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At least 109 records · Page 6

Potential Heating Energy and Cost Savings of Dual Fuel Heat Pump Controls as a Residential Building Equipment Retrofit in the U.S.

This study investigated the energy and cost savings potential by modeling a dual fuel heat pump system with its control for a residential building in (5A) cold climate in U.S. The simulation analysis showed that the application of the DFHP system and its control to the target building can save the heating energy by 42% over a gas furnace system (baseline system). Although the HP-only system can save more heating energy (i.e., 53%) over the baseline system than DFHP system does, the DFHP with its control demonstrated the higher cost savings when a time of use electricity rate was considered.

Yoon, Yeobeom↗

ResStock Dataset 2024.1 Documentation

Public ResStock datasets provide credible, relevant, and accessible information on energy use and related non-energy metrics to a variety of stakeholders in the residential buildings space. The current public datasets include baseline building characteristics, timeseries (15-minute) energy consumption, and timeseries carbon emissions for the baseline (existing) U.S. housing stock and the U.S. housing stock with 10 "what-if" energy measure packages applied. This report documents a new public ResStock dataset to complement and build upon the existing public datasets. This dataset is specifically intended to be a resource for state and local decision-makers considering options for energy retrofits for their housing stock to reduce carbon emissions, energy use, and/or utility bills. These data consist of housing stock characteristics and modeled full-year energy consumption, carbon emission, energy bill, and energy burden data for the baseline U.S. housing stock as well as the U.S. housing stock with 260 "what-if" energy measure packages applied. These measure packages include measures related to the building envelope, appliances, pools and spas, lighting, water heating, and HVAC (including efficiency improvements and fuel switching with equipment at a range of performance levels) in a variety of combinations. This report provides methodology information on the generation of this dataset and serves as a key part of the dataset's public documentation.

buildings↗

ResStock Measure Documentation: Residential Variable-Speed Geothermal Heat Pump (4.4 COP, 30.9 EER)

The goal of this work is to develop energy efficiency, demand flexibility, and other retrofit end-use load shapes (electricity, gas, propane, or fuel oil) that cover a majority of the high-impact, market-ready (or nearly market-ready) measures. "Measures" refers to retrofits that can be applied to buildings during modeling. An "end-use savings shape" is the difference in energy consumption between a baseline building and a building with an energy efficiency, demand flexibility, or other retrofit measure applied. It results in a time-series profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each time step. ResStock (TM) is a highly granular, physics-based, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the residential building stock across the United States. The baseline model intends to represent the U.S. residential building stock as it existed in 2018. Technical documentation for the inputs and assumptions in the baseline building stock model is available in Reyna et al. (2025). Calibration and validation of the baseline model results are available in the final technical report of the End-Use Load Profiles project (Wilson et al. 2022). This documentation focuses on a single end-use savings shape measure: Residential Variable-Speed Geothermal Heat Pump (GHP). This document provides the relevant new modeling information for variable-speed systems not previously covered in either the single-stage or two-stage documents. Variable-speed GHPs represent the most efficient option available for this technology: They provide the most savings, with up to 46% for the applicable portion of the housing stock, compared to 31% for less efficient single-stage GHPs. Additional results shown here detail how the savings change for sections of the housing stock with different base heating fuels and in different climate zones, and they show the savings potential by state for both heating and cooling. Utility bills and electric panel impacts are also shown and discussed.

15 GEOTHERMAL ENERGY↗

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↗

Hierarchical Model-Free Transactive Control of Building Loads to Support Grid Services

Residential buildings consume 4.4 quads of electricity annually, approximately 37% of the total electricity consumption in the United States. This represents a vast resource that can be used for demand management and other ancillary services. This project aims to develop a robust, scalable hierarchical transactional control mechanism incorporating elements of model-free control (MFC) and game theory to harness buildings to provide ancillary services to the grid. This approach is being taken to address the challenges of incorporating traditional transactional control schemes into existing buildings. The challenges include small individual building sizes requiring aggregation of many buildings, unpredictable energy usage that makes model identification difficult, and satisfying the sensitive occupant comfort constraints. In the proposed approach, by separating the control mechanism into two layers above and below the load aggregator, MFC can be used below the aggregator to modulate flexible building loads in response to pricing signals with guaranteed performance. This allows the burden of identifying an accurate model of the system to be shifted to the above-aggregator layer, where fluctuations in individual building usage have less impact on predicted building system behavior. Game theory concepts can then be used to determine pricing curves and control signals among regional aggregators. Managing this control in a game-theoretic approach will allow us to build in financial incentives that increase customer engagement. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable on small, embedded devices. In a broader sense, developing a strategy capable of effectively incorporating residential and small commercial buildings will allow greater throughput of existing and emerging grid services in addition to future transactive energy grid management methods. Using MFC within a hierarchical control architecture will allow the shifting of existing forecasting challenges to an aggregate level, where dynamics are slower and more predictable. This will enable a smooth interface between the grid services requests of utilities and the reliable control required by participating buildings. MFC, which supports distributed control architecture, permits a scalable solution that can be deployed to neighborhood-size systems as well as individual buildings. This project focuses on three objectives: (1) developing the mathematical framework, algorithm toolkit, and software toolset of the two-layer transactive control testbed; (2) developing a scalable solution for application over many residential and small-size commercial buildings with sparse distributed communication; and (3) field testing and implementation on hardware of the control strategies developed in the previous two objectives. The research and development activities are focused and designed to be impactful within the relevant 2025 targets timeframe. An open-source control framework for exploiting variability and dispatchability of building loads will be delivered as the outcome of the project. This capability enables greater participation of loads in electricity markets and ancillary services that are both useful for the utility and financially beneficial for building owners.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Digital System-On-Chip CO 2 Sensor (Final Report)

The overall goal of the project was to build a low-cost digital CO 2 sensor made of N5’s patented sensing architecture using a digital application specific integrated circuit (ASIC) to reduce the amount of energy usage in residential and commercial buildings. The proposed small form-factor CO 2 monitoring device contains a molecular sieve membrane filter capable of monitoring indoor air quality which indicates the content of CO 2 inside a residential or commercial building.

36 MATERIALS SCIENCE↗

Integration of Thermoelectric Modules to Vapor Compression Systems

This paper describes the technology of a thermoelectric (TE) integrated heat pump. It uses a TE heat pump to subcool the refrigerant liquid before entering the evaporator to enlarge the evaporating capacity; and elevate the heat in the refrigerant flow to a supplemental heating coil and discharge the capacity to the indoor air flow. Using the DOE/ORNL Heat Pump Design Model, four system configurations were modelled on a baseline two-speed heat pump, the baseline heat pump with adding a supplemental coil, the TE integrated heat pump having one stage TE heating to control a 20R liquid refrigerant temperature drop; and having two stages TE heating to control up to 40R temperature drop. The system models were used to produce performance curves for EnergyPlus building energy simulations. We selected template residential buildings, poorly insulated: pre-1990 buildings, and well-insulated: IECC2021 buildings; in five cold climate zones: 5A, 5B, 6A, 6B, 7. The building energy simulations demonstrated energy saving potentials, utility cost reductions and estimated payback periods.

Shen, Bo↗

Simulation, Challenge Testing & Validation of Occupancy Recognition & CO 2 Technologies (Final Project Report)

This final report covers the results of the development of testing methods of occupancy sensor systems connected to HVAC controls. This project focused on the development of test methods to evaluate the performance of HVAC-connected occupancy sensor systems, including occupancy presence, occupancy counting, and CO 2 sensor systems in commercial and residential buildings. This included evaluation of the reliability, ease of commissioning, and energy savings potential of these sensor systems. The results of this work help to standardize the methods used to evaluate performance, to enable the ability to compare sensor system performance following the same methods, to understand which sensor systems perform better or worse compared to others. The U.S. building stock’s energy usage can benefit substantially from having building system operations informed by reliable occupancy recognition and CO 2 measurements, however to date, standard methods have not been in place to ensure that sensor systems’ reported performance is uniformly evaluated. The results of this work support the development of a standard or guideline that outlines the developed methods of testing. This project also included the testing of both off-the-shelf and novel SENSOR team-developed low-cost occupancy sensor systems, using the developed methods of testing. The results of this testing helped to inform further development and improvement of new low-cost sensor systems that will benefit from being used in residential and commercial buildings throughout the country.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluation of Interior Cellular Shades in a Residential Building

Windows are major contributors to energy demand in residential homes because of their inferior thermal resistance compared with the opaque envelope and sometimes from unwanted solar heat gain. Window attachments can help to mitigate this demand by controlling the solar heat gains and enhancing the thermal resistance of the windows. In this study, the energy savings potential of cellular shades in residential homes is studied using experimental testing and energy simulations. The energy performance of the shading devices was experimentally tested during the heating season from December 2019 to May 2020 with a focus on cellular shades. Five shading devices—three single and two double cellular/cell-in-cell shades—were used to compare the performance with generic horizontal (venetian) blinds using two nearly identical sideby-side rooms in a residential building with their exterior window facing east. Another objective of the experimental testing was to evaluate any impact of the side-channel of the shading device on energy savings. To observe the impact of the side-channels on energy savings, from shades in two of the test cases, cellular shades with side-channels were used. From the experimental testing, daily energy savings in the range of 9% to 23% were observed by considering data from 6 p.m. until 6 a.m. of the next day.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Smart thermostat data-driven U.S. residential occupancy schedules and development of a U.S. residential occupancy schedule simulator

Occupancy schedule is one of the key inputs in Building Energy Modeling (BEM) to reflect the interaction between buildings and occupants. Over the past decades, standardized occupancy schedules, developed mainly by engineering rule-of-thumb, have been widely used in BEM due to its simplicity and lack of real measured occupancy data. However, the BEM community has recognized their association with uncertainty and reliability in simulation results from BEM. This study introduces representative occupancy schedules in the U.S. residential buildings, derived from a large smart thermostat dataset and time-series K-means clustering, and an open-source tool to generate a stochastic residential occupancy schedule. Over 90,000 residential occupancy schedules were estimated from the ecobee Donate Your Data dataset. Then, the representative occupancy schedules were identified through clustering. This study further investigated the impacts of three parameters (day, house type, and state) on residential occupancy schedules. Then, a tool, the Residential Occupancy Schedule Simulator (ROSS), is developed using the representative occupancy schedules derived in this study. Details of this tool are presented in this paper. In conclusion, the derived representative occupancy schedules and the ROSS tool can help improve the energy modeling of residential buildings.

42 ENGINEERING↗

Nova Analysis: Holistically Valuing the Contributions of Residential Efficiency, Solar and Storage

Policies to address climate change and grid modernization, in combination with cost reductions and technological advancements in energy efficiency (EE) and distributed energy resources (DER), are driving rapid deployment of building electrification and energy efficiency retrofits, rooftop solar photovoltaics (PV), smart thermostats, smart water heaters, and battery energy storage. In residential buildings, there are multiple stakeholders (occupant, utility, aggregator, society at large) that are each focused on different value streams. This project uses a suite of metrics intended to all of these value streams to try to holistically analyze the benefits that come from solar, storage, and energy efficiency. To demonstrate the value of these metrics, a semi annual study was performed simulating hundreds of homes across the U.S. under several different upgrade scenarios.

14 SOLAR ENERGY↗

Analysis of Building Model Forecasts using Autonomous HVAC Optimization System for Residential Neighborhood

Heating, ventilation, and air conditioning (HVAC) systems account for the highest share of home energy consumption in the United States. Optimized HVAC control can provide thermal improved comfort to the occupants, improve energy efficiency, reduce energy cost, and support grid services. In this paper, we discuss a multi-agent and cloud-based software framework that has been deployed in occupied residential neighborhood. This system enables automatic data collection, learning, optimization, and dispatches signals to neighborhood devices. HVAC optimization is based on model predictive control (MPC). Since the operational performance of MPC depends on model forecasting accuracy, it is crucial to evaluate the model continuously and modify or retrain it as necessary. In this research, we developed an automated workflow to evaluate the performance of temperature and power forecasts based on measured data in the real world. This will provide researchers with a deeper understanding of the model and how it can be improved.

Lebakula, Viswadeep↗

End-Use Load Profiles for the U.S. Building Stock

The United States is embarking on an ambitious transition to a 100% clean energy economy by 2050, which will require improving the flexibility of electric grids. One way to achieve grid flexibility is to shed or shift demand to align with changing grid needs. To facilitate this, it is critical to understand how and when energy is used. High quality end-use load profiles (EULPs) provide this information, and can help cities, states, and utilities understand the time-sensitive value of energy efficiency, demand response, and distributed energy resources. Publicly available EULPs have traditionally had limited application because of age and incomplete geographic representation. To help fill this gap, the U.S. Department of Energy (DOE) funded a three-year project, End-Use Load Profiles for the U.S. Building Stock, that culminated in this publicly available dataset of calibrated and validated 15-minute resolution load profiles for all major residential and commercial building types and end uses, across all climate regions in the United States. These EULPs were created by calibrating the ResStock and ComStock physics-based building stock models using many different measured datasets, as described in the "Technical Report Documenting Methodology" linked in the submission.

Array↗

Data-driven occupant-behavior analytics for residential buildings

Many advances have been made in building technology to help save energy, but influencing the behavior of the occupants is still necessary to achieve low-energy use targets. One of the most practical ways to influence and change occupant behaviors is through incentives. Developing incentives for energy-saving and quantifying the impact of occupant behaviors are both active areas of research. Here, we propose a data analytics framework for detecting changes in occupant behaviors, which will help build an analytics feedback loop from behavior impact to incentive design. The framework has two major parts. The first forecasts energy consumption for each occupant, while the second determines a probability distribution for changes in energy consumption. The parts are interchangeable with other existing machine learning and statistical methods. A specific instantiation of the framework, using kernel ridge-regression for forecasting and k-means to find an empirical behavior distribution, is described in detail. An HVAC use-case with 5 different incentivized behaviors is used as an example to show that the framework can detect behavior changes induced by incentives. Furthermore, we show that some simpler behavior-change detection methods do not work, further justifying the use of advanced analytics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy Savings With Acceptable Indoor Air Quality Through Improved Airflow Control in Residential Retrofits

The Partnership for Advanced Residential Retrofit (PARR) has been a U.S. Department of Energy (DOE) Building America team since 2009, with a primary focus on upgrading the performance of existing buildings to reduce energy loads. In this project, PARR’s work explored the integration of airflow-focused measures in residential retrofit homes with the goal to maximize energy savings while ensuring acceptable indoor air quality (IAQ) using a systems approach to controlling four contributing air streams: • Building air leakage (natural, uncontrolled infiltration), • Forced-air distribution system static pressure and airflow rate, • Distribution system duct leakage, and • Mechanical ventilation. This project addressed airflows in houses, their combined impact on energy use and IAQ, and the comparative effects of typical insulation and air sealing practices versus integrated system-level retrofits. Additionally, practical considerations for contractors taking either approach were addressed. Finally, the effects of supply ventilation and exhaust ventilation on IAQ were compared in occupied homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Perform Life Cycle Energy and GHG Emission Analysis, Select Candidate Refrigerant(s), Developing Heat Pump by Using Low-GWP Refrigerants and 5 mm Diameter Tubes

Reducing environmental impacts from the energy conversion systems has been an important research topic due to recent severe global climate changes. In residential buildings, the space heating and cooling are main energy consumers, which are relying on vapor compression based heat pumps. To mitigate the environmental impacts of residential systems, the heat pumps using low-GWP refrigerants and 5mm-tube heat exchangers are proposed to replace the conventional 9 mm or 7 mm tube heat exchangers. This research uses a simulation-based design method to optimize the refrigerant circuitries of a 5-ton low-GWP refrigerant heat pumps whose indoor and outdoor heat exchangers adopt 5 mm tubes. Heat pump systems using four commercially available low-GWP refrigerants (R454A, R454C, ARM20A and ARM20B) are optimized and compared with the baseline R410A system. The results indicate that directly replacing 9 mm tubes into 5mm tubes in the baseline systems induces heat pump performance degradation; by optimizing the 5 mm tube heat pumps with added tube rows, the system refrigerant charge is reduced up to 33% compared with the baseline; the optimized low-GWP 5 mm tube heat pumps offer the same or higher performance under both cooling and heating mode; that under cooling mode, the EER improvement is up to 10.7% and under heating mode the COP improvement is up to 3.4%; and a smart flow control device to maintain counter-flow circuitry pattern on both operating modes can improve the heating performance of 5 mm tube optimized system by up to 3.0%. In an effort to better understand the environmental impacts of these systems, life cycle climate performance (LCCP) evaluation method is used to assess the baseline and optimized systems. LCCP considers the direct and indirect emissions of the system over the course of its lifetime from manufacturing to disposal. Our analyses indicate that the optimized systems using 5mm tubes and low-GWP refrigerants can reduce life-cycle CO 2 emission significantly. And improving system efficiency is the most effective way to reduce the emission of low-GWP refrigerant systems. This report shows that using 5 mm diameter tubes in heat exchangers is a feasible approach to develop heat pumps with low-GWP refrigerants. Using the proposed design approach can yield higher system efficiency with lower environmental impact.

42 ENGINEERING↗

Experimental and data-driven characterization of window-induced air leakage in residential buildings

Windows contributes up to 40% of envelope heat losses and around 9% of total building energy consumption due to air leakage. In the U.S., 48 million homes still use single-pane windows. Although the U.S. has an estimated 1.4 billion windows in its building stock and about 24 million windows are installed annually, only around 29 million individual window replacements (∼2%) occur each year. To address this gap, this study generates empirical evidence by (1) evaluating the contribution of windows to whole-building air leakage in 20 residential buildings using blower door tests before and after window replacement and (2) assessing whether building and window characteristics influence the measured change. Most simulation studies assume that replacing windows not only lowers the U-factor but also reduces air leakage by 10–20%. However, this assumption lacks empirical validation, highlighting the need for experimental analysis of air leakage specifically associated with windows. Using blower door tests in accordance with ASTM E779–19, the results indicated an average reduction in air infiltration of 6.1% within the range of 0.5–19.30% across all buildings and no significant correlations were found between air leakage improvements and any building/window characteristics. This research aims to help homeowners, and energy modelers to provide empirical data on importance of upgrading to more energy-efficient windows, supporting energy-efficient building standards.

Air leakage↗

Lawrence, Massachusetts, Residential Building Efficiency and Electrification Analysis [Slides]

As part of the Communities Local Energy Action Program (CLEAP), the Lawrence Stakeholders Coalition (LSC) is interested in assessing and understanding the potential for and pathways to electrification for the City of Lawrence. The LSC's main questions are: What is the impact of various electrification packages on residential electricity bills and what types of buildings should the LSC target for electrification plus weatherization packages? This technical assistance, using ResStock tool modeling, aims to assist the Coalition's electrification and energy burden reduction planning by: 1. Providing cross-cutting data on housing stock characteristics, energy burden characteristics, fuel types, energy consumption, and system efficiency; and 2. Providing information on upgrade package costs, emissions reduction, and energy reductions by prioritized housing segment. The ResStock analysis presented here focuses on opportunities to reduce energy burden, energy consumption, and energy bills for single family homes, multifamily buildings, and mobile homes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗