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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Residential Solar-Adopter Income and Demographic Trends: 2024 Update [Slides]

The report describes income, demographic, and other socio-economic trends among U.S. residential rooftop solar adopters. The report is based on address-level data for roughly 4.1 million residential rooftop solar systems installed through 2023, representing 87% of all U.S. systems. With its unique size, geographic scope, and level of detail, this report is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and researchers. Key findings include the following: -The median income of households that installed solar in 2023 was about $\$$115k/year, compared to a U.S. median of $\$$75k/year for all households and $\$$94k/year for all U.S. owner-occupied households. -Compared to owner-occupied households in the same state, 2023 solar-adopter incomes were 7% higher in the median case, and in 10 states, median solar-adopter incomes were below the corresponding median income for all owner-occupied households. -Roughly 49% of solar adopters in 2023 had incomes below 120% of their area median income (AMI), a threshold sometimes used to define “low-and-moderate income” (or LMI), while 26% were below 80% of AMI, often used to define “low-income”. -Solar adoption continues to shift toward less affluent households over time, with the median present-day income of solar adopters dropping from $\$$141k for households that installed systems in 2010 to $\$$115k in 2023. -PV systems installed in 2023 by households earning less than $\$$50k had a median size of 6.4 kW, 33% were third-party owned, and 6% included battery storage, compared to corresponding values of 8.0 kW, 18%, and 14% for households earning more than $\$$200k. -Compared to all households in their respective state, solar adopters in 2023 were slightly more likely to be college educated and to live in rural areas; had higher home values; and were more likely to live outside a disadvantaged community (DAC), be middle-aged, identify as non-Hispanic white, work in a business or financial occupation, and own a single-family home. In conjunction with the report, Berkeley Lab has published an updated accompanying set of online data visualizations that allow users to further explore the underlying data. Berkeley Lab is also offering related analytical support to states, local agencies, and other organizations on issues related to solar adoption among low-to-moderate income households; requests for analytical support may be submitted through this online form.

14 SOLAR ENERGY↗
DOE OSTI2025

Performance Results from DOE Cold Climate Heat Pump Challenge Field Validation

Space conditioning and water heating consume over 40% of the nation’s primary energy use and represent a significant component of many homeowners’ monthly energy bill. However, in cold climates, performance of heat pumps has traditionally suffered as the units have been unable to efficiently transfer heat from colder outdoor air temperatures to warm the interior space of homes. Optimizing heat pumps for cold climates (5 °F and below) requires coordinated effort to ensure heat pump technologies can be enjoyed by Americans living in these regions. The DOE Cold Climate Heat Pump (CCHP) Challenge sought to address this challenge by partnering with industry to develop, test, and validate the performance of new, highly efficient heat pumps in real homes. The Challenge, launched in 2021, brought together leading heating, ventilation, and air conditioning (HVAC) manufacturers to develop prototype units optimized for performance at cold climates. This report summarizes results from the field validation that occurred 2022-2024.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

A Computational Review of Privacy-Preserving Mechanisms for the Smart Grid

Smart grid technologies have rapidly become one of the largest and most comprehensive sources of data for the modern utility. For the most part, data streams are seen as an essential tool that enable utilities to carry their day-to-day business operations, but they also create the need for efficient and secure data management strategies. In the context of the smart grid, ensuring data privacy is becoming an increasing concern due to a combination of factors that range from shifts in operational paradigms and rapid technology evolution to changes in legislation. Furthermore, researchers have highlighted the risks associated with improperly protected energy records. For example, energy consumption data from homes could be used to infer the behaviors and habits of home occupants through activity recognition or user profiling (Fan, 2017), which may lead to unfair service pricing, targeted advertising, or other personal security violations. Similarly, Electric Vehicles’ (EVs) charging metadata could be used to reveal private information about the owner such as their payment methods, preferred charging stations, and other locational and timing information that could be used to reconstruct the vehicle owner’s behaviors. The privacy of user data, even when used for statistical analysis or machine learning training processes, also needs to be carefully considered, as an individual’s private traits may still be vulnerable if their inclusion/exclusion greatly impacts the result or could be linked to a public dataset through cross-reference. The breach of user privacy also has severe impacts for organizations that store, transmit, or work on the data in the form of diminishing the public’s trust in them while potentially incurring legal consequences (e.g., fines and suspensions under the European Union General Data Protection Regulation, Health Insurance Portability and Accountability Act, etc.). Because of these risks, several privacy-preserving mechanisms are available to help organizations comply with privacy legislations and prevent the unauthorized and malicious use of user data. In light of these concerns, this report focuses on performing a computational review of privacy-preserving mechanisms that have received a significant amount of interest in literature. It specifically focuses on 1) homomorphic encryption, 2) zero-knowledge proofs, 3) differential privacy, and 4) federated learning. It is worth noting that although many of the methods presented in this document rely on cryptographic primitives, their intent is not to provide perfect secrecy, but rather to enable users to maintain privacy, and thus they shall not be compared or equated to other constructs that are aimed to address cybersecurity constructs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

DIY Affordable Window Shading

This document shows how you can easily and affordably shade your windows to keep your home from getting too hot on sunny days. This phenomenon (what researchers call “solar heat gain”) can threaten occupant comfort and safety, especially during heatwaves. Still, many homes lack adequate protection. All of these solutions can be implemented inexpensively using common household items or items that can easily be purchased online. Additionally, you don’t need specialized tools or expertise to install them. Note that these are ideally temporary fixes, so households with sufficient means should still pursue permanent ones (e.g.,shades—preferably on the outside—or specialized windows or films). In their absence, the stopgap measures described below can help protect you and your loved ones during heatwaves and other exceptional events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

National Energy Education Development Project (NEED Project) (CRADA Final Report)

The U.S. Department of Energy Building Technologies Office (BTO) funds student competitions that introduce students to careers in the building sciences and increase public awareness around high-performance buildings to support the goal of developing, demonstrating, and accelerating the adoption of cost-effective technologies, techniques, tools, and services that enable high-performing, energy-efficient and demand-flexible residential and commercial buildings in both the new and existing buildings markets. The U.S. Department of Energy Solar Decathlon® (DOE/SD) is a flagship, high-visibility international competition started in 2002 that advances the goals of BTO by introducing students to building science careers; educating students and the public about the latest technologies and materials in high-performance buildings; encouraging student-led projects and research centered around building science; and demonstrating to the public the comfort and savings of homes that combine energy-efficient construction, home systems, appliances and innovative design with onsite renewable energy production. SD is a collegiate competition, comprising 10 contests, that challenges student teams to design and build highly efficient and innovative buildings powered by renewable energy. The winners will be those teams that best blend architectural and engineering excellence with innovation, market potential, building efficiency, and smart energy production. Solar Decathlon is comprised of two Challenges – Design Challenge (annual) and Build Challenge (biennial). The National Renewable Energy Laboratory (NREL) provides competition management for Solar Decathlon. NREL and Participant establish this CRADA to enable the success of the overall Solar Decathlon program by managing sponsorship funds and creating a K12 education program. Participant is to act as an Education Partner to Solar Decathlon, which includes: 1) accepting and dispersing sponsorship funds for DOE/SD; and 2) providing K12 education program to support Solar Decathlon Competition Events in April each year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

A Scalable Hardware-and-Human-in-the-Loop Grid-interactive Efficient Building Equipment Performance Dataset

This project developed a publicly available, high-fidelity dataset about the interactions among humans, homes, and heat pumps supporting grid interactive efficient buildings to balance demand on the grid with comfort for occupants. Laboratory measurements and simulations of the hardware capture the second-scale electric power dynamics of heat pumps providing grid services like load shifting and load shedding. Field measurements, behavior tracking, and qualitative surveys of people in their homes over multiple years—including experimentally adjusting the heating and cooling system to provide grid services—to capture the reciprocal effect of human behavior on grid services, and grid services on human comfort. Taken together, these data capture the complete Hardware and Human in the loop system for residential heat pumps, reducing large uncertainties in simulation for design, and models for control of heat pumps, and grid-interactive buildings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Defining Power Efficient Residential Electric Appliances and Equipment

While the long-established concept of "energy efficiency" has successfully reduced energy consumption and bills in homes, it is no longer sufficient to address the modern challenges of electrical load growth, infrastructure upgrades and associated affordability challenges. We introduce the concept of “power efficiency” for household appliances and equipment, providing a framework to support affordable home modernization and grid management. Energy efficiency is the measure of energy used (kWh) to provide comfort/conveniences, power efficiency is the measure of power used (kW) to provide those same comforts/conveniences. Energy efficiency was needed because energy is a limited resource and expensive. Now power efficiency is needed because power delivery into a building is a limited resource and expensive. We propose a new set of metrics for defining and measuring power efficiency by investigating how current appliance nameplate ratings are established, and assessing the availability and use of existing data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

New Norms or Old Habits: Evaluating Interlinked Trajectories of Online Shopping and Work Commute Post-Pandemic

The COVID-19 pandemic has significantly shifted travel behaviors, with major changes observed in online shopping and travel to work. Despite considerable research into pandemic-induced changes in travel behavior, it remains uncertain whether these new patterns have persisted or reverted to pre-pandemic norms. This study addresses this uncertainty by evaluating whether shifts in online shopping and work travel during the pandemic have become permanently ingrained in individuals' daily routine. Leveraging data from the 2022 National Household Travel Survey, a bivariate ordered probit model is employed to analyze changes in online shopping and work travel - whether they have increased, decreased, or remained stable compared to pre-pandemic levels across different population segments. The analysis finds that the pandemic did not significantly alter online shopping for home delivery and travel to work for the majority of society. However, a substantial portion of respondents reported increased online shopping for home delivery and reduced travel to work compared to pre-pandemic levels, with online shopping trends appearing more permanent. Segment-wise analysis and model results indicate heterogeneity in behavioral shifts with females engaging more in online shopping, while zero-vehicle households are traveling less to work, compared to pre-pandemic levels. Additionally, increase in online shopping frequency is significantly and negatively correlated with decrease in traveling to work. These findings highlight the need for improved digital infrastructure, flexible work policies, and integrated transportation solutions tailored to evolving demographic and socioeconomic needs in the post-pandemic era. Additionally, the study calls for integrating passenger and freight movement in a single framework rather than treating them in silos.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Reese Housing Power Project (Final Technical Report)

The Reese Housing Power Project is located on Tribal trust land in Colusa, CA and expands existing medium-voltage distribution to seven new households with the addition of medium-voltage cabling, step down transformers, smart meters, and street lighting for the new development. The Tribe utilized their existing Co-Generation power plant and micro grid to supply the new homes with highly reliable power with fewer interruptions and at a reduced rate compared with the local utility. The project gives the Tribe greater independence from traditional power sources and provides jobs for the community. The project reduces electric energy costs, increases Tribe self-reliance, and provides highly reliable electric power to seven tribal members’ homes. Construction of the project also provided jobs for the community.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Data Quality Assessment of Optiwatt Vehicle Telematics Data

In October 2024, the Idaho National Laboratory (INL) received data from Optiwatt (Compass Global, Inc.) describing the driving and charging behavior of electric vehicle (EV) drivers. The data shared had been collected from approximately 10,000 vehicles and included vehicle specifications, driving information like odometer readings at the beginning and end of origin-destination pairs (i.e., trips with identification of home for trip start and end for Tesla vehicles), and charging information such as charging energy consumed per charge session and if the charge occurred at home. The vehicle data were provided from 9 EV makes and 18 EV models, with production years ranging from 2012–2024, but more than 9,500 of the vehicles were Tesla EVs. The data includes more than six million trips and more than three million charging events that occurred between June 2023 to Aug 2024 and collected from California and the Eastern United States. The purpose of this report is to review the quality of the data received from Optiwatt and the feedback INL received from Optiwatt after data concerns were shared with them.

33 - ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Draft Impacts: Modeling and Lab Validation (CRADA Final Report)

Chimney draft is a significant source of variability in real-world wood heater performance, yet laboratory tests conducted for certification do not capture this variability. Because draft varies with climate, chimney height, and home conditions, a heater that performs well in the lab can perform quite differently when installed in a home. Until now, wood heater manufacturers and installers have lacked the tools needed to anticipate how draft will vary across real installations or to advise on corrective measures when draft is too low or too high. The goal of this project was to develop and validate an open-source draft prediction tool for cordwood heater chimney systems. Over 18 months, Lawrence Berkeley National Laboratory (LBNL) and the Hearth, Patio & Barbecue Association (HPBA) collaborated to build a physics-based, Python tool that predicts how chimney draft evolves during operation, from ignition through steady burning. HPBA convened a stakeholder group of manufacturers and venting experts who provided feedback throughout development. LBNL validated the tool against laboratory measurements from a catalytic and a non-catalytic cordwood heater operated across a range of chimney heights and room-pressure conditions.

42 ENGINEERING↗
DOE OSTI2023

Relationship between Telework Experience and Presenteeism during COVID-19 Pandemic, United States, March–November 2020

Persons with COVID-19–like illnesses are advised to stay home to reduce the spread of SARS-CoV-2. We assessed relationships between telework experience and COVID-19 illness with work attendance when ill. Adults experiencing fever, cough, or loss of taste or smell who sought healthcare or COVID-19 testing in the United States during March–November 2020 were enrolled. Adults with telework experience before illness were more likely to work at all (onsite or remotely) during illness (87.8%) than those with no telework experience (49.9%) (adjusted odds ratio 5.48, 95% CI 3.40–8.83). COVID-19 case-patients were less likely to work onsite (22.1%) than were persons with other acute respiratory illnesses (37.3%) (adjusted odds ratio 0.36, 95% CI 0.24–0.53). Among COVID-19 case-patients with telework experience, only 6.5% worked onsite during illness. Telework experience before illness gave mildly ill workers the option to work and improved compliance with public health recommendations to stay home during illness.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Analytical Framework for Homeowner-Focused Computational Cost-Benefit Mitigation Decision Making

As a result of increasing windstorm losses in the United States over the past 50 years, a variety of residential wind hazard mitigation strategies have been recommended. Wind hazard mitigation undoubtedly reduces windstorm losses; however, little customized information is available to support the economic decision-making process for individual stakeholders, especially at the consumer level. Therefore, there is a need for decision support tools to calculate, evaluate, and present the economic benefits of mitigation over variable decision-making time horizons for unique building characteristics in specific geographical locations. This paper presents a cost-benefit computational decision-making recommendation framework that evaluates and presents the cost effectiveness of mitigation, customized based on location, years of interest, and building characteristics. The decision-making framework consists of two cores. The user-independent core and user-dependent core which consists of eight steps, divided into four subprocesses: (1) data acquisition, (2) data evaluation, (3) cost-benefit calculation, and (4) results comparison and decision making. To demonstrate the framework, a wood-framed single-family home in light suburban terrain in Golden Meadow, Louisiana, is used as a case study, considering retrofit mitigation with a $15,000 budget and a decision-making time horizon of 30 years. The case study provides six mitigation options, with cost ranging between approximately $2,000 and $15,000 and net benefit/cost ratios ranging from 2.4 to 13. Once fully implemented in a decision making information tool, the developed mitigation recommendation framework will provide valuable information that can be used by home designers, builders, owners, and other stakeholders to better understand the economic facets of wind hazard mitigation, providing critical information as part of the overall decision-making process.

Orooji, Fatemeh↗
DOE OSTI2024

Experimental and Modeled Assessment of Interventions to Reduce PM2.5 in a Residence during a Wildfire Event

Increasingly large and frequent wildfires affect air quality even indoors by emitting and dispersing fine/ultrafine particulate matter known to pose health risks to residents. With this health threat, we are working to help the building science community develop simplified tools that may be used to estimate impacts to large numbers of homes based on high-level housing characteristics. In addition to reviewing literature sources, we performed an experiment to evaluate interventions to mitigate degraded indoor air quality. We instrumented one residence for one week during an extreme wildfire event in the Pacific Northwest. Outdoor ambient concentrations of PM2.5 reached historic levels, sustained at over 200 μg/m3 for multiple days. Outdoor and indoor PM2.5 were monitored, and data regarding building characteristics, infiltration, and mechanical system operation were gathered to be consistent with the type of information commonly known for residential energy models. Two conditions were studied: a high-capture minimum efficiency rated value (MERV 13) filter integrated into a central forced air (CFA) system, and a CFA with MERV 13 filtration operating with a portable air cleaner (PAC). With intermittent CFA operation and no PAC, indoor corrected concentrations of PM2.5 reached 280 μg/m3, and indoor/outdoor (I/O) ratios reached a mean of 0.55. The measured I/O ratio was reduced to a mean of 0.22 when both intermittent CFA and the PAC were in operation. Data gathered from the test home were used in a modeling exercise to assess expected I/O ratios from both interventions. The mean modeled I/O ratio for the CFA with an MERV 13 filter was 0.48, and 0.28 when the PAC was added. The model overpredicted the MERV 13 performance and underpredicted the CFA with an MERV 13 filter plus a PAC, though both conditions were predicted within 0.15 standard deviation. The results illustrate the ways that models can be used to estimate indoor PM2.5 concentrations in residences during extreme wildfire smoke events.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

SWA_Challenges_MF_ESMFNC_ZERH

This study completed by Steven Winter Associates documents the challenge that exist for existing multi family buildings to achieve Energy Star for new homes or Zero Energy Ready Home Certification.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

BENEFIT with Northeastern University: HVAC Hardware-in-the-Loop Experimental Testing of a Heat Pump and Air Conditioner

This dataset includes HVAC Hardware-in-the-Loop (HIL) experimental results for a single stage, SEER 16, HSPF 9.5, 3-ton single-speed air source heat pump with 15 kW of backup auxiliary heating tested in both cooling and heating mode, and a two stage, SEER 21, 2-ton central air conditioner tested in cooling mode for a set of outdoor temperatures and indoor setpoint temperatures. In addition to these tests, experimental tests focused on the operation of auxiliary heating for the heat pump for winter condition were also conducted. The laboratory experiments for transient testing of the heat pump and air conditioner were conducted using the two HIL systems in the Systems Performance Laboratory (SPL) at NREL’s Energy Systems Integration Facility (ESIF). Further information on laboratory design and capabilities of the SPL along with the architecture of HVAC HIL system can be found in: Sparn, B. F. 2018. Laboratory Resources and Techniques to Evaluate Smart Home Technology (No. NREL/CP-5500-71696). National Renewable Energy Laboratory (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy18osti/71696.pdf and the experimental setup and validation of HVAC HIL platform can be found in: Ramaraj, S. and Sparn, B. 2022. Validation of HVAC Hardware-In-the-Loop Simulation for Advanced Control Strategies in Smart Homes (No. NREL/CP-5500-82562). National Renewable Energy Lab (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy22osti/82562.pdf. These experimental results can be used to validate how we currently model the cycling behavior of heat pumps and air conditioners. Additionally, many demand response programs implement heat pump and air conditioner control by changing the thermostat set point – these data may also be used to verify our models for heat pump and air conditioner demand response control are implemented correctly. The Test_Matrix file describes all the indoor and outdoor test conditions for heat pump and air conditioner and the file names of data sets include information about the test conditions. A wide range of outdoor air temperatures were chosen to accommodate summer and winter conditions. In addition to operating the HVAC equipment with different outdoor temperatures, we also operate the system with different indoor temperature set points to represent different grid signals or different operating conditions. For cooling conditions, the baseline set point is 72°F. To represent Load Up signals, the setpoint is changed to 68°F. The Load Shed set point is 76°F. For heating conditions, the baseline set point was assumed to be 68°F. The Load add set point is 72°F and the Load shed set point is 64°F. The starting indoor temperature for cooling conditions was set ~2°F above the indoor setpoint temperature so that the equipment turned on quickly. Similarly, the initial indoor temperature was set ~2°F lower than setpoint for heating mode tests to ensure that heating began quickly. The return air temperature was assumed to be equal to the indoor setpoint temperature in all cases. The experimental data are sampled at 1-second intervals. The data from ecobee thermostat at 5-minute interval are resampled and added to the corresponding file. The content of each data set is as follows: • T_Return (C): Measured return air temperature [C] • T_Return_SP (C): Return air temperature setpoint from E+ model, sent to HIL [C] • T_Supply (C): Measured supply air temperature at evaporator outlet [C] • T_Outdoor (C): Measured outdoor air temperature [C] • T_Outdoor_SP (C): Outdoor air temperature setpoint from weather file, sent to HIL [C] • T_Indoor (C): Measured indoor air temperature [C] • T_Indoor_SP (C): Indoor air temperature setpoint from E+ model, sent to HIL [C] • Outdoor Unit Power (W): Measured power of the outdoor unit [W] • Indoor Unit Power (W): Measured power of the indoor unit [W] • Evaporator Airflow Rate (CFM): Measured evaporator or indoor unit airflow rate sent to E+ model [CFM] • Cooling/Heating Capacity (kW): Calculated cooling/heating capacity sent to E+ model [kW] • T_SP_Thermostat (C): Thermostat cooling/heating setpoint temperature [C] • T_Indoor_Thermostat (C): Thermostat indoor air temperature [C]

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1972

Topography and pigeon orientation

Two types of homing experiments with pigeons to determine the influence of topographical features on the orientation behavior of the birds are discussed. The releases and following were conducted by ground experiments in which the birds are tracked by visual observation at points of topographical interest and the helicopter method by which the birds are tracked throughout the entire flight. The ground experiments showed a strong influence of topographical features on initial orientation. The helicopter experiments showed that the ground experiments do not provide adequate information on the manner in which homing occurs.

Wagner, G.↗