and long-term institutional integration of digital assurance capabilities that turn compliance burdens into competitive advantages

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2021

Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition

Neodymium-iron-boron (NdFeB) magnets are the most powerful magnets per unit volume sold in the commercial market. Despite the increasing demand for clean energy applications such as electric vehicles and wind turbines, disruptive events including the COVID-19 pandemic have caused significant uncertainties in the supply and demand for NdFeB magnets. Therefore, this study aims to alleviate the risk of supply shortage for NdFeB magnets and the containing critical materials, rare-earth elements (REEs), through the development of a resilient reverse supply chain and logistics network design. We develop scenarios to model the unique impact of the COVID-19 pandemic on the proposed business, incorporating both disruption intensity and recovery rate. We formulate a chance-constrained two-stage stochastic programming model to maximize the profit while guaranteeing the network resiliency against disruption risks. To solve the problem in large-scale instances, we develop an efficient Benders decomposition algorithm that reduces the computational time by 98.5% on average compared to the default CPLEX algorithm. When applied to the United States, the model suggests the optimal facility locations, processing capacities, inventory levels, and material flows for NdFeB magnet recyclers that could meet 99.7% of the demand. To the best of our knowledge, this study is the first to incorporate the impacts of the COVID-19 pandemic to design a resilient NdFeB magnet recycling supply chain and logistics network, leveraging risk-averse stochastic programming.

42 ENGINEERING↗
DOE OSTI2022

Characterizing manufacturing sector disruptions with targeted mitigation strategies

It has become clear in recent decades that manufacturing supply chains are increasingly vulnerable to disruptions of varying geographical scales and intensities. These disruptions—whether intentional, accidental, or resulting from natural disasters—cause failures and capacity reductions to manufacturing infrastructure, with lasting effects that can cascade throughout the manufacturing network. An overall lack of understanding of solutions to mitigate disturbances has rendered the challenge of reducing manufacturing supply chain vulnerability even more difficult. Additionally, the variability of disruptions and their impacts complicates policy maker and stakeholder efforts to plan for specific disruptive scenarios. It is necessary to comprehend different kinds of disturbances and group them based on stakeholder-provided metrics to support planning processes and modeling efforts that promote adaptable, resilient manufacturing supply chains. This paper reviews existing methods for risk management in manufacturing supply chains and the economic and environmental impacts of disruptions. In addition, we develop a framework using agglomerative hierarchical clustering to classify disruptions using U.S. manufacturing network data between 2000 and 2021 and characteristic metrics defined in the literature. Our review identifies five groups of disruptions and discusses both general mitigation methods and strategies targeting each identified group. Further, we highlight gaps in the literature related to estimating and including environmental costs in disaster preparedness and mitigation planning. We also discuss the lack of easily available metrics to quantify environmental impacts of disruptions and how such metrics could be included into our methodology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

DOE EV Data Collection - Charging Data

Charging data are collected from one of three sources, each with varying levels of additional information. These sources, in approximate order from most to least additional information, are: • The electric vehicle supply equipment (charger) • Onboard the vehicle itself • From a utility submeter. Many chargers provide software that allows for the collection and reporting of charging session data. If unavailable, data may be recorded by the charging vehicle’s onboard systems. If neither of these options is available, data can be acquired from utility submeters that simply track the energy flowing to one or more chargers. Data collected directly from the electric vehicle supply equipment (EVSE) are typically the most accurate and highest frequency. However, it is not always possible to discern which exact vehicle is being charged during any one session. EVSE-side data can be identified where a single charger ID but a range of vehicle IDs are present (e.g., CH001, EV001-EV005). Data collected from the vehicle’s onboard systems usually does not provide information on which exact charger is being used. Vehicle-side data can be identified where a single Vehicle ID but a range of Charger IDs are present (e.g., EV001, CH001-CH005). Data collected from utility submeters provide no information on which specific vehicle is charging or which specific charger is in use. Submeter data can be identified where multiple Vehicle IDs and multiple Charger IDs are present, but only a single Fleet ID is present (e.g., EV001-EV005, CH001-CH005, Fleet01). The **Charge Data Daily/Session Dictionaries** contains definitions for each available parameter collected as part of an individual charging session, aggregated at either a daily or session level. The parameters available will vary between vehicles and chargers. The **Charger Attributes** table contains specific charger characteristics, coded to at least one anonymous Charger ID and linked to either a single or a range of Vehicle IDs. Vehicle ID can be used as a key between charging data and vehicle attribute tables. The **Charger Attributes Data Dictionary** contains definitions for each available parameter collected on the physical and operational characteristics of the charging hardware itself. The **Vehicle Attributes Data Dictionary** contains definitions for each available parameter associated with a vehicle’s physical and functional attributes and fleet context. The **Vehicle Attributes** table contains specific vehicle characteristics, coded to an anonymous Vehicle ID. This Vehicle ID can be used as a key between vehicle data and vehicle attribute tables, and in cases where charging data are supplied, links a vehicle with the charger(s) that supplied it power. The **Charging Data** tables contain the data from each charger’s operations, coded to at least one anonymous Charger ID and linked to either a single or a range of Vehicle IDs. Vehicle ID can be used as a key between charging data and vehicle attribute tables. Data is being uploaded quarterly through 2023 and subject to change until the conclusion of the project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Clean Energy Manufacturing: Renewable Energy Technology Benchmarks

The manufacturing of clean energy technologies has become a global enterprise. An analysis of four clean energy technology manufacturing processes—wind turbine components, crystalline silicon solar photovoltaic modules, light-duty vehicle lithium-ion battery cells, and light-emitting diodes—was conducted to provide a reference point for comparison over time as this sector evolves. The manufacturing supply chain analysis included processing of raw materials, making required subcomponents, and assembling final products, using benchmarks that crossed 12 economies: Brazil, Canada, China, Germany, India, Japan, Malaysia, Mexico, South Korea, Republic of China (Taiwan), the United Kingdom, and the United States. Larger economies, with extensive manufacturing supply chains and high prevailing wages, tend to retain more value added from clean energy manufacturing than small economies. Manufacturing of clean energy technologies drives extensive trade among economies to support the widely distributed supply chain links. Production of wind turbine components and photovoltaic modules is more centralized than production of light-emitting diodes and lithium-ion battery cells. Across the four clean energy technologies evaluated, there was generally an excess of manufacturing capacity relative to global supply.

benchmarks↗
DOE OSTI2023

Techno-economic evaluation of industrial heat pump applications in US pulp and paper, textile, and automotive industries

Industrial process heat decarbonization through electrification could contribute significantly to climate change mitigation efforts. In the US industry, thermal processes accounted for more than two-thirds of the total final energy demand in 2021. Cross-cutting electrification technologies like industrial heat pumps are suitable for the process heat supply to several industrial unit operations in a sustainable way while also improving overall energy efficiency. This study employs a bottom-up approach to investigate the techno-enviro-economic potentials of deploying high-temperature and steam-generating heat pumps in US textile, pulp and paper, and automotive sectors in different timeframes. The results show that the annual technical potential energy and CO 2 savings by electrifying heat supply are 310 PJ (or 36% of the projected energy demand) and 28 MtCO 2 (or 71% of the projected CO 2 emissions) in 2050 respectively, however, these incur additional costs in each sector (ranging between 5 and 18 $\$$/GJ). The required heating capacity of industrial heat pumps is estimated at 15 GW, which translates roughly into a market of over 6000 heat pump units and an investment volume of $\$$7 billion in the studied processes. Although there may be individual cost-effective opportunities for electrifying heat supply in specific industrial sites, the overall costs are estimated to be high in the three industrial sectors due to the large disparity between electricity and natural gas prices and low heat source temperatures. To overcome the identified techno-economic barriers, comprehensive action plans for different stakeholders are also given. This study provides novel insights that should inform policymakers’ and executives’ decisions about the electrification of the current and future US industrial heat supply in relevant industrial sectors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Enabling residential heating decarbonization through hydronic low-temperature thermal distribution using forced-air assistive devices

Space heating represents approximately one-tenth of the United States’ energy use and has a breadth of potential for emission reduction. An element of space heating, hydronic heat distribution methods, use water supply temperatures up to 82.2 °C (180 °F). However, this operating temperature can be incompatible with high-efficiency heat generation systems, which typically provide heating temperatures of up to 60 °C (140 °F). In this work, a low-cost retrofit solution is developed using experimentally validated computational tools by incorporating an airflow distributor that preferentially directs the airflow from a fan to enhance heat transfer over the finned-tube heat exchanger found in conventional baseboards. The same heat output of traditional baseboard heat distribution systems operating at higher water supply temperatures (71.1 – 82.2 °C) can also be achieved at lower temperatures (≤60 °C). Specifically, results indicate that the technology can produce more than a 46.7% improvement in the heat transfer output at temperatures as low as 60 °C (140 °F), effectively matching the same output range achieved by 71.1 – 82.2 °C (160–180 °F) water supply temperatures. An important benefit of this solution is that it utilizes the existing infrastructure as opposed to requiring the replacement of the entire distribution system. Additionally, this technology enables existing building infrastructure to be coupled with newer, high-efficiency heating systems such as condensing boilers, solar-thermal systems, and geothermal/air-to-water heat pumps that may produce lower water supply temperatures (60 °C). A geospatially resolved techno-economic and environmental analysis is completed and presented to further understand the equivalent carbon footprint of enabling higher efficiency heat generation systems with the improved efficiency heat distribution system disclosed. Using 2021 grid-average emission factors, an emission reduction of up to a 67.5% decrease (2658 kgCO 2 /yr) for a single-family home, depending on state and climate region, could be realized by replacing a traditional natural gas-fired boiler with an air-to-water heat pump coupled to the same high-temperature heat distribution system along with the low-cost retrofit solution. A complete CO 2 emission reduction of 6688 kgCO 2 /yr, depending on state and climate region, could be realized if all electricity is further renewably sourced. Thus, this study provides a possible pathway towards enabling the reduction of operational emissions in space heating.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗