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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Impacts of Thawing Permafrost on Residential Infrastructure: Results and Resources

Permafrost underlies approximately 20% of the landmass in the Northern Hemisphere. Inevitably human infrastructure has been and will be built on permafrost; however, due to climate change, the permafrost in many regions has begun to thaw. Using past reports and surveys as guidance, a survey was conducted to track the effects of permafrost thaw on housing infrastructure in the community of Point Lay, Alaska. The Cold Climate Housing Research Center, Inc. and the National Renewable Energy Lab conducted a literature review and interviews to document community issues from thawing permafrost and identify potential mitigation strategies for existing and new infrastructure. Researchers also identified strategies for individual homeowners to inspect their foundations for current issues or anticipate future ones. This poster will cover the results from the survey on the effects of permafrost thawing to Point Lay and include permafrost basics, common concerns from thawing permafrost, steps to identify permafrost sites and visible signs of permafrost degradation, and potential mitigation strategies that may be beneficial to Alaskans and increase resilience in the Arctic.

Alaska↗
DOE OSTI2023

Acidic Gas Reduction For Residential Natural Gas Furnace

The United States has more than 119 million homes, and 47% of them rely on natural gas as their primary heating fuel. However, most U.S. homes still use noncondensing units with an annual fuel utilization efficiency (AFUE) of ~80%, rather than efficient condensing furnaces. This is due to the high cost of condensing furnaces, which usually use expensive corrosion resistant super-ferritic stainless steel alloy heatexchangers (HX) to avoid corrosion and fouling acid condensation, along with the cost and difficulty of retrofitting the venting used by the replaced furnace. Here, this article discusses a low-cost acidic gas reduction (AGR) catalyst technology that enables a novel condensing natural gas furnace with an ultraclean (i.e., nearly zero) flue gas and neutral condensate that is environmentally friendly.

03 NATURAL GAS↗
DOE OSTI2022

Case Studies of Residential Façade Upgrades in Four Climate Zones

This paper reports on a project that explored the viability of insulation and window upgrades during siding retrofits in four case studies across the United States. Thousands of homes are re-sided every year, but only a fraction of consumers add insulation and upgrade the windows at the same time, even though a siding replacement is the ideal time to update the thermal performance of building enclosures. To better understand why more siding retrofits do not include insulation and window upgrades, research staff from several organizations collaborated with the U.S. Department of Energy on a multi-faceted research project that included a cost analysis, workforce analysis, market assessment, and contractor assessment. This paper will review four in-field case studies conducted with contractors actively engaged in home re-siding projects that agreed to add rigid insulation and window upgrades as part of their projects. Findings from the case studies will be presented including contractor perspectives, cost, and technical approaches on projects, located in multiple climate zones including Bellingham WA, Jackson MS, Kalamazoo MI, and Phoenix AZ. All projects involved adding continuous rigid insulation on the exterior walls and installation of new cladding. Cladding types varied from wood and metal to fiber cement, vinyl, and traditional stucco. All homes also received a window upgrade, although upgrades varied depending on the original condition of the windows and climate; upgrades included triple-pane windows, low-e storm windows, and exterior shading. Key findings including technical approaches, opportunities, barriers, and project cost will be presented.

re-siding, insulation, rigid insulation, exterior ↗
DOE OSTI2019

Indoor Radon Measurements from Residential Buildings with Basements in a Community with Potential LLRW Contamination - 19566

The Port Hope Area Initiative (PHAI) represents the Government of Canada's commitment to the cleanup and safe, local, long-term management of historic low-level radioactive waste (LLRW) in two Southern Ontario municipalities-Port Hope and Clarington. The PHAI (see reference for internet address) is based on community-recommended solutions for the cleanup and safe long-term management of approximately 1.7 million cubic meters of LLRW. It is currently one of Canada's largest environmental remediation projects at a cost of over one billion dollars. Canadian Nuclear Laboratories (CNL) is implementing the PHAI on behalf of Atomic Energy of Canada Limited, a Federal Crown Corporation. An initial characterization and remediation program in the urban area of Port Hope was conducted from 1976 to 1981. The waste is the result of radium and uranium processing in Port Hope by the former Federal Crown Corporation Eldorado Nuclear Limited between 1933 and 1988. One contaminant of concern in the LLRW is radium-226 (Ra-226) which may lead to elevated indoor levels of radon-222 (Rn-222) indoors. As part of CNL's implementation of the PHAI, Arcadis is conducting the Port Hope Project Property Radiological Survey of approximately 4,800 small-scale sites to identify 1) properties that have not been affected by historic operations and 2) properties that have residual historic low-level radioactive waste impacts requiring remediation either for soils or for interior contamination or both. Over the last six years, a component of the Small Scale Sites (SSS) characterization surveys have measured radon concentrations in essentially all buildings in Port Hope using alpha-track detectors. All properties had subsurface characterization including analytical characterization and lithology following the radon measurement reporting to measure if soil concentrations exceeded the PHAI Cleanup Criteria (PHAI CC) for Ra-226 of 0.29 Bq/g. Buildings with radon gas exceeding a trigger level of 200 becquerels per cubic meter (Bq/m{sup 3}) or those with ventilation systems required investigation of soil concentrations around the perimeter of the building. Ra-226 concentrations above the background level of 0.05 Bq/g due to LLRW sources were forwarded to create remedial action plans (RAPs) to remove the contamination near the building. The SSS surveys provide a substantive data set on the approximately 3,000 properties measured to date with interior Rn-222 gas measurements and descriptions of the physical characteristics of the buildings, the lithology of soils near the buildings and the measurements of Ra-226 concentration in the soils on the property. Consideration of the potential for contribution from non-LLRW Ra-226 from natural sources or coal ash was required on some properties. This paper describes the data and exploratory analysis of the relationship(s) between LLRW and non-LLRW factors that affect the variation in indoor radon concentrations. Historical information on the urban area, the measured Ra-226 concentration and the age of the building were correlated with radon concentrations. A large variety of native soils are found in the complex terrain and the type of native soil was correlated with the radon concentrations. A statistical analysis to address the impact of co-related explanatory variables to model indoor radon concentrations is planned when the SSS activities are complete. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

An Open-Source Framework for Characterizing Urban Energy Models: Integrating Top-Down and Bottom-Up Methods to Predict Residential Buildings Characteristics: Preprint

Bottom-up urban energy models are crucial for understanding current energy use patterns and informing design strategies. However, accurately characterizing these models to represent different communities remains a challenge due to the extensive data needed for simulating existing energy use behavior. This data includes information related to human activities and building characteristics, all of which correlate with socioeconomic factors. To overcome this challenge, we developed an automated framework that utilizes both top-down and bottom-up data, to predict unknown building and occupant characteristics that are needed for more accurate and equitable modeling and analytics. Our framework, integrated into the URBANopt district energy modeling platform, uses statistical data models from ResStock. URBANopt models co-located buildings and neighborhoods. At this scale there are data gaps in building characteristic data, such as materials, insulation, occupancy, income, and energy usage of the buildings. To address this data gap, we use ResStock data, representative at the census tract scale, and develop machine-learning and deeplearning techniques to disaggregate it to individual buildings. By mapping unique occupant, building and economic properties to URBANopt energy models, we gain detailed insights into the variability of building energy use across different neighborhoods. This insight helps deploy technologies for co-located buildings and supports targeted upgrades for communities with unique economic and demographic characteristics, ensuring energy equity. Accurate characterization of energy models allows us to develop equitable strategies tailored to diverse neighborhoods, whether underserved or affluent. Our automated framework streamlines energy modeling and provides a reliable tool for building energy characterization.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2024

Benchmark Testing of Two Residential Refrigerators Using R-600a

Household refrigerators provide a convenient and safe means of food preservation and storage. More than 100 million refrigerators are used in US homes, resulting in significant primary energy consumption and carbon emissions. As a greenhouse gas with a 100-year global warming potential of 1,430, R-134a has been banned in new US domestic refrigerators and freezers since 2021, and R-600a with a global warming potential of 3 is widely employed as a working fluid in the current US household refrigerator market. In this paper, benchmark testing was conducted for two 2023 refrigerators using R-600a. Moreover, the effect of representative customer use patterns, such as door opening and warm food storage, was studied to evaluate the effect on the energy consumption of the refrigerators. These results will provide background knowledge for facilitating the integration of new technologies to achieve significantly reduced greenhouse gas emissions in future efficient refrigerators.

Gao, Zhiming↗
DOE OSTI2025

Short-Term Electric Load Forecasting for a Residential Household in Alaska

Accurate short-term load forecasting at a fine scale is essential for demand response programs, peak shaving, and load-shedding strategies [1]. While traditionally, only aggregate short-term consumption data was available, advanced metering infrastructure (AMI) now provides data at the individual consumer level [1]. There is increasing interest in utilizing this data for short-term load forecasting (from an hour to a few days) to optimize grid operations. Electricity consumption in individual households is highly influenced by residents’ personal behaviors [2]. As a result, unlike aggregate loads, electrical power usage in single households often shows significant volatility, making meter-level load forecasting for individual users particularly challenging [3], [4]. Deep learning methods, with their strong ability to model nonlinear data, have become popular for improving the accuracy of household electricity consumption forecasting [4]. Notably, the Long ShortTerm Memory (LSTM) has attracted significant attention [5], [6].

42 ENGINEERING↗
DOE OSTI2026

Model-Based Investigation of Multi-Fault Interactions and Performance Degradation in Residential Heat Pump Systems

Faults in heat pump systems can significantly degrade performance, reduce efficiency, and accelerate component wear, leading to higher operating costs and maintenance demands. While numerous studies have investigated the impact of individual faults, the interactions between multiple concurrent faults remain insufficiently understood, despite their common occurrence in real-world operation. This study conducts a comprehensive simulation analysis of multiple simultaneous faults in a vapor compression heat pump using a validated heat pump design model (HPDM) tool. Detailed component-level modeling methods are implemented to examine performance sensitivity under combinations of refrigerant flow and heat exchanger faults. The results reveal complex fault interactions that can mask or amplify system deviations, challenging conventional diagnostic approaches. Findings from this work provide meaningful insights for the development of more robust fault detection and diagnosis algorithms, supporting improved reliability and energy efficiency in next-generation heat pump technologies.

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗
DOE OSTI2026

Preliminary Assessment for the Electric Load Shifting Potential of Integrating Thermal Energy Storage with Heat Pumps in Residential Buildings in Texas of United States

The widespread adoption of electric-driven heat pumps for heating and cooling is expected to significantly increase electric demand. Cooling electric demand will result in an increase in peak hours electric loads, placing additional strain on the grid during peak hours. This challenge, combined with the current rapidly increasing demand from data centers, exacerbates the electric demand duck curve problem. Integrating thermal energy storage (TES) with heat pump can shift electric use for heating and cooling from peak to off-peak hours of the electric grid, which can help flatten the daily electric demand profile of a building. This paper presents a novel design that integrates heat pump with TES (HP-TES), which uses phase change materials (PCM). Heat pump charges TES by melting or freezing PCM during off-peak hours when there is no thermal demand from the building. TES is then discharged (i.e., by freezing or melting PCM) during peak hours to provide a more favorable heat source or heat sink for the heat pump to meet the thermal demand of the building with lower electricity use than conventional air-source heat pumps. Computer simulations were developed to predict the performance of HP-TES applied to a typical single-family house in the US. The building-level simulation results were scaled up to preliminarily assess the aggregated impacts of deploying HP-TES across all single-family houses in Texas of the United States, including reduction of peak demand of the electric grid.

Anees, Fady [ORNL]↗
DOE OSTI2018

Tracking the Sun: Installed Price Trends for Distributed Photovoltaic Systems in the United States - 2018 Edition

Berkeley Lab’s Tracking the Sun report series is dedicated to summarizing installed prices and other trends among grid-connected, distributed solar photovoltaic (PV) systems in the United States. The present report, the 11th edition in the series, focuses on systems installed through year-end 2017, with preliminary trends for the first half of 2018. As in years past, the primary emphasis is on describing changes in installed prices over time and variation in pricing across projects based on location, project ownership, system design, and other attributes. New to this year, however, is an expanded discussion of other project characteristics in the large underlying data sample. Future editions will include more of such material, beyond the report’s traditional focus on installed pricing. The trends described in this report derive primarily from project-level data reported to state agencies and utilities that administer PV incentive programs, solar renewable energy credit (SREC) registration systems, or interconnection processes. In total, data were collected and cleaned for more than 1.3 million individual PV systems, representing 81% of U.S. residential and non-residential PV systems installed through 2017. The analysis of installed pricing trends is based on a subset of roughly 770,000 systems with available installed price data. Key findings from this year’s report include the following: -Installed Prices Continued to Fall through 2017 and into 2018. National median installed prices in 2017 were $3.7 per watt (W) for residential systems (a $0.2/W or 6% decline from the prior year), $3.1/W for small non-residential systems (a $0.4/W or 11% decline), and $2.2/W (a $0.1/W or 5% decline) for large non-residential systems. Data for the first half of 2018 show an additional drop of $0.1/W for residential and small non-residential systems, and effectively no change for large non-residential systems. These recent trends are generally consistent with the pace of price declines since 2014, and mark a slowing from the years immediately preceding (2009-2013) when prices fell by roughly $1/W per year. -Installed Prices Vary Widely Across Individual Projects. Among residential systems installed in 2017, 20% were priced below $3.0/W (the 20th percentile value) while another 20% were above the 80th percentile at $4.5/W. Non-residential systems also exhibit wide spreads, albeit shifted downward, from $2.4/W to $4.1/W for small non-residential and from $1.8/W to $2.8/W for large non-residential projects. These pricing spreads have persisted over time and are both reflective of the heterogeneity in PV systems and markets, as well as suggestive of the potential for further price declines. -Pronounced Pricing Disparities Exist Across States. State-level median installed prices in 2017 ranged from $2.6/W to $4.5/W for residential systems, from $2.2/W to $4.0/W for small non-residential systems, and from $2.1/W to $2.4/W for large non-residential systems. Three of the largest state markets (California, Massachusetts, and New York) are relatively high-priced, pulling overall U.S. median prices upward. These cross-state pricing differences reflect both idiosyncratic features of particular states as well as more-fundamental differences related to market and policy conditions. -Installed Pricing Variation Also Reflects Differences in System Design, Installer, and Customer Characteristics (among other factors). Significant pricing differences were also observed across system sizes within each customer segment (with median prices ranging from $3.2/W to $4.5/W across residential systems of varying size, and from $2.1/W to $3.7/W across non-residential systems), between third-party owned (TPO) and host-owned residential systems ($3.3/W vs. $3.8/W), across residential installers ($2.1/W to $9.6/W for host-owned systems and $1.1/W to $5.1/W for TPO systems), between residential new construction and retrofit systems in California ($2.3/W vs. $3.9/W), between large non-residential systems at commercial sites and tax-exempt customer sites ($2.1/W vs. $2.6/W), and between systems with standard vs. premium efficiency modules ($3.6/W vs. $4.2/W among residential systems). A public version of the underlying dataset can be downloaded at https://emp.lbl.gov/tracking-the-sun.

14 SOLAR ENERGY↗
DOE OSTI2022

Building Energy Modeling Enhancements to Identify Least-Cost Pathways to Net-Zero Carbon Homes: Preprint

Residential grid-interactive efficient buildings (GEBs) can utilize high levels of energy efficiency and demand flexibility to deliver value to occupants, the grid, and society. However, without the ability to analyze, design, and optimize residential GEBs there is a risk that homes will not realize their full potential value as efficient and dynamic resources, which could ultimately lead to higher than necessary energy costs for U.S. households and lower realization of potential energy efficiency and demand flexibility benefits such as increased convenience/automation, thermal comfort, durability, indoor air quality, and resilience. In 2018, the National Renewable Energy Laboratory (NREL) Residential Modeling Team developed a vision for an open source Residential GEB Analytics Platform built within DOE's EnergyPlus and OpenStudio modeling environment that would enable the design and optimization of residential GEBs, including the identification of least-cost pathways to highly energy-efficient and energy-flexible homes (e.g., net zero carbon homes). We created a detailed workplan for the development of new and enhanced residential GEB component-level models for EnergyPlus and OpenStudio needed to progress toward the vision for the analytics platform while delivering near-term benefits to industry. This paper 1) presents the vision for the platform, summarizing the workplan for residential GEB modeling enhancements; 2) highlights significant advancements that have been achieved between 2018 and 2022, including stochastic residential occupancy modeling, flexible water heater modeling, detailed lithium-ion stationary battery modeling, and realistic residential HVAC modeling; and 3) outlines ongoing efforts and next steps toward the full vision for the platform.

building energy modeling↗
DOE OSTI2019

Quantifying Resolution Implications for Agent-based Distributed Energy Resource Customer Adoption Models

In this report we explore tradeoffs of top-down and bottom-up methods in their precision and computational burden using NREL's dGen model, an agent-based model of residential and non-residential distributed PV adoption. In particular, we assess the role of agent resolution in instantiating statistically-representative populations in the model--and the resulting variance of model projections at the state, sector and county levels. Running the model for a single state with fixed macroeconomic assumptions, we vary both the number of agents instantiated and the number of unique simulations. Notably, in each run we introduce sources of uncertainty in cumulative DPV adoption results during agent instantiation as we stochastically sample agent attributes from localized building characteristic and solar resource distributions. We find three key trends which guide what can be expected of results. First, precision of the model projections, as measured by the variance of the unique simulations increased as a function of the number of agents sampled, though with diminishing returns to scale. The result is expected given the Law of Large Numbers. Second, the mean or expected value of projections decreased as the number of agents instantiated increased. Empirically, aggregate DPV capacities projected by dGen are 7% lower on average at a 10-agent resolution compared to 1-agent resolutions, and up to 10% lower in the non-residential sector. We attribute this outcome to a system sizing scheme that biases lower cumulative installed capacity as agent resolution increases when roof size and load are not positively correlated. Finally, the variance of model projections differed by sector, where variance was substantially larger in the commercial sector, largely due to differences in parameterization by sector. We explain the larger variance in the non-residential sector as an outcome of the greater variance in building uses and load shapes as compared to the residential sector, and we find that a resolution on the order of 100-agents per county would be necessary to bring non-residential variance in line with residential variance at a 2-agent resolution. We propose that further research explore increasing precision and agent resolution in the non-residential sector. Moreover, given that days of intensive computing may be required to resolve a suitable estimate even at the extent of a single state within acceptable levels of precision, to promote computational efficiency we also suggest more clearly quantifying sources of variability at the county level such that resolution can by dynamically increased where county level results are least precise.

14 SOLAR ENERGY↗
DOE OSTI2015

Do PEV Drivers Park Near Publicly Accessible EVSE in San Diego but Not Use Them?

The PEV charging stations deployed as part of The EV Project included both residential and non-residential sites. Non-residential sites included EVSE installed in workplace environments, fleet applications and those that were publicly accessible near retail centers, parking lots, and similar locations. The EV Project utilized its Micro-Climate® planning process to determine potential sites for publicly accessible EVSE in San Diego. This process worked with local stakeholders to target EVSE deployment near areas where significant PEV traffic and parking was expected. This planning process is described in The Micro-Climate deployment Process in San Diego1. The EV Project issued its deployment plan for San Diego in November 2010, prior to the sale of PEVs by Nissan and Chevrolet. The Project deployed residential EVSE concurrent with vehicle delivery starting in December 2010. The installation of non-residential EVSE commenced in April 2011 consistent with the original Project schedule, closely following the adoption of PEVs. The residential participation portion of The EV Project was fully subscribed by January 2013 and the non-residential EVSE deployment was essentially completed by August 2013.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Sighten Final Technical Report DEEE0006690 Deploying an integrated and comprehensive solar financing software platform

Over the project, Sighten built a comprehensive software-as-a-service (Saas) platform to automate and streamline the residential solar financing workflow. Before the project period, significant time and money was spent by companies on front-end tools related to system design and proposal creation, but comparatively few resources were available to support the many back-end calculations and data management processes that underpin third party financing. Without a tool like Sighten, the solar financing processes involved passing information from the homeowner prospect into separate tools for system design, financing, and then later to reporting tools including Microsoft Excel, CRM software, in-house software, outside software, and offline, manual processes. Passing data between tools and attempting to connect disparate systems results in inefficiency and inaccuracy for the industry. Sighten was built to consolidate all financial and solar-related calculations in a single software platform. It significantly improves upon the accuracy of these calculations and exposes sophisticated new analysis tools resulting in a rigorous, efficient and cost-effective toolset for scaling residential solar. Widely deploying a platform like Sighten’s significantly and immediately impacts the residential solar space in several important ways: 1) standardizing and improving the quality of all quantitative calculations involved in the residential financing process, most notably project finance, system production and reporting calculations; 2) representing a true step change in terms of reporting and analysis capabilities by maintaining more accurate data and exposing sophisticated tools around simulation, tranching, and financial reporting, among others, to all stakeholders in the space; 3) allowing a broader group of developers/installers/finance companies to access the capital markets by providing an out-of-the-box toolset that handles the execution of running investor capital through a rooftop solar financing program. Standardizing and improving all calculations, improving data quality, and exposing new analysis tools previously unavailable affects investment in the residential space in several important ways: 1) lowering the cost of capital for existing capital providers by mitigating uncertainty and de-risking the solar asset class; 2) attracting new, lower cost investors to the solar asset class as reporting and data quality resemble standards of more mature asset classes; 3) increasing the prevalence of liquidity options for investors through back leverage, securitization, or secondary sale by providing the tools necessary for lenders, ratings agencies, etc. to properly understand a portfolio of residential solar assets. During the project period, Sighten successfully built and scaled a commercially ready tool for the residential solar market. The software solution built by Sighten has been deployed with key target customer segments identified in the award deliverables: solar installers, solar developers/channel managers, and solar financiers, including lenders. Each of these segments greatly benefits from the availability of the Sighten toolset.

14 SOLAR ENERGY↗
DOE OSTI2023

Next Generation Integrated PV Products Cost and Workflow Analysis (Final Report)

Residential photovoltaic (PV) costs have fallen consistently for over a decade (Ardani et al. 2018). DOE has subsequently developed a new residential PV cost target for 2030 of $0.05/kilowatt hour (SETO 2023). Ardani et al. (2018) conclude that integrated roofing and PV (RIPV) products may be key to achieving the residential target for both new construction and retrofit residential PV. In RIPV, the PV product is incorporated into or replaces the roofing material. RIPV systems can use conventional crystalline or thin-film technologies, may be aesthetically attractive alternatives to traditional racked and mounted PV systems, and may increase building property values (Cook et al. 2023). These products also have the potential to provide customer acquisition, labor, and equipment cost savings over traditional, racked and mounted residential rooftop PV and several companies have recently introduced integrated roofing and PV (RIPV) products (Cook et al. 2023). In 2022, Tesla was the market leader, representing 94% of RIPV capacity installed in 2022 through its Solar Roof offering, while GAF Energy and its Timberline Solar product was second capturing 3% (Feldman et al. 2023). In this project, NREL analyzed three research questions: (1) How do current RIPV products compare to racked and mounted PV in terms of costs, install times and processes? (2) How are RIPV products installed and are there opportunities for cost savings? (3) What are the key barriers to expanding market opportunities for integrating solar and roofing products? In this project, we explored residential RIPV cost reduction opportunities by analyzing installation processes. Our study documented residential RIPV installations at two reroofing sites (20.52 kilowatts) and the equivalent of nine new construction sites (71.75 kW) in California through a methodology known as time and motion study. We also conducted 15 interviews with subject-matter experts to identify barriers and solutions to maximize these products' market penetration.

14 SOLAR ENERGY↗