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At least 181 records · Page 10

Challenges and Opportunities for Basic Efficiency Measures in Low-Income Homes: A Southeast Alaska Case Study

Juneau, Alaska, is the state's capital city and aims to reach 80% renewable energy for the space heating and transportation sectors by 2045. This goal highlights a need to electrify both sectors to take advantage of the inexpensive hydropower available from the local electric utility, Alaska Electric Light and Power. To that end, researchers examined the feasibility of deploying storm windows via a case study of installing storm windows in two local low-income homes. Newer models of storm windows provide an extra layer of insulation over existing windows while preserving operability and views. They can also improve comfort and reduce noise. In addition to conducting pre- and post-installation air leakage tests, energy monitoring, and occupant interviews, researchers worked with the regional housing authority and a local builder to install the storm windows and replace inoperable windows in the two houses in 2021. The team encountered several challenges, including a lack of egress windows, energy data from a wide variety of heating systems, extremely leaky homes, and installation issues, such as windows that were not square. These results point to several barriers to the widespread deployment of window upgrades in the area and open the door to opportunities to design deployment programs that improve safety and efficiency.

cold climate↗

‪A Novel Methodology for Longitudinal Studies of Home Thermal Comfort Perception and Behavior

Human-building interactions significantly influence building energy consumption and affect peak energy demand. For example, heating and cooling contribute 46% of daily peak residential energy demand. Grid-interactive efficient buildings (GEBs) can potentially increase energy-demand flexibility and accelerate the adoption of renewables. However, traditional demand response (DR) programs focused on shedding peak loads disregard the human-building interactions leading to occupant thermal frustration. Specifically, they do not model occupants’ ability to override thermostat controls, nor how indoor environmental conditions and sociocultural factors affect the timing and magnitude of overrides. Studies have found 20% of occupants override thermostat setpoints during DR events longer than 6 hours yet lack detail about the motivation that might guide more successful efforts. Balancing energy-demand flexibility with occupant thermal comfort requires understanding dynamic occupant behavior, the underlying psychophysiological drivers, in the context of homes. This paper presents methods for scalable longitudinal studies of residential occupant behavior dynamics to inform the development of psychophysiological occupant-centric building models. Smart sensors were installed to measure local environmental conditions in 20 homes in two regions of the United States. Just-in-time ecological momentary assessments (EMAs) provided qualitative data on occupant thermal comfort and local environmental conditions not captured in Internet-of-Things (IoT) based studies or existing datasets. Participant interviews provided insight into environmental attitudes, mental models, and the role of economics in comfort and behavior, which in turn may affect thermostat interactions. Based on these data, interventions in the next phase of the study will collect data and monitor occupant behavior during simulated DR events.

Kane, Michael↗

Resources for Homeowners: Home Efficiency Upgrades

A fact sheet to support small business building contractors in communicating with homeowners about potential benefits of home efficiency strategies and suggestions for navigating home upgrades. This work was developed under the Building Business Network (B-Biz) program, which aims to improve adoption of high-performance building technology solutions by collaborating with organizations that support small business contractors that provide and service high-performance building technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Emerging Per- and Polyfluoroalkyl Substances in Tap Water from the American Healthy Homes Survey II

Humans experience widespread exposure to anthropogenic per- and polyfluoroalkyl substances (PFAS) through various media, which can lead to a wide range of negative health impacts. Tap water is an important source of exposure in communities with any degree of contamination but routine or large-scale PFAS monitoring often depends on targeted analytical methods limited to measuring specific PFAS. We analyzed 680 tap water samples from the American Healthy Homes Survey II for PFAS using non-targeted analysis (NTA) to expand the range of detectable PFAS. Based on detection frequency and relative abundance, about half of the identified PFAS were found only by NTA. We identified (with varying degrees of confidence) 75 distinct PFAS, including 57 exclusively detected by NTA. The identified PFAS are members of seven structural subclasses differentiated by their head groups and degree of fluorination. Clustering analysis categorized the PFAS into four coabundance groups dominated by specific PFAS subclasses. One group uniquely identified by NTA contains zwitterionic PFAS and other PFAS transformation products which are likely associated with aqueous firefighting foam contaminants in a small number of spatially correlated samples. These results help further characterize the scope of exposure to emerging PFAS experienced by the U.S. population via tap water and augment nationwide targeted-PFAS monitoring programs.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE Zero Energy Ready Home Case Study HIA 2021: Martha Rose Construction, Abbot’s Alley Net Zero, Sedro Wooley, WA

Case study of a DOE 2021 Housing Innovation Award winning custom home in a marine climate that got a HERS -13 with PV, with 1,804 square feet, highly efficient construction; high-efficiency ductless minisplit heat pumps, appliances, and lighting; triple-pane windows; and 9.9 kW of solar panels on each of the monoplane roofs.

Building America, residential construction, home b↗

Home energy management under realistic and uncertain conditions: A comparison of heuristic, deterministic, and stochastic control methods

We report home energy management systems (HEMS) have been shown to reduce energy bills and to provide grid services including peak demand reduction and demand flexibility. However, uncertainty in residential energy systems is a significant issue and can reduce the benefits of a HEMS to the homeowner or grid operator. Sources of uncertainty include weather forecasts, predictions of energy-related occupant activities (e.g., hot water draws), and parameter estimation for the building envelope and energy-consuming equipment. This paper tackles the problem of uncertainty by developing a framework that simulates HEMS in uncertain conditions and evaluates the performance of multiple control strategies. A linear, reduced-order residential building model for model predictive control applications is derived and compared to a full-order model. Stochastic model predictive control is shown to perform better than deterministic and heuristic methods when considering realistic forecasts with uncertainty. The framework can evaluate the performance of HEMS in real-world applications, which can help de-risk HEMS deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Potential impact of work from home jobs on residential energy bills: A case study in phoenix, AZ, USA

Nearly one-third of U.S. households face challenges paying energy bills. During the day, many residents have routine access to cooled environments provided by others—employers, shopping centers, and other public buildings. The COVID-19 pandemic, however, has significantly shifted the cost burden of air conditioning in hot cities. Specifically, during the pandemic, many companies either laid off employees or put them in work-from-home (WFH) assignments. Large tech companies are already promoting WFH as a long-term option for their employees, even after the pandemic. This change in the nature of the workforce might reduce daily travel expenses for workers, but could also significantly increase residential energy bills, particularly during summer in very hot climates. Here, this study uses building energy simulations to quantify the potential residential energy bill penalties resulting from WFH for typical residences in Phoenix. Four building archetypes are used in this study to represent variations in building vintage, occupancy, and characteristics. The results show that, for some single-family residences in Phoenix, WFH can increase annual energy bills by more than $1100 (up to a 70% increase). The study also demonstrates that building performance enhancement retrofit measures have the potential to reduce this WFH energy bill penalty for the existing buildings substantially.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An Empirical Validation of a Constrained Bin Packing Algorithm for a Home Energy Management System

The increasing number of intelligent electrical appliances and home energy management systems provide a big opportunity for demand response services from residential and small commercial buildings to the grid. Simultaneously, direct control of individual devices by utilities can cause communication bottlenecks, as well as coordination and privacy concerns. These challenges can be addressed by combining the constituent devices into a single house battery equivalent for the purposes of demand response, using Minkowski sum and a 2d bin packing problem. However, the well-studied traditional problems have not been tested in a real house, as implementation carries significant challenges of its own. We deploy the packing problem on residential devices in a controllable house. We report the barriers we found, such as charge forecast and scalability of the algorithm, and discuss our solutions. The study serves as an intermediate step between existing theoretical research and possible future steps, such as prototype deployments of systems that provide residential demand response.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Magnetotelluric Data from Mountain Home, ID

This dataset includes magnetotelluric transfer functions in the form of EDI files for 16 stations collected by the USGS and 40 stations collected by Quantec Geoscience for Lawerence Berkeley National Lab around the Mountain Home area in Idaho. A 3D electrical resistivity model is included that images resistive and conductive bodies in the subsurface that maybe important for geothermal characterization. The model was created using ModEM using the high performance computer Yeti at the USGS.

15 GEOTHERMAL ENERGY↗

Honda Smart Home - Davis, CA

The Honda Smart Home demonstrates zero-carbon living and transportation capacity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Residential Home Repairs, Energy Efficiency, and Electrification in the Hill District of Pittsburgh [Slides]

Through Communities LEAP, a community coalition focused on the Hill District neighborhood of Pittsburgh is working with a technical assistance provider network led by the National Renewable Energy Laboratory (NREL). The coalition includes community organizations, nonprofits, the city government, and the utility. Technical assistance provides analysis and information to support Hill District stakeholders in their goals to create informed residential energy efficiency and renewable energy transition strategies. This report summarizes the insights from stakeholder engagement with organizations that provide home repair services, weatherization, and residential energy efficiency in the Hill District as well as from a building analysis to characterize Hill District housing stock and the potential costs and benefits of energy efficiency and electrification measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy Efficiency Field Study: Influence of Key Measures in Home Rules States

The goal of the Energy Efficiency Field Study: Influence of Key Measures in Home Rule States project is to empower and support the states of Utah and Arizona in the successful implementation of their building energy codes. Employing the Department of Energy (DOE) Residential Building Energy Code Field Study Data Collection & Methodology, the research team evaluated real-world implementation status against a baseline, with a particular focus on the unique challenges presented by the dry, hot climates of Utah and Arizona.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Housing-Performance Atlas of Baltimore Row Homes: Archetype-Based Multi-Hazard Baseline of Energy, Heat, Survivability, and Durability

Baltimore’s historic row-home neighborhoods face escalating risks to energy, heat, and durability under intensifying climate stress. This study develops a Housing-Performance Atlas that quantifies multi-hazard performance for eight representative archetypes using DesignBuilder/EnergyPlus Version 7.3.1.003, under Baltimore TMY3 boundary conditions. Performance is evaluated across the following four adaptation domains: energy use intensity, passive survivability during 72 h outage events, roof overheating exposure (>150 °F exceedance hours), and material service life derived from ISO 15686 and synthesized into Lean and Full Deficit Indices for comparative resilience ranking. Results show that EUI ranged from 46.7 to 67.6 kBtu ft −2 ·yr −1 , survivability from 0 to 23 h, and roof temperatures exceeded 150 °F for 150–210 h, shortening roof service life by up to 10 years. Composite Lean and Full Deficit Indices ranged 7.8–92.4, ranking Model 5 (end-unit, flat roof, two-story with basement) as the most resilient configuration and Model 8 (end-unit, pitched roof, three-story above-grade) as the least resilient due to compounded overheating and energy losses. Heat-related domains accounted for nearly 70% of overall resilience deficits, confirming thermal safety and roof reflectivity as retrofit priorities. The Housing-Performance Atlas establishes a reproducible diagnostic framework linking simulation, service life, and resilience metrics to guide cost-effective, climate-responsive retrofits in Baltimore’s aging urban housing stock.

Housing-Performance atlas↗

Sensitivity-Informed Bayesian Inference for Home PLC Network Models with Unknown Parameters

Bayesian inference is used to calibrate a bottom-up home PLC network model with unknown loads and wires at frequencies up to 30 MHz. A network topology with over 50 parameters is calibrated using global sensitivity analysis and transitional Markov Chain Monte Carlo (TMCMC). The sensitivity-informed Bayesian inference computes Sobol indices for each network parameter and applies TMCMC to calibrate the most sensitive parameters for a given network topology. A greedy random search with TMCMC is used to refine the discrete random variables of the network. This results in a model that can accurately compute the transfer function despite noisy training data and a high dimensional parameter space. The model is able to infer some parameters of the network used to produce the training data, and accurately computes the transfer function under extrapolative scenarios.

42 ENGINEERING↗

Validation of HVAC Hardware-in-the-Loop Simulation for Advanced Control Strategies in Smart Homes: Preprint

Residences with smart thermostats can use advanced control strategies to manage their cooling/heating demand, but it is difficult to evaluate optimal control strategies for flexible heating, ventilation, and air conditioning (HVAC) systems in a traditional laboratory setting. The HVAC hardware-in-the-loop (HIL) system combines physical HVAC equipment and a physical thermostat with a simulated house to enable realistic operation of the hardware in any climate. This HIL platform allows researchers to evaluate advanced control strategies for homes with different construction or vintage types, as well as different climates and occupancy schedules. To demonstrate the capabilities of the HVAC HIL system, experimental results with a SEER 16, HSPF 9.5, 3 ton single-speed air source heat pump are validated against past field data collected from a heavily instrumented, unoccupied, retrofit house located in Sacramento, California. Three different cooling strategies are recreated in the HVAC HIL platform, including two different pre-cooling schedules that were designed to shift energy use away from the evening peak. The room temperatures, heat pump energy use, and run time show good agreement between the field data and HIL experimental results for three strategies.

cooling strategies↗