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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Demographic Information Incorporated Household Energy Consumption Analysis: Preprint

The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.

building loads↗
DOE OSTI2023

Demographic Information Incorporated Household Energy Consumption Analysis

The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.

building loads↗
DOE OSTI2020

High-Frequency, Multiclass Nonintrusive Load Monitoring for Grid-Interactive Residential Buildings

Smart buildings with net-load metering and control capabilities can provide valuable flexibility to grid operators. This article develops a novel approach for high-frequency, multiclass nonintrusive load monitoring (NILM) that enables effective net-load monitoring capabilities with minimal additional equipment and cost. Relative to existing NILM work, the proposed solution operates at a faster timescale, providing accurate multiclass state predictions for each 60-Hz ac cycle without relying on event-detection techniques. The approach is validated using a test bed with residential appliances and shown to have high accuracy, good generalization properties, and sufficient response time to support building grid-interactive control at fast timescales relevant to the provision of grid frequency support services.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2026

Envelope-driven comfort risk in residential demand response

Residential demand response (DR) is a valuable resource for grid reliability, but remains challenging because the highly heterogeneous residential building stock leads to widely varying and hard-to-predict load and comfort responses during DR events. Although prior research has estimated the technical potential of DR-capable technologies for achieving energy demand savings, little is known about how they affect thermal comfort. In particular, it remains unclear how indoor thermal conditions due to DR depend on the thermal envelope characteristics of the housing stock. To address this gap, this study provides a systematic, location-specific assessment of indoor thermal performance during DR-events across the US housing stock using both typical DR weather data and detailed building metadata. We evaluate how envelope characteristics influence indoor temperatures during realistic simulated summer and winter DR events across 37 US locations, applying both temperature threshold and rate of temperature change criteria to estimate region-level probabilities of discomfort. Additionally, we show the impact of distinct weather patterns that intensify or abate thermal stress on comfort outcomes. Results show a near-universal overheating risk in summer DR events, where comfort outcomes are strongly influenced by rapid risk of comfort violations. In contrast, overall winter DR discomfort risk is lower, risk escalation is more gradual and shows greater sensitivity to event duration. These findings offer a data-driven quantification of comfort risk across diverse climates and building envelopes, demonstrating the need for region-specific DR scheduling and discomfort mitigation strategies tailored to local weather patterns and the performance of existing residential buildings.

Demand response↗
DOE OSTI2022

Electricity Bill Calculator (elecprice) v0.1.0

The Electricity Bill Calculator Library is a generic tool for manipulating the tariffs of electricity, with an emphasis on commercial Time-Of-Use (TOU) rates in the U.S. and residential Net Energy Metering tariffs in CA. Typical uses of the package are price signal generation and bill computation. To generate price signals from a specific tariff and given a time window, the tool creates a pandas dataframes containing the various components of the electricity charges, at each time step. This is particularly useful for Demand Response (DR) applications, such as price-based optimization of energy in buildings. The tool also computes bills given a building's power consumption and a specific tariff and returning the corresponding cost of electricity, as well as a breakdown per type of rate.

Prakash, Anand Krishnan↗
DOE OSTI2022

Simulation, Challenge Testing and Validation of Solutions for Residential and Commercial Occupancy Sensing/Counting and CO2 Sensing (Final Report)

Carbon dioxide sensors used for monitoring and control applications in buildings are known to be sensitive to long term drift and can be affected by variations in temperature, humidity, other gas interferents, pressure and other factors that cannot be corrected through the typical auto-calibration methods often embedded in the sensor electronics. This investigation was part of the Category D defined in the ARPA-E Saving Energy Nationwide in Structures With Occupancy Recognition (SENSOR) Financial Assistance Funding Opportunity Announcement No. DE-FOA-0001737, FFDA No. 81.135, January 18, 2017. The FOA defined target criteria for the evaluation of the Category C commercial CO2 sensors selected for review and development through the ARPA-E SENSOR program and charged the Iowa State Category D team with developing an evaluation methodology for Category C sensors in accordance with these criteria. As part of the work, the Iowa State team chose to engage the standards community in the development of the evaluation methodology. Standard development work in the D22.05 Indoor Air and D22.03 Ambient Atmospheres and Source Emissions subcommittees of ASTM International Committee D22 on Air Quality on the evaluation of low cost sensors and provision of guidance for using indoor carbon dioxide concentrations to evaluate indoor air quality and ventilation is of particular relevance to the Category D efforts. To date, three draft standards with specific input by the Iowa State Category D team have passed the subcommittee balloting stage and are being balloted in December 2022 and January 2023 in the main D22 committee. In addition to the aforementioned standards to which the PI was a contributing author, intellectual property developed in this project pertaining to “An Automated System for Evaluation of the Long Term Performance of Carbon Dioxide Sensors” and “An Automated Ground Truth System for Real-Time Reliability Assessment, Capture of Control Decisions and Energy Savings Measurements for Occupancy Recognition Systems and Other Applications” are the other major deliverables of the project. These standards and the developed intellectual property are expected to benefit the public in a number of ways stemming from their provision of means to benchmark the performance of carbon dioxide and other sensor systems. In particular, there is high interest in techniques to demonstrate the performance of low-cost carbon dioxide sensors which can be used for typical HVAC applications (e.g., demand controlled ventilation, outdoor and indoor air monitoring, estimation of occupancy, etc.).

42 ENGINEERING↗
DOE OSTI2024

Evaluation of phase change thermal storage in a cascade heat pump

Here this study proposes a low-global warming potential cascade heat pump system with integrated phase change material (PCM) for combined space heating and cooling. PCM is embedded in the intermediate heat exchanger that couples an outdoor R290 refrigerant circuit and an indoor CO 2 circuit. We used a clustering method to develop seasonally representative load and ambient temperature profiles for residential buildings in Minneapolis, Minnesota. We simulated the system peak shaving performance on the selected representative days, assuming three different PCM options including ice (0 °C), tetradecane (5.6 °C), and a commercially available PCM, SP9 (10.5 °C). The baseline was the same cascade system without thermal storage. We investigated the effect of both thermal energy storage capacity (kWh th ) and PCM transition temperature on system performance. The results show that higher thermal energy storage capacity shaves more electric energy until it reaches a maximum value set by the load characteristics of the building. SP9, with the highest transition temperature, shaves the most electric energy, while ice shaves the least. Moreover, ice has the highest charging cost, especially in the cooling season when the outdoor circuit has to operate at an evaporating temperature lower than 0 °C to make ice. Our results show that SP9 presents the lowest levelized cost of storage, closely followed by ice. A lower off-peak electricity rate benefits ice more than SP9 or tetradecane because ice has the largest charging cost penalty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Analysis of predicted mean vote-based model predictive control for residential HVAC systems

Model Predictive Control (MPC) is an advanced process control method that has attracted much attention in building heating, ventilation, and air conditioning (HVAC) systems. Here, this paper analyzes the optimal precooling performance in residential buildings using MPC with two different comfort indices, namely, temperature and predicted mean vote (PMV). It first formulates, for each comfort index, an optimization problem that accounts for different factors, such as weather, home thermal condition, prediction horizon, time-of use (TOU) utility rate, and rated cooling capacity. The problem is then solved, resulting in an MPC strategy that determines the HVAC on/off control signal and minimizes energy cost over a receding time horizon while maintaining thermal comfort. The energy performance difference between temperature-based and PMV-based MPC strategies is subsequently investigated, especially in light of the interior wall surface temperature and under different combinations of the factors. Extensive simulation results demonstrated that the proposed MPC strategies are adaptive and their performances depend primarily on weather, home thermal condition, and prediction horizon, while the impact of TOU utility rate and rated cooling capacity is relatively small. Because the PMV-based MPC strategy can take advantage of the lower interior wall surface temperature due to precooling, it resulted in 8–45% cost savings for the scenarios investigated and an average increase of 0.042–0.113 in the absolute value of the PMV index compared to the temperature-based MPC strategy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Electrolyte and Cutoff Potential Effects on Cycle Life of Li4Ti5O12/LiNi0.9Mn0.1O2 Batteries for Behind-the-Meter Storage Applications

Behind-the-Meter Storage (BTMS) is a stationary battery energy storage system that is connected to the electrical distribution system on the customer's side of the utility's service meter. BTMS systems are used to store electrical energy from the grid as well as inconstant, renewable energy, such as local solar and wind generation. A successful BTMS system will allow the customer to pair their energy generation and storage to optimize electrical consumption from the grid, improving reliability and minimizing cost. For BTMS applications, batteries must be designed and optimized with different set of criteria from other leading segments of the Li-ion battery market, like transportation, due the system being stationary and proximal to the residential or commercial building it's benefitting. BTMS applications prioritize safety, cost (low/no-critical materials), reliability (20-year calendar life), and durability (10,000 cycle life), while having the ability to (minimally) compromise energy density and rate capability. Lithium titanate (Li4Ti5O12-, LTO) is a promising anode candidate for BTMS applications due to its high safety and capacity retention, while maintaining a reasonable 160 mAhg-1 reversable capacity and composition of relatively abundant materials. (1) Specifically, LTO has a high working voltage which helps to prevent Li dendrite formation, improving safety. Furthermore, LTO also has negligible lithiation-based volume change, leading to less mechanical pulverization, or loss of active material, upon cycling. For the cathode, materials with little or no Co are of high interest due to the high cost and low abundance of Co. LiMn2O4 (LMO) has been paired with LTO for BTMS applications in the past due to its safety, low cost (abundancy), and reasonably high operating voltage. (2-4) However, the low capacity of LMO limits energy density and specific energy. While not the highest priority for BTMS applications, increasing energy density will enable deployment in space constrained BTMS applications and decrease total cost. LiNi0.9Mn0.1O2 (LN-MO) is a recently developed material with promise due to its high operating voltage and relatively low price. (5) However, Ni-rich layered oxides, including LNMO, tend to struggle with capacity retention during high-voltage cycling due to mechanical pulverization, irreversible phase transitions, and unstable solid-electrolyte interphase. The study presented here focuses on building an understanding of how electrolyte solvent and varied cutoff potentials will impact the cycle life of LTO/LN-MO cells. Specifically, a comparison is provided between ethylene carbonate (EC), ethyl methyl carbonate (EMC), fluoroethylene carbonate (FEC), and Gen2 electrolyte solvents with 1M Lithium hexafluorophosphate (LiPF6) salt, cycling to two upper termination potentials, 2.6V and 2.7V. Electrochemical testing and diagnostics (e.g., differential capacity analysis, area specific impedance, constant voltage hold, and rate capability) and post-mortem characterization will be used to understand the aging behavior and failure mechanisms of the 8 cell combinations (four electrolytes and two voltage cutoffs). Cells with FEC electrolyte showed a lower initial capacity compared to cells with Gen2, EMC, and EC cycling at both voltages; however, the cells with FEC showed consistent trends in capacity retention with 2.6V and 2.7V termination potentials, while the cells with the other electrolytes showed much higher rates of capacity loss when cycling to the higher voltage. These results indicate that FEC may play a role in improving durability of high-voltage, Ni-rich electrode systems for use in high-cycle applications, such as BTMS.

electrolyte↗
DOE OSTI2022

Multimodal sensor fusion framework for residential building occupancy detection

For several years now, smart building energy systems have been a research area of intensive activity. In light of the increasing need for sustainable buildings and energy systems, this trend motivates an increasing need for a solution to reduce carbon dioxide emissions and improve energy efficiency. This work proposes a high-performing and transferable occupancy detection framework that combines sensor data from different data modalities, including time series environmental data (temperature, humidity, and illuminance), image data, and acoustic energy data using ensemble method. To draw out the best prediction performance in each modality, the proposed framework was developed, including various models that were designed to learn the occupancy patterns reflected in the physical data streams. To tackle the time series environmental data, we designed two variants of an occupancy detection spatiotemporal pattern network (Occ-STPN) that performs both feature level and decision level fusion, respectively. We also propose a new metric; the fading memory mean square error (FMMSE), that provides a fair evaluation and penalization of delayed occupancy predictions. Multiple open-sourced datasets, including the Electricity Consumption and Occupancy and the University of California, Irvine's (UCI) building occupancy detection dataset, along with our own real data collected from six different houses, were used to validate the algorithms' performance. The experimental results presented herein break down the performance for each sensing modality, and a detailed analysis of the performance is also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Assessing the New Home Market Opportunity: Case Study and Cost Modeling for Solar and Storage in 2030

Residential solar and storage markets are growing in the United States. With approximately 1 million new homes constructed every year, this represents a significant opportunity for solar and storage installations. Some homebuilders have begun to build new homes with solar and storage included as a standard offering. It is not clear how solar and storage is incorporated into the new construction process and at what cost. Further, it is unclear what barriers or opportunities exist to scale this model nationwide. To fill this gap in the literature, this research conducts a case study of Mandalay Homes' new solar and storage community in Arizona to gather lessons learned. From this foundation, we further generate a set of pathways to reduce install costs and expand solar and storage market penetration in this sector. To model existing and 2030 solar and storage costs, we use the National Renewable Energy Laboratory's (NREL's) bottom-up cost model. This modeling is further informed by 12 interviews conducted with new home builders, solar contractors, and other subject matter expert organizations. Our case study analysis generated three key considerations for other homebuilders including: 1. Educating local permitting, inspection, and in some cases utility officials on solar and storage products, designs, and code compliant building practices may be required. The need for education may decline as more local governments and utilities review and approve solar and storage projects. 2. Incorporating solar and storage systems into the homebuilding process can add complexity and related coordination challenges. This does not need to result in home construction delays, but can result in costly contractor "dry runs" to construction sites. 3. Deploying solar and storage at the time of new construction has significant economies of scale, which can improve the value proposition of the systems. The case study, extant literature, and interviews were used to model both existing and future solar and storage installation costs at time of new construction. Here, we find three key cost reduction opportunities relating to solar and battery storage hardware, customer acquisition, and overhead. If future contractors can maximize the cost reduction opportunities outlined here, residential new construction costs could decline by 8 - 25% by 2030, depending on the modeled scenario. Though we expect costs to decline through 2030, it is unclear which of these scenarios may ultimately appear. Interviewees further identified a variety of barriers across each cost category that could temper the savings shown here. At the same time, interviewees described several pathways to scale the new construction solar and storage market, beyond installation cost savings. Interviewees confirmed that changes in finance, rate design, resilience policies, deployment mandates, and DER aggregation could all support more market adoption than seen today. These findings suggest that there are significant opportunities to expand new construction markets and this research can serve as a baseline to assess progress in this segment through 2030.

14 SOLAR ENERGY↗
DOE OSTI2023

Quantification of Energy Savings and Demand Reduction for a Heat Pump Integrated with Thermal Energy Storage (Final Report)

To mitigate the variation in demand on the electric grid, thermal energy storage (TES) is an alternative to electric batteries or installing new peaking power plants. Stakeholders and policy makers across the United States have expressed interests in promoting TES, as demonstrated by the US Department of Energy’s Grid-Interactive Efficient Buildings program and the efforts of various state legislatures. However, the cost value provided by TES are unclear. If reliable cost benefits were determined, stakeholders would have a clearer picture of the financial returns that can be gained from their investment in TES. The study in this report is conducted by ORNL with collaboration with Emerson the Helix Innovation Center. In the first part of this report, EnergyPlus was used to perform whole-building simulations for two residential buildings in Indianapolis and Atlanta. The HVAC system in both buildings were equipped with phase change material TES. The TES tank was charged in off-peak hours and discharged in peak hours to perform load shifting. First, the economic value implied by existing time-of-use (TOU) rates offered by utility companies was analyzed via whole-building simulation. Second, existing demand reduction (DR) incentives sourced from 3 different electrical grid administrators (i.e., California, Texas, and New England region) were surveyed to determine their implied value. The study suggests that the traditional value analysis that focuses on ROI for the building owner significantly undervalues TES technology making economic viability difficult. A more comprehensive value analysis that includes peak demand management and deferred capital for peaking power plants shows that TES should be economically viable but here the value is greater for the utility and requires large market penetration and aggregation to fully realize the benefits. Therefore, to facilitate commercialization, new business models are needed that include a broader range of stakeholders and distribute the value of TES proportionally. In the 2 nd part of this project, the benefits of a novel phase change material (PCM) integrated heat pump configuration were evaluated via detailed component based simulation. A one-dimensional PCM heat exchanger model which discretizes the PCM tank and refrigerant tubes into small control volumes is developed. Each control volume can have different PCM temperatures, PCM properties, and heat transfer coefficients. The PCM tank is charged by a wrapped tank condenser and discharged by an internal refrigerant coil. The PCM heat exchanger model is integrated into DOE/ORNL Heat Pump Design Model for heat pump system simulation. To demonstrate the performance of the PCM integrated heat pump, a case study in Chicago was performed. A Time-of-Use utility structure-based control strategy is implemented to schedule the PCM tank charging and discharging mode switching. Compared with a conventional electric heat pump, the PCM integrated heat pump shows superior performance on load shifting and utility cost reduction. As a result, the proposed system demonstrates 24.6% utility saving for cooling application and 25.8% utility saving for heating application.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Robustness of energy performance of Zero-Net-Energy (ZNE) homes

Zero-net-energy (ZNE) homes produce an adequate amount of energy on-site to meet their energy demand based on source energy for an entire year. California building energy efficiency standards require new residential buildings started in 2020 to be ZNE. For various reasons, a home designed as ZNE may not achieve ZNE performance in real operation. Here we aimed to quantify the robustness of the energy performance of ZNE homes due to weather variability, climate change, and the uncertainty of occupant behavior. A single-family ZNE house, based on the optimal cost-effective design in three California climate zones, was used to develop the EnergyPlus simulation models. Weather variations were considered from a combination of the historical 30 years’ actual meteorological year (AMY) weather data, typical year weather data in TMY3, and future weather data based on Intergovernmental Panel on Climate Change scenarios. Three scenarios of occupant behavior from the energy perspective were defined to represent the uncertainty about occupants’ activities, comfort requirements, and their adaptive interactions with buildings and systems. In terms of annual source energy, the simulation results of the ZNE homes showed: (1) a decrease of 23–38 percent for occupants with energy austerity behavior and an increase of 120–130 percent for occupants with energy wasteful behavior, compared with the baseline assumption of normal occupants; (2) a variation range of –15 percent to +14 percent for the results using 30-year AMY weather data compared with the baseline results using TMY3 weather data; (3) an increase of 10–13 percent with future weather in Fresno and Riverside and a decrease of 15 percent with San Francisco; and (4) climate change can reduce the gap between the austerity and wasteful consumption. These findings provide insights into how ZNE homes may perform in reality and inform architects, engineers, occupants, and policymakers to pay more attention to occupant behavior on design, operation, and regulations of ZNE homes to ensure energy performance robustness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

AI-Driven Smart Community Control for Accelerating PV Adoption and Enhancing Grid Resilience

Rapid deployment of residential photovoltaic (PV) systems helps decarbonize our electricity supplies, but under certain circumstances, high-penetration PV may pose challenges to the electrical distribution grid. In a project funded by the U.S. Department of Energy's Solar Energy Technologies Office and Building Technologies Office, the National Renewable Energy Laboratory and its partners studied how flexible building loads and battery storage, when coordinated at home-level and community-level scales, can be used to address those challenges and enhance grid resilience. In this webinar, we will discuss the methodology, simulation and field pilot results, insights from partners, and lessons learned from the project.

artificial intelligence↗
DOE OSTI2020

Metrics and Analytical Frameworks for Valuing Energy Efficiency and Distributed Energy Resources in the Built Environment: Preprint

This paper summarizes efforts to develop new—and enhance existing—analytical frameworks and metrics to quantify the value that grid-interactive efficient homes with solar (GEB-solar homes) can provide. Industry is working to characterize and understand these capabilities and benefits, but existing analytical frameworks for evaluating energy efficiency (EE) are often siloed from those that evaluate distributed energy resources (DERs). Five metrics were adapted from an extensive literature review and applied to case studies of a modeled home in Riverside, California: ramp up/down, cover factor demand/supply, and curtailable load. Eight different technology scenarios were analyzed using a more tightly connected suite of building-to-grid models (BEopt, REopt, ReEDS, and PLEXOS). Additionally, an initial version of the Cambium tool was developed, characterizing the marginal prices and emissions from NREL’s 2018 Standard Scenarios. These grid costs were extended to a time-varying proxy retail rate and applied as part of a new grid alignment metric. In the results, a more integrated combination of GEB-solar technologies led to a higher cover factor demand—the percentage of gross home load covered by on-site solar—however, a benchmark was required to determine what range of cover factor was “best” for given grid conditions. To that end, a grid alignment cost metric was applied to the case study scenarios. The average cost to serve the net load of the home decreased from a median of ~$0.24/kWh to ~$0.10/kWh when the most integrated technology scenario was optimized towards the grid pricing proxy versus the time-of-use (TOU) rate.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

Thermal Management by Engineering the Alignment of Nanocellulose

One of the grand current research challenges is to improve the energy efficiency of residential and commercial buildings, which cumulatively consume more than 40% of the energy generated globally. In addition to improving the comfort of the inhabitants and mitigating the growing energy consumption problem, new building materials and technologies could provide a safe strategy for geoengineering to mitigate global climate change. Herein, recent progress in developing such advanced materials from nanocellulose, which is often derived from wood or even dirty feedstocks like waste, is reviewed. By using chemical and bacteria-enabled processing, nanocellulose can be used to fabricate broadband photonic reflectors, thermally super-insulating aerogels, solar gain regulators, and low-emissivity coatings, with potential applications in windows, roofs, walls, and other components of buildings envelopes. These material developments draw inspiration from advanced energy management found in nature, such as the nanoporous photonic structures that evolved in cuticles of beetles. Fabrication of such materials takes advantage of mesoscale liquid crystalline self-assembly, which allows for pre-designed control of cellulose nanoparticle orientations at the mesoscale. Finally, with the potential fully realized, such materials could one day transform the current energy-lossy buildings into energy plants on Earth and possibly even enable extraterrestrial habitats.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Aerogel from Sustainably Grown Bacterial Cellulose Pellicles as a Thermally Insulative Film for Building Envelopes

Improving building energy performance requires the development of new highly insulative materials. An affordable retrofitting solution comprising a thin film could improve the resistance to heat flow in both residential and commercial buildings and reduce overall energy consumption. Here, we propose cellulose aerogel films formed from pellicles produced by the bacteria Gluconacetobacter hansenii as insulation materials. We studied the impact of the density and nanostructure on the aerogels’ thermal properties. A thermal conductivity as low as 13 mW/(K·m) was measured for native pellicle-based aerogels that were dried as-is with minimal post-treatment. The use of waste from the beer brewing industry as a solution to grow the pellicle maintained the cellulose yield obtained with standard Hestrin-Schramm media, making our product more affordable and sustainable. In the future, our work can be extended through further diversification of food wastes as the substrate sources, facilitating higher potential production and larger applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Laboratory and field validation of the performance benefits and costs of thin triple-pane windows in residential buildings

The adoption of high-performance triple-pane windows that significantly reduce heat transfer has been slow, in part because they are thicker, heavier, and more costly than double-pane windows. One path to increase adoption of triple-pane windows is to replace the conventional double-glazing insulated glass unit (IGU) with a modified triple-glazing design that uses a very thin central pane of glass. This thinner triple-pane IGU can then be “dropped in” to the double-pane IGU pocket without requiring major modifications to frame design. The Department of Energy sponsored laboratory and field testing of thin triple-pane windows by Pacific Northwest National Laboratory. This article presents findings from both the Lab Homes study and subsequent field demonstrations carried out over a 3-year period (2020–2023). The laboratory and field studies demonstrated the manufacturing and distribution feasibility of thin triple-pane windows, successfully installed at multiple sites, using double-pane frames from four different manufacturers and thin triple-pane IGUs from two different manufacturers. Compared to a home with double-pane, clear-glass windows, testing demonstrated average whole-home heating energy savings of 12% and cooling energy savings of 27% for thin triple-pane windows. Improvements in comfort, sound insulation, and condensation potential were noted in both laboratory and field studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗