Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “RESIDENTIAL”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Energy Auditor Job Task Analysis

The National Renewable Energy Laboratory (NREL) is contracted by the U.S. Department of Energy (DOE) Weatherization Assistance Program (WAP) to develop and maintain the resources under the Guidelines for Home Energy Professionals (GHEP) project. The purpose of the GHEP project is to increase the quality of work conducted for residential energy retrofits in the United States through the WAP network and other residential retrofit programs. The HEP certifications support WAP and the broader residential home performance industry through the credentialing process and development of defined JTAs for Energy Auditors (EA) and Quality Control Inspectors (QCI). This report outlines the most recent updates (2022) to the EA JTA.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Cold Climate Air-Source Heat Pump Demonstration and Analysis: Experimental Study on Cold Temperature Performance

Space heating energy is the largest end use for U.S. residential buildings, accounting for nearly 45% of residential building energy consumption nationwide, and approximately 51% of space heating energy is consumed on-site by combusting natural gas (EIA 2020a). In Colorado, approximately 53% of the statewide residential building energy consumption goes to space heating, 76% of which is provided by natural gas (EIA 2020a). Heat pumps are an efficient, electric alternative space heating technology and have been proven viable for decades. However, historically air-source heat pumps (ASHPs) have been limited to temperate climates because of (1) subpar performance at extremely cold outdoor air temperatures, (2) the need for air conditioning in summer months, and (3) the availability of natural gas in colder climates. Relatively recent advances to cold climate ASHP technology, which typically relies on inverter-driven, variable-speed compressors and variable-speed fans, have significantly improved low-temperature heat pump performance, enabling the technology to potentially save energy for many homes in cold climates.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

ResStock Technical Reference Documentation (V.3.3.0)

ResStock™ is the best-in-class building stock energy model for simulating and publishing energy use, utility bills, and greenhouse gas emissions from the residential sector of the U.S. ResStock answers two primary questions: (1) How is energy used in the U.S. residential building stock? and (2) What is the timeseries aggregate impact of energy technologies? Specifically, ResStock quantifies energy use across geographical locations, demographic groups, building types, fuels, end uses, and time of day. Additionally, it details the impact of efficiency or electrification measures: total changes in the amount of energy used by measure; where or in what use cases efficiency or electrification upgrade measures save energy; when or at what times of day savings occur; and which building stock or demographic segments have the biggest savings potential. This model, and the datasets it produces, are foundational to identifying pathways to affordable and equitable decarbonization of the U.S. residential buildings sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting

The BuildingsBench datasets consist of: - Buildings-900K: A large-scale dataset of 900K buildings for pretraining models on the task of short-term load forecasting (STLF). Buildings-900K is statistically representative of the entire U.S. building stock. - 7 real residential and commercial building datasets for benchmarking two downstream tasks evaluating generalization: zero-shot STLF and transfer learning for STLF. Buildings-900K can be used for pretraining models on day-ahead STLF for residential and commercial buildings. The specific gap it fills is the lack of large-scale and diverse time series datasets of sufficient size for studying pretraining and finetuning with scalable machine learning models. Buildings-900K consists of synthetically generated energy consumption time series. It is derived from the NREL End-Use Load Profiles (EULP) dataset (see link to this database in the links further below). However, the EULP was not originally developed for the purpose of STLF. Rather, it was developed to "...help electric utilities, grid operators, manufacturers, government entities, and research organizations make critical decisions about prioritizing research and development, utility resource and distribution system planning, and state and local energy planning and regulation." Similar to the EULP, Buildings-900K is a collection of Parquet files and it follows nearly the same Parquet dataset organization as the EULP. As it only contains a single energy consumption time series per building, it is much smaller (~110 GB). BuildingsBench also provides an evaluation benchmark that is a collection of various open source residential and commercial real building energy consumption datasets. The evaluation datasets, which are provided alongside Buildings-900K below, are collections of CSV files which contain annual energy consumption. The size of the evaluation datasets altogether is less than 1GB, and they are listed out below: 1. ElectricityLoadDiagrams20112014 2. Building Data Genome Project-2 3. Individual household electric power consumption (Sceaux) 4. Borealis 5. SMART 6. IDEAL 7. Low Carbon London A README file providing details about how the data is stored and describing the organization of the datasets can be found within each data lake version under BuildingsBench.

Array↗
DOE OSTI2018

Laboratory Resources and Techniques to Evaluate Smart Home Technology: Preprint

Smart home technologies promise to make residential buildings more comfortable, less costly to operate, more energy efficient, and more integrated with the grid, but these systems are difficult to evaluate in traditional laboratory spaces. To aid in the development and evaluation of new home energy management systems (HEMS), NREL built the Systems Performance Laboratory (SPL) within the Energy Systems Integration Facility. SPL has electrical infrastructure for three residential buildings, complete with smart meters, breaker panels and a full complement of major and minor appliances in each 'home.' Cord and plug power connections mean that appliances can easily be swapped for different models. Distributed energy resources (DER), such as residential photovoltaic (PV) inverters and home batteries, are also available for integration. Sensors monitor the power consumption of all loads and controllers can simulate occupancy to drive the appliances in realistic ways. A novel hardware-in-the-loop application was developed to ensure air conditioner cycling by combining a building simulation with a physical air conditioner and a thermostat, which allows us to simulate performance in any climate with any building construction. Another application of the hardware-in-the-loop technique uses a grid simulation to model the grid impact for different control strategies related to smart home technologies. This laboratory is a powerful, flexible tool that can be employed to evaluate the effect that home energy management and other smart home technologies will have at the appliance, whole-home, and distribution feeder levels - all of which are important perspectives for different stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Evaluation of Retrofit Delivery Packages

Residential energy retrofit activities are a critical component of efforts to increase energy efficiency in the U.S. building stock; however, retrofits account for a small percentage of aggregate energy savings at relatively high per unit costs. This report by Building America research team, Alliance for Residential Building Innovation (ARBI), describes barriers to widespread retrofits and evaluates opportunities to improve delivery of home retrofit measures by identifying economies of scale in marketing, energy assessments, and bulk purchasing through pilot programs in portions of Sonoma, Los Angeles, and San Joaquin Counties, CA. These targeted communities show potential and have revealed key strategies for program design, as outlined in the report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Evaluation of Retrofit Delivery Packages

Residential energy retrofit activities are a critical component of efforts to increase energy efficiency in the U.S. building stock; however, retrofits account for a small percentage of aggregate energy savings at relatively high per unit costs. This report by Building America research team, Alliance for Residential Building Innovation (ARBI), describes barriers to widespread retrofits and evaluates opportunities to improve delivery of home retrofit measures by identifying economies of scale in marketing, energy assessments, and bulk purchasing through pilot programs in portions of Sonoma, Los Angeles, and San Joaquin Counties, CA. These targeted communities show potential and have revealed key strategies for program design, as outlined in the report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Exploring urban typologies using comprehensive analysis of transportation dynamics

Abstract As urban areas continue to expand and develop, categorizing cities into typologies offers a valuable framework for understanding metropolitan dynamics and fostering inter-city collaboration. However, existing typologies related to urban mobility have limitations, failing to consider cities within a single large urban region and often overlooking crucial dimensions such as trip demand and traffic flow. In this paper, we introduce a transportation-focused characterization for cities within a large urban region, specifically the San Francisco Bay Area, California. We incorporate over 40 metrics across five transportation dimensions: trip demand, road network, multi-modal network, traffic flow, and land use. Specifically, for the trip demand dimension, we include metrics capturing residents’ trip characteristics, such as mode share, intra-city trips, and inter-city trips. Additionally, we analyze the purpose of trips entering the city to gain a deeper understanding of incoming trip patterns. In the traffic flow dimension, we examine metrics like vehicle miles traveled, delay, and congestion to assess the traffic conditions on the street network. These, combined with other dimensions, provide a comprehensive view of a city’s transportation dynamics. Using unsupervised machine learning clustering methods, we identified eight distinct typologies for the Bay Area: Live Work Cities; Job and Activity Magnet Cities; Anchor Cities; Multi-modal Cities; Hyper-connected Cities; Low-density Residential Cities; Medium-density Residential Cities; and Mixed-use Residential Cities. Our findings show that many clusters are strongly influenced by trip demand and traffic flow metrics. Finally, we examine the practicality of this typology and its potential to guide collaborative transportation management strategies. The typologies provide a foundation for dialogue among Bay Area cities, focusing on evaluating shared characteristics and leveraging successes or challenges to develop unified strategies for transportation management.

Kuncheria, Anu↗
DOE OSTI2021

Short-term apartment-level load forecasting using a modified neural network with selected auto-regressive features

Residential electricity load profiles and their diversity have become increasingly important to realize the benefits of Smart or Transactive Energy Networks (TENs). An important element of TENs will be practical, accurate, and implementable residential load forecasting techniques. While there have been many approaches to short-term load forecasting, few have included forecasting for individual households, partly because the high volatility and idiosyncrasies present in individual household load data can pose significant challenges. In this study, we develop a Convolutional Long Short-Term Memory-based neural network with Selected Autoregressive Features (termed a CLSAF model) to improve short-term household electricity load forecasting accuracy by employing three strategies: autoregressive features selection, exogenous features selection, and a “default” state to avoid overfitting at times of high load volatility. We include aggregations of apartments to floor and building level, because utilities may favor transactive approaches that rely on aggregator models, e.g., a cluster of consumers as opposed to an individual. We demonstrate that the CLSAF model, by virtue of its enhanced feature representation and modest computational resources, can accomplish load forecasting in a multi-family residential building across three spatial granularities (individual apartment/household, floor, and building levels), with an accuracy improvement of up to 25% compared to a persistence model. We propose a data screening technique to characterize time-series electricity-load data. This technique is suitable for integration into a TEN ecosystem and allows one to estimate confidence levels of the load forecasts to optimize computational resources and the risks associated with uncertain forecasts.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

High‑performance cold‑climate heat pump using tandem compressors with and without vapor injection: Laboratory investigation and field demonstration

Cold‑climate air‑source heat pumps must maintain heating capacity and stable operation at low ambient temperatures for residential applications. This study adapts tandem single-speed compressors—proven in commercial systems —for residential CCHPs, integrating VI and validating performance across laboratory and extreme field conditions to achieve cold-climate targets. That is to achieve ≥75% of the rated heating capacity at −25.0 °C relative to 8.3 °C and heating coefficient of performance (COP) greater than 4.0 at 8.3 °C. Laboratory testing confirmed that both configurations met these targets while operating within acceptable discharge‑temperature limits. Relative to the non‑VI configuration, the VI system provided up to 15% higher heating capacity and up to 9% higher heating COP under identical conditions, yielding a 5.6–9.1% increase in heating seasonal performance factor (HSPF). Field tests in Ohio and Alaska, with minimum outdoor temperatures of −25.0 °C and −34.0 °C, respectively, showed stable operation, minimal supplemental heating (<3.2%), low defrost penalties, and consistent output. Tandem‑compressor architectures proves promising for cold-climate residential heating.

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗
DOE OSTI2017

Estimating the cost of saving electricity through U.S. utility customer-funded energy efficiency programs

The program administrator and total cost of saved energy allow comparison of the cost of efficiency across utilities, states, and program types, and can identify potential performance improvements. Comparing program administrator cost with the total cost of saved energy can indicate the degree to which programs leverage investment by participants. Based on reported total costs and savings information for U.S. utility efficiency programs from 2009 to 2013, here we estimate the savings-weighted average total cost of saved electricity across 20 states at 0.046 per kilowatt-hour (kW h), comparing favorably with energy supply costs and retail rates. Programs targeted on the residential market averaged 0.030 per kW h compared to 0.053 per kW h for non-residential programs. Lighting programs, with an average total cost of 0.018 per kW h, drove lower savings costs in the residential market. We provide estimates for the most common program types and find that program administrators and participants on average are splitting the costs of efficiency in half. More consistent, standardized and complete reporting on efficiency programs is needed. Differing definitions and quantification of costs, savings and savings lifetimes pose challenges for comparing program results. Reducing these uncertainties could increase confidence in efficiency as a resource among planners and policymakers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Assessing electrification readiness in U.S. single-family homes based on a nationwide survey of electrical panel capacities

Electrification of residential buildings is a key strategy for increasing the use of renewable energy sources. Central to this transition is understanding the capacity of existing electrical infrastructure—specifically electrical panels—to safely and effectively manage increased electricity demands from electrification technologies. However, comprehensive nationwide data on electrical panel capacities in U.S. single-family homes is currently lacking. To address this gap, we conducted a nationwide survey of single-family homes, collecting detailed data on electrical panel capacities, breaker slot availability, major electric and gas appliances, electrical panel models, and home characteristics such as construction year and floor area. Photographic documentation was used to verify electrical panel data and appliance information. Results show that approximately 60% of surveyed homes have electrical panels rated at ≥200 amperes (A), indicating that a significant portion of the existing housing stock can accommodate additional electric loads. However, 31% of homes possess panels rated at ≤100 A, potentially restricting their ability to adopt new electric appliances without significant upgrades. Panel capacities positively correlate with both home size and construction year, with newer and larger homes generally better suited for electrification. Homes with higher-capacity panels tend to have fewer gas appliances, reflecting a gradual shift toward electric technologies. Conversely, homes with lower-capacity panels frequently rely on multiple gas appliances, highlighting substantial electrification challenges. Additionally, approximately 3% of surveyed homes had potentially hazardous electrical panel models, emphasizing important safety considerations in the residential electrification process. Our findings underscore the need for targeted policies, financial incentives, and infrastructure investments designed specifically to address infrastructural and safety barriers, particularly in older and smaller homes, to support equitable and efficient electrification across the U.S. residential sector.

Gul, Sadia↗
DOE OSTI2021

Decarbonizing via disparities: Problematizing the relationship between social identity and solar energy transitions in the United States

As solar adoption across the United States continues to grow, so do the gaps between rural and urban communities in how they choose to embrace these technologies, leading to serious questions of social justice and equity by researchers and policymakers alike. While recent studies have examined the racial and social justice elements of solar adoption alongside institutions' role in shaping pro-solar policies, codes, and code enforcement, an opportunity exists to discuss how the place and composition of the body politic in terms of race/ethnicity and rurality exists. This paper establishes a methodology for examining location and body politic composition concerning adopting all types of solar (residential, non-residential, utility-scale), utilizing the State of Georgia as a case study. Results indicate that the approach yields useful and informative findings; namely, there is a significant difference in adopting non-residential and utility-scale solar between rural and urban counties. We conclude by discussing further opportunities to expand on this analysis and the impact of assessing solar adoption in terms of value alignment between a body politic and the policies that shape the adoption of sustainable energy technologies. Finally, combining solar adoption information for the State of Georgia with Census data, this study compares solar adoption trends across counties--grouped by urban/rural classification and racial and ethnic majority.

14 SOLAR ENERGY↗
DOE OSTI2025

Scalability and Effectiveness of Smart Charge Management

The rise in electric vehicle (EV) adoption presents growing challenges for power grids, particularly from simultaneous residential charging, which can cause voltage fluctuations and increase feeder peak loads. Baltimore Gas and Electric (BGE), with support from the U.S. Department of Energy, initiated a pilot program to evaluate managed residential EV charging through Smart Charge Management (SCM). This study analyzes real-world charging behavior data from the pilot and feeder-level base loads from BGE to simulate residential charging scenarios through 2035 across the Washington, DC–Baltimore region. Grid impacts under unmanaged charging are compared to three SCM strategies: TOU-immediate, TOU-distributed, and Load Balancing. Results show that the magnitude of peak reduction is highly feeder-dependent. Some feeders achieve reductions of more than 40% at high enrollment levels, while others show improvements closer to 10–15%. This heterogeneity reflects differences in baseline feeder load shapes, EV penetration, and plug-in behavior across customers. Results also highlight trade-offs between shifting load away from peak periods and minimizing secondary demand peaks, offering practical insights for future utility program design.

Electric vehicle↗
DOE OSTI2022

Patterns of indoor radon concentrations, radon-hazard potential, and radon testing on a small geographic scale in Utah

Currently, there are no publicly-available estimates of indoor radon concentration at scales smaller than the county. Radon-hazard potential soil maps that reflect underlying geologic factors can be created at small geographic scale and linked to residential and census data. We determined the association between residential radon tests and high radon-hazard potential soil at the residential and block group levels using a large Utah-based dataset. We also identified characteristics of block groups with limited tests in the dataset.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2018

A study of appliance ownership and electricity consumption determinants in urban Ghanaian households

The residential sector in Ghana accounts for about 40% of aggregate electricity consumption out of which urban centers contribute 70%. The high weighted share of residential electricity use is attributed to high appliance ownership and use, and other household/building factors. The ability to determine how changes in the pattern of these factors influence electricity demand is critical if efforts to reduce consumption are to be effective. Here this study combines a residential electricity consumption survey (RECS) with electricity end-use monitoring of 60 households in Tema city Ghana, to yield the first ever comprehensive investigation of city-scale electricity consumption in urban Ghanaian homes. A multiple linear regression analysis is used to identify the most statistically significant indicators of appliance ownership and household electricity consumption. Results indicate that ownership of air conditioner, freezer, fan, refrigerator and television; and changes in socio-economic and building factors such as energy efficiency awareness and practice; income; household size and floor space show high statistical significance, and collectively explain 57% variance in households’ total electricity consumption. The presence of dependent children increases ownership of television, iron, washing machine and small kitchen appliances. This work provides a solid foundation for developing more tailored energy-saving policy interventions targeted at households.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Beyond-the-Meter: Unaccounted Sources of Methane Emissions in the Natural Gas Distribution Sector

The United States Environmental Protection Agency maintains an inventory of greenhouse gas emissions in accordance with the Intergovernmental Panel on Climate Change. Methane (CH 4 ), a potent gas with a global warming potential 86–125× that of carbon dioxide (CO 2 ) over a twenty-year period, is the main component of natural gas (NG). As NG becomes an increasingly larger percentage of the energy resources used in the United States, it is ever more important to evaluate the CH 4 emissions inventory. However, the inventory also does not account for all possible sources of CH 4 leaks, contributing to uncertainty in the national CH 4 inventory. Discrepancies between top-down and bottom-up inventories of CH 4 emissions imply that there are significant unaccounted-for sources of CH 4 leaks, especially over cities. Diffuse CH 4 plumes above cities that are not attributable to distribution pipelines or other NG infrastructure suggest many small beyond-the-meter leaks together contribute to large emissions. Here, we evaluate the distribution sector of the CH 4 emissions inventory and make suggestions to improve the inventory by analyzing end-user emissions. Preliminary research into beyond-the-meter emissions suggests that while individually small, the appliances and buildings that make up the residential sector could contribute significantly to national scale emissions. Furnaces are the most leak-prone of appliances, contributing to 0.14% of total CH 4 emissions from the NG sector in the United States. Combining measurements from whole house emissions and steady-state operation of appliances, we estimate that residential homes and appliances could release 9.1 Gg CH 4 yearly in the United States, totaling over 2% of the CH 4 released from the NG sector. Here, while factors such as appliance age and usage, climate, and residential setting could influence the emissions profile of individual appliances, these preliminary estimates justify further exploration of beyond-the-meter emissions.

03 NATURAL GAS↗
DOE OSTI2022

Electricity consumption variation versus economic structure during COVID-19 on metropolitan statistical areas in the US

The outbreak of novel coronavirus disease (COVID-19) has resulted in changes in productivity and daily life patterns, and as a result electricity consumption (EC) has also shifted. In this paper, we construct estimates of EC changes at the metropolitan level across the continental U.S., including total EC and residential EC during the initial two months of the pandemic. The total and residential data on the state level were broken down into the county level, and then metropolitan level EC estimates were aggregated from the counties included in each metropolitan statistical area (MSA). This work shows that the reduction in total EC is related to the shares of certain industries in an MSA, whereas regardless of the incidence level or economic structure, the residential sector shows a trend of increasing EC across the continental U.S. Since the MSAs account for 86% of the total population and 87% of the total EC of the continental U.S., the analytical result in this paper can provide important guidelines for future social-economic crises.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗