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At least 667 records · Page 37

The Environmental Impact of Deep Energy Retrofits in Residential Construction

Almost two thirds of the residential homes in the U.S. were constructed before the Department of Energy implemented energy conservation measures that were later formalized in the building codes. To reduce energy consumption and carbon emissions from the built environment, improvement to the existing housing stock is a prerequisite. However, improvements that lower energy consumption address carbon emissions related to heating, cooling and plug loads but not the embodied carbon of the building materials that also contribute to global carbon emissions. As the enclosure is made more efficient a larger portion of total carbon emissions is embodied carbon from the building materials. To mitigate carbon emissions, a holistic approach is required so that any improvement to the home results in a net reduction in carbon emissions. To understand the overall environmental impact of building enclosure improvements, the embodied and operational carbon emissions are calculated in this investigation and compared to the overall energy savings associated with enclosure improvements. The energy savings together with a reduction in operational carbon emissions are calculated using a novel building envelope metric. The net carbon emissions are then determined before and after the energy improvement measures. This approach allows or enables architects and builders to select designs that result in maximizing the overall reduction in energy and carbon emissions.

Aldykiewicz Jr, Antonio↗

Universal image representation based on a multimodal graph

A system for classifying a target image with segments having attributes is provided. The system generates a graph for the target image that includes vertices representing segments of the image and edges representing relationships between the connected vertices. For each vertex, the system generates a subgraph that includes the vertex as a home vertex and neighboring vertices representing segments of the target image within a neighborhood of the segment represented by the home vertex. The system applies an autoencoder to each subgraph to generate latent variables to represent the subgraph. The system applies a machine learning algorithm to a feature vector comprising a universal image representation of the target image that is derived from the generated latent variables of the subgraphs to generate a classification for the target image.

Bremer, Peer-Timo↗

How Heat Pumps Can Bring Relief to Households

An estimated 230,000 low-income households in Los Angeles lack access to cooling and are projected to experience more than two months of dangerous indoor temperatures (above 86 F) by 2035. Multifamily building residents are at much higher risk of dangerous heat exposure. Through robust modeling and analysis in the LA100 Equity Strategies project, the National Renewable Energy Laboratory (NREL) identified strategies that could save lives and maintain safe home temperatures for low-income households during heat waves, including the installation of whole-home heat pumps.

buildings↗

Ductless Heat Pump Energy Monitoring in a Cold Climate

In 2018, the City and Borough of Juneau, Alaska set the goal of reaching 80% renewable energy for heating and transportation by 2045. An important factor to help reach this goal is finding energy efficiency home heating technologies such as ductless air source heat pumps (DHPs), which rely on the local hydropower electric grid to provide space heating for an entire home or a main living area. To help residents reduce energy costs and move toward the community renewable energy goal, a team of local, state, and national partners joined to run Thermalize Juneau 2021, an energy campaign that provided education, a simplified installation process, and a bulk purchase discount. Overall, the campaign enrolled 165 participants, resulting in 75 DHP installations and over 30 energy efficiency improvements. To evaluate the reliability and energy use of the DHPs installed during the Thermalize Juneau campaign, researchers installed energy monitors on heat pumps of 14 participants and conducted interviews with homeowners. Data from two heating seasons (2021-2022 and 2022-2023) has allowed researchers to examine the accuracy of pre-campaign energy savings predictions, establish energy savings for a small group of households, and provide insights on the energy use and occupant satisfaction of DHPs which will help to inform future heat pump deployment efforts in the area.

air source heat pump↗

Factors Influencing Grid-connected Heat Pump Water Heater Performance in the Southeast U.S.

Grid-connected heat pump water heaters (HPWH) can shift electrical load while minimizing impacts to hot water availability for occupants. This capability provides a flexible grid resource to utilities seeking to manage peak loads Such load control also can feasibly improve renewable utilization within the utility electric production mix, for instance using off-peak generation during periods with high renewable energy generation. It also offers lower electric bills to customers through increased energy efficiency of HPWH and cuts greenhouse gas emissions. In particular, the Southeast U.S. due to its high penetration of electric water heating presents a promising opportunity for grid-connected HPWHs. This paper builds upon the results of an extensive HPWH load shifting field study conducted in 51 occupied homes in Florida using EcoPort technology (Butzbaugh et al, 2022). In 2022, only an initial evaluation was available. Here, long term load results are available as well as examination of various control strategies and influences. Analysis is conducted for HPWH energy use and load shifting performance based on home occupancy (i.e., low and high) and water heater location (i.e., conditioned and unconditioned) across different temperature profiles. An unexpected outcome of this analysis was the poor performance of HPWHs located in conditioned spaces, possibly because of inadequate air volume from improper installation. We did find higher demand reductions from 2-hour load ups and slightly improved for critical peak signals in the afternoon control periods. As expected, higher occupancy households showed great load reductions.

Fenaughty, Karen↗

Interactive Rotated Object Detection for Novel Class Detection in Remotely Sensed Imagery

In this paper we propose IRTR-DETR an Interactive and Real-Time Rotated DEtection TRansformer that extends IRTDETR to predict rotated bounding boxes. IRTR-DETR maintains the Human-In-The-Loop (HIL) workflow of IRTDETR but introduces rotation-aware heads for improved detection of objects with arbitrary orientations. Similarly to IRTDETR IRTR-DETR can be trained with a small labeled sample set in an interactive setting but we show that it can also be pretrained on related but not identical data--such as a building damage dataset--before being applied to tasks like identifying buildings under construction. We demonstrate the efficacy of our approach on the publicly available Tiny-DOTA and xBD dataset as well as two study-cases on proprietary datasets of greenhouses and houses under construction ("waffle homes"). Detecting greenhouses is highly relevant in the context of damage assessment while "waffle homes" aid understanding typical floorplans and building codes in different areas both thereby supporting population modeling emergency response and policy planning. Our method outperforms the state of the art in interactive rotated object detection on the Tiny-DOTA dataset by 5.7 percent and improves upon the non interactive RTDETR by 7.85 to 19.39 percent (depending on the number of provided samples) while maintaining its real-time efficiency.

Burges, Marvin [ORNL] (ORCID:0000000312690769)↗

Ductless Heat Pump Energy Monitoring in a Cold Climate

In 2018, the City and Borough of Juneau, Alaska, set the goal of reaching 80% renewable energy for heating and transportation by 2045. An important factor to help reach this goal is energy-efficient home heating technologies such as ductless air- source heat pumps (DHPs), which rely on the local hydropower electric grid to provide space heating for an entire home or a main living area. To help residents reduce energy costs and move toward the community renewable energy goal, a team of local, state, and national partners joined together to run Thermalize Juneau 2021, an energy campaign that provided education, a simplified installation process, and a bulk purchase discount. Overall, the campaign enrolled 165 participants, resulting in 75 DHP installations and over 30 other energy efficiency improvements. To evaluate the reliability and energy use of the DHPs installed during the Thermalize Juneau campaign, researchers installed energy monitors on heat pumps of 14 participants and conducted interviews with homeowners. Data from two heating seasons (2021-2022 and 2022-2023) allowed researchers to examine the accuracy of pre-campaign energy savings predictions, establish energy savings for a small group of households, and provide insights on the energy use and occupant satisfaction of DHPs, which will help inform future heat pump deployment efforts in the area.

air source heat pump↗

Statistical Estimation of EV Driver Charging Behavior and Influential Factors

INL received data collected via telematics from battery electric vehicles (BEVs), and these vehicles were owned by retail customers who had entered into a telematics user agreement. The goal of analyzing these data was to develop mathematical models to characterize how different sets of BEV drivers use charging infrastructure at home and away from home (i.e., public charging) and quantify how various factors influence BEV drivers’ decision to charge and use available infrastructure. The data used in this analysis are unique because they provide real world BEV driving and charging behavior at the individual driving and parking event level. In this study we seek to leverage this data to quantify BEV charging and driving metrics to help inform models that predict quantities like the specific times when loads are imposed on the electrical grid due to BEV charging. Most models that have been developed to predict electrical grid load due to BEV charging, use simulations of BEV driving events and rely on assumptions such as every vehicle charges every night. Using a statistical modelling framework, we seek to investigate BEV charging behavior and quantitatively assess these common assumptions of BEV charging behavior.

33 - ADVANCED PROPULSION SYSTEMS↗

Oregon Residential Energy Code Field Study

A research project in the state of Oregon identified opportunities to reduce homeowner utility bills in residential single-family new construction by increasing compliance with the state energy code. The study was initiated in November 2019; data collection began in November 2019 and continued through February 2020. Analysis of the data has led to a better understanding of the energy features present in homes and identified over $600,000 in potential annual savings to Oregon homeowners that could result from increased compliance with the 2017 Oregon Residential Specialty Code (2017 ORSC).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

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↗

Characterizing peak electricity demand for U.S. households: an assessment of end-use loads and demand factors

Understanding household peak electricity demand is critical to evaluate the technical need for electrical infrastructure upgrades. This study characterizes peak loads for existing and new equipment using metered data from a convenience sample of 11,940 U.S. dwellings from four sources, including 911 from two sources with end-use metering. After standardized data cleaning and labeling, we derived descriptive statistics for key metrics, such as maximum demand and demand factors, and developed predictive models relating 60- to 15-min demand for the National Electrical Code (NEC). Mean 15-min maximum demand was 9.7 kW (median 9.0 kW; IQR 7.0–11.5 kW, 95% CI 9.6–9.8 kW), indicating spare capacity in 98% of homes with hypothetical 100 A panels. Maximum demand increased with floor area and number of high-demand loads. Dwelling maximum demand was driven by higher-power, longer-duration heating appliances and vehicle charging, while most user-operated appliances contributed little. Demand factors are used to account for how most devices contribute less than their rated power to maximum demand. Existing load mean demand factors (28%; median 10%; IQR 0–58%; CI 28–29%) were higher than those for new loads (21%; median 7%; IQR 0–35%; CI 20–21%), because new loads changed the timing and magnitude of maximum demand. New high-demand loads had higher than average demand factors (40–60%). Whole dwelling demand factors support the NEC's 40% assumption, but they challenge its conservative 100% treatment of new HVAC. We propose a data-driven 50% demand factor for new equipment, which would align with metered data, improve affordability, and modernize electrical codes.

Appliances↗

Lockdown impacts on residential electricity demand in India: A data-driven and non-intrusive load monitoring study using Gaussian mixture models

This study evaluates the effect of complete nationwide lockdown in 2020 on residential electricity demand across 13 Indian cities and the role of digitalisation using a public smart meter dataset. We undertake a data-driven approach to explore the energy impacts of work-from-home norms across five dwelling typologies. Our methodology includes climate correction, dimensionality reduction and machine learning-based clustering using Gaussian Mixture Models of daily load curves. Results show that during the lockdown, maximum daily peak demand increased by 150-200% as compared to 2018 and 2019 levels for one room-units (RM1), one bedroom-units (BR1) and two bedroom-units (BR2) which are typical for low- and middle-income families. While the upper-middle- and higher-income dwelling units (i.e., three (3BR) and more-than-three bedroom-units (M3BR)) saw night-time demand rise by almost 44% in 2020, as compared to 2018 and 2019 levels. Our results also showed that new peak demand emerged for the lockdown period for RM1, BR1 and BR2 dwelling typologies. We found that the lack of supporting socioeconomic and climatic data can restrict a comprehensive analysis of demand shocks using similar public datasets, which informed policy implications for India's digitalisation. We further emphasised improving the data quality and reliability for effective data-centric policymaking.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Decarbonizing residential buildings in the United States: A comparative analysis of households and construction professionals

In this study, we present a comparative analysis of surveys distributed to home occupants and construction professionals in the U.S., focused on energy upgrades and electrification retrofits that support residential building decarbonization. The surveys were executed by separate research groups and combined for this study. The study examines the decision-making, sentiments, perceptions, experiences, and practices of both groups by analyzing data from three separate surveys. These surveys assess technologies, attitudes, awareness, motivations, barriers, and opportunities related to energy retrofits and electrification. The analysis highlights key differences in the perceptions and behaviors of households and construction professionals, revealing substantial barriers to achieving decarbonization goals. For example, households cite climate change and sustainability as key motivators for pursuing energy retrofits (89%), while construction industry professionals view these themes as less important for their clients (44%). This suggests an opportunity for the construction industry to align its messaging with the values that households prioritize, helping to advance residential decarbonization. Overall, the study identifies challenges faced by both groups, factors influencing the adoption of energy-efficient practices, and inconsistencies between occupant and construction industry professionals' views. These insights contribute to the development of targeted strategies and policies to accelerate the decarbonization of residential buildings in the U.S.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Superfluid density in overdoped cuprates: Thin films versus bulk samples

Recent study of overdoped La 2–x Sr x CuO 4 cuprate superconductor thin films by Božovic et al. has revealed several unexpected findings, most notably the violation of the BCS description which was believed to adequately describe overdoped cuprates. In particular, it was found that the superfluid density in La 2–x Sr x CuO 4 films decreases on the overdoped side as a linear function of critical temperature T c , which was taken as evidence for the violation of Homes' law. Here we show explicitly that the law is indeed violated, and as the main reason for violation we find that the superfluid density in Božovic's films is suppressed more strongly than in bulk samples. Based on the existing literature data, we show that the superfluid density in bulk cuprate samples does not decrease with doping, but instead tends to saturate on the overdoped side. The result is also supported by our recent measurement of a heavily overdoped bulk La 2–x Sr x CuO 4 sample. Moreover, this saturation of superfluid density might not be limited to cuprates, as we find evidence for similar behavior in two pnictide superconductor families. We argue that quantum phase fluctuations play an important role in suppressing the superfluid density in thin films.

2-dimensional systems↗

NREL/Habitat for Humanity, Wheat Ridge, CO

Habitat for Humanity Zero Energy Home (ZEH) provided 15 years of continuous monitoring for single family house with various energy features.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Ventilation in Residential Care Environments

The purpose of this study was to evaluate the effect of ventilation rate, directional airflow (e.g. pressure relationships) and airflow barriers on bioaerosol concentration and movement within assisted-living and residential care environments. Included within this report is a comprehensive literature review, field data collection test plan and, an evaluation of commercially available mitigation technologies related to the transmission of COVID-19 in LTC environments. Additionally, this report includes aerosol testing in an actual LTC facility using the test plan developed herein. Nearly 1.5 million people live in 16,000 nursing homes in the U.S. As of December 20, 2020 the Centers for Medicare and Medicaid Services (CMS) identified a total of 662,549 confirmed and suspected COVID-19 cases in these and other long-term care (LTC) facilities resulting in 92,373 deaths. At this time, COVID-19 cases in LTC facilities accounted for only 3% of the U.S. total of 21M confirmed cases yet nearly a third of the 350,000 total U.S. deaths. Preliminary studies have found little correlation between the quality of care and transmission of COVID-19 in these facilities, suggesting that even the best infection control practices may not be effective in containing the spread of this potentially airborne disease. As a result, many LTC facilities have implemented quarantine procedures and other measures to isolate infectious residents from the general population. Unfortunately, most LTC facilities were not designed for airborne infection control and guidance for retrofitting existing LTC spaces for airborne isolation is limited.

42 ENGINEERING↗

Design Heating and Cooling Load Calculation Versus Building Load Simulation for Cold Climate Heat Pumps: Understanding the "Gap"

This report explores the differences between Manual J-equivalent block load calculations and building HVAC energy simulation results using EnergyPlus™ calculations when designing cold climate heat pump systems for residential use. This study will help HVAC researchers and advanced designers understand the impacts of oversizing heat pumps on home energy use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗