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Learn about types of heating and cooling systems, system maintenance, and best practices for saving energy with your heating and cooling. This fact sheet from Energy Saver also includes information on buying a new heating or cooling system; efficiency ratings; and selecting new systems including air conditioners, heat pumps, and furnaces.
Extreme heat conditions pose significant indoor survivability challenges for resource-constrained communities, which often lack access to cooling, have poorly insulated homes, and face compounding socioeconomic vulnerabilities. Moreover, concurrent power outages worsen health risks and heat-related illnesses. It is therefore crucial to develop innovative and affordable cooling approaches to protect vulnerable populations. This study assesses the efficacy of “cool rooms”– a designated space within a home equipped with passive and low-power active cooling measures to maintain safe indoor temperatures during extreme heat events and power disruptions. Using a physics-based building energy modeling approach, we evaluate the efficacy of various retrofit packages in maintaining thermal safety within the cool room under recent extreme heat conditions. The results indicate that passive measures can reduce 64% of hours with unmet standard effective temperatures, while the combination of passive and low-power active measures with built-in batteries further cuts this to 86%. Nevertheless, these strategies remain insufficient to maintain indoor thermal safety during extended outages. In contrast, integrating a solar-powered mini-split heat pump, whose technical potential was evaluated in this study, reduces indoor air temperatures below the 28 °C overheating threshold and significantly improves indoor habitability. The localized cool room strategy also offers potential for grid resilience by reducing peak electricity demand by up to 70% compared to whole house cooling during heat waves. The findings can inform the development of actionable heat mitigation plans and retrofit policies for residential communities with relatively low adoption of air conditioning such as warm marine climates.
Heat pumps offer a great low carbon emission method to heat homes. Thermalize Juneau 2021 was a clean energy campaign that helped homeowners in Juneau, Alaska install heat pumps into their homes. Juneau is located near the climactic limit of many heat pumps, and we were interested in how well the heat pumps can function in cold climates. This was done by using Sense meters to remotely monitor the energy usage of 10 homes with heat pumps. The Sense meters are small devices that connect to the electrical panel and monitor the energy use of multiple appliances through machine learning. First, we recorded the energy usage of a heat pump in the lab using both the Sense meter and the existing lab datalogger. Both recorded very similar energy usage data which confirmed that the Sense meter can accurately measure the fluctuations in the heat pump energy use. Next, we looked at the energy data from the Sense meters in the homes with heat pumps and paired it with local weather data to see how well the heat pumps functioned in the cold weather.
In 2018, the Bureau and City of Juneau set the goal of reaching 80% renewable energy in the sectors of transportation and space heating by 2045. This effort will minimize their reliance on fossil fuels, reduce their carbon footprint and increase their resilience in the event of a natural disaster as fuel oil reaches Juneau by boat and such shipments may be disrupted in a disaster. The community's resilience in the face of a disaster and lower carbon footprint goes hand-in-hand with public safety and health. The Cold Climate Housing and Research Center (CCHRC) partnered with several local and statewide groups, including Alaska Heat Smart and Information Insights, Inc, to lead Alaska's first thermalize campaign. Thermalize Juneau 2021 is an energy campaign working to lower the cost of heating homes in Juneau through beneficial electrification and increased energy efficiency. The goal of the campaign was to offer homeowners a streamlined and more affordable way to install heat pumps and energy efficiency improvements into their homes. Converting household heating from fuel to electricity also helps improve indoor and outdoor air quality and reduces maintenance requirements. The campaign had over 160 participants. As of Fall 2021, it is in its final stages of heat pump installations and energy efficiency improvements. In addition to tracking the energy savings and carbon reduction attributed to the campaign, the social equity was an important aspect. Thermalize Juneau attempted to include all the demographics present in Juneau in the campaign. The presentation will cover the goals and implementation of the campaign, current data on how it is improving community and household resilience, lessons learned, and next steps.
Remote, cold climates present challenges to finding safe and affordable options to heat homes. In Alaska, residential ground source heat pumps (GSHPs) have been gaining in popularity to fill this gap. However, there is little research on their long-term performance or effect on soil temperatures. The extended heating season and cold soils of Alaska provide a harsh testing ground for GSHPs, even those designed and marketed for colder climates. The large and unbalanced heating load of cold climates creates a challenging environment for GSHPs. In 2013 the Cold Climate Housing Research Center (CCHRC) installed a GSHP at its Research and Testing Facility (RTF) in Fairbanks, Alaska. The heat pump replaced an oil-fired condensing boiler heating a 464 m2 office space via an in-floor hydronic radiant heating system. The ground heat exchanger (GHE) was installed in moisture-rich silty soils underlain with permafrost near 0°C. The intent of the installation was to observe and monitor the system over a 10-year period in order to develop a better understanding of the performance of GSHPs in sites with permafrost and to help inform future design. As of this writing, the heat pump system has been running for seven heating seasons. The efficiency in those seven heating seasons has been variable with ups and downs that have been difficult to explain. This paper seeks to understand the variability in performance as well as make recommendations for GSHP use in other cold climates.
In 2018, the City and Borough of Juneau, Alaska set the goal of reaching 80% renewable energy for heating and transportation by 2045. An important factor to help reach this goal is finding energy efficiency home heating technologies such as ductless air source heat pumps (DHPs), which rely on the local hydropower electric grid to provide space heating for an entire home or a main living area. To help residents reduce energy costs and move toward the community renewable energy goal, a team of local, state, and national partners joined to run Thermalize Juneau 2021, an energy campaign that provided education, a simplified installation process, and a bulk purchase discount. Overall, the campaign enrolled 165 participants, resulting in 75 DHP installations and over 30 energy efficiency improvements. To evaluate the reliability and energy use of the DHPs installed during the Thermalize Juneau campaign, researchers installed energy monitors on heat pumps of 14 participants and conducted interviews with homeowners. Data from two heating seasons (2021-2022 and 2022-2023) has allowed researchers to examine the accuracy of pre-campaign energy savings predictions, establish energy savings for a small group of households, and provide insights on the energy use and occupant satisfaction of DHPs which will help to inform future heat pump deployment efforts in the area.
In 2018, the City and Borough of Juneau, Alaska, set the goal of reaching 80% renewable energy for heating and transportation by 2045. An important factor to help reach this goal is energy-efficient home heating technologies such as ductless air- source heat pumps (DHPs), which rely on the local hydropower electric grid to provide space heating for an entire home or a main living area. To help residents reduce energy costs and move toward the community renewable energy goal, a team of local, state, and national partners joined together to run Thermalize Juneau 2021, an energy campaign that provided education, a simplified installation process, and a bulk purchase discount. Overall, the campaign enrolled 165 participants, resulting in 75 DHP installations and over 30 other energy efficiency improvements. To evaluate the reliability and energy use of the DHPs installed during the Thermalize Juneau campaign, researchers installed energy monitors on heat pumps of 14 participants and conducted interviews with homeowners. Data from two heating seasons (2021-2022 and 2022-2023) allowed researchers to examine the accuracy of pre-campaign energy savings predictions, establish energy savings for a small group of households, and provide insights on the energy use and occupant satisfaction of DHPs, which will help inform future heat pump deployment efforts in the area.
Geothermal heat pumps can be great alternatives to air conditioners and furnaces, and require less electricity to run. This case study focuses on Medford Site Veterans Home and is part of a series: https://www.energy.gov/eere/geothermal/geothermal-heat-pump-case-studies.
Water heating constitutes approximately 18% of energy consumption and is the second largest energy expenses in United States homes. Heat pump water heaters (HPWHs) are energy efficient technologies with lower carbon footprints as compared to conventional water heating technologies, such as gas and electrical resistance heaters. The performance of water-source HPWHs can be improved by recovering heat from blackwater using drain heat recovery heat exchangers. Depending on water draw patterns of single family and multifamily residences, the operation and heat transfer performance of these heat exchangers are highly transient. This paper examines the thermo-hydraulic performance of a drain heat recovery heat exchanger during its transient and steady-state operations. The heat recovery performance of the exchanger was evaluated at different inlet temperatures and flow rates ranging from 9°C to 36°C and 0.03 kg/s to 0.28 kg/s, respectively. The obtained effectiveness varies from 45%–85% depending on the operating conditions. The test facility, steady-state and transient experimental procedures are reported in detail. Further, the effect of operating conditions on the effectiveness is discussed. The experimental approach and results of the study will provide insights into the transient operation of drain recovery heat exchangers as well as, guide sizing for various steady state conditions.
The LNPK 156 Geothermal Coalition formed around the idea of building a new geothermal heating and cooling system in Duluth, MN for the Lincoln Park Justice40 neighborhood. The Coalition has been spearheaded by the City of Duluth and the local non-profit Ecolibrium3, and is named after the census tract of the neighborhood containing large portions of Lincoln Park, as well as a wastewater treatment plant, managed by the Western Lake Superior Sanitary District (WLSSD). The idea of building a geothermal system came to fruition over the period of about a decade, with repeated observations that the warm water discharged from the wastewater treatment plant was an energy-rich resource that has currently been untapped and released into the St. Louis River. The objective of this project was to build a geothermal system that harnesses wastewater heat recovery methods and satisfies the demand in a portion of Lincoln Park – a neighborhood experiencing high energy burdens, low life-expectancy, and where the natural gas and fuel oil used to heat homes and businesses results in decreased air quality and increased carbon emissions. The goal was to utilize this wastewater heat recovery method to benefit the neighborhood hosting the wastewater plant itself.
In the transactive energy (TE) paradigm, the devices of participative consumers, or prosumers, may be aggregated and employed to drive operational objectives at the network level. Home heating, ventilation and air-conditioning (HVAC) systems in particular are well-suited to modulate their behaviours based on both home thermal flexibility and requests from the utility grid. This paper develops a robust, hierarchical power dispatch scheme in the context of a residential distribution network. The formulation couples a unique, multiphase linear distribution optimal power flow (OPF) at the upper level with model predictive control (MPC)-based HVAC fleet controllers at the lower level. The proposed approach is tested on nearly 2000 homes with a three-phase distribution network in an intraday market setting, where two major applications are explored and analysed.
The City of Reading, located in southeastern Pennsylvania, is the main city in the Greater Reading Area and the county seat of Berks County, with a population of approximately 95,112 as of 2020. Historically a disinvested manufacturing community, it has a poverty rate of around 40%, a housing stock averaging 90 years old, and an owner-occupied housing rate below 40%. In 2019, Reading adopted a resolution to achieve 100% renewable energy by 2050. The city aims to transition residential, small commercial, and small manufacturing sectors to renewable energy for electricity and heating, bypassing natural gas. This C2C Expert Match aimed to improve the energy efficiency and comfort of older rowhomes in Reading, which often rely on home heating oil and lack cooling systems. A representative energy model of a typical rowhome was developed to evaluate retrofit strategies focused on reducing overheating risk, as well as the potential impacts of heat pump installation. Additionally, resources such as case studies and best practices on energy efficiency, thermal resilience, and electrification retrofits were gathered to support the implementation of effective measures in the community.
This paper studies the performance of a model predictive control (MPC) algorithm in a home energy management system (HEMS) as the set of controllable resources varies and under both a constant and a time-of-use (TOU) electricity price structure. The set of controllable resources includes residentially-owned photovoltaic (PV) panels, a home battery system (HBS), an electric vehicle (EV), and a home heating, ventilation, and air conditioning (HVAC) system. The HEMS optimally schedules the set of controllable resources given user preferences such as indoor thermal comfort and electricity cost sensitivity. The home energy management system is built on a chance constrained, MPC-based algorithm, where the chance constraint ensures the indoor thermal comfort is satisfied with a high probability given uncertainty in the outdoor temperature and solar irradiance forecasts. Simulation results for varying sets of controllable resources under two different electricity price structures demonstrate the variation in the HEMS control with respect to HBS operation, electricity cost, and grid power usage.
This report describes cold climate air source heat pump technology. Cold climate air source heat pumps (ccASHPs) are a variation of an existing air conditioning technology - heat pumps - that are designed to heat homes adequately in very cold weather (usually at or below 5 degrees F) and, as a secondary function, cool these homes during warm weather.
The software provides a measure selection technique indicating cost effective retrofit activities that can be applied to a home using a standard Savings to Investment Ratio (SIR). Users must provide an input file describing the characteristics of the home to be evaluated. The software takes the input data provided and calculates energy savings and cost savings predicted for a standard set of measures given the input parameters. The Weatherization Assistant computes estimates of pre-retrofit whole building space heating and cooling energy consumptions based on the house description data supplied by the user. The consumptions are computed using a monthly heating and cooling variable base degree-day method by algorithms similar to those developed for the CIRA program [LBL, 1982]. The building consumptions are needed in computing the energy savings from measures affecting the efficiencies of the heating and cooling equipment. Weatherization Assistant then computes the energy savings and costs for each individual measure applicable to the building described as if it were the only measure installed in the house. From these energy savings, a discounted dollar savings over the life of each measure is computed. The ratio of this dollar savings to the cost of installing the measure, the "savings-to-investment ratio" (SIR), is used in an initial ranking of the measures' effectiveness. The "interacted" savings and SIR of measures are then determined assuming the measures are added to the house collectively, in order of their ranking, e.g., the second ranked measure is installed in the house initially described by the user after having been modified by the first ranked measure. If this second-ranked measure's updated SIR is greater than a user-defined limit, the measure is left implemented, else it is removed so that the next measure's effectiveness is not dependent on it. The choice between two mutually exclusive measures (such as different levels of insulation) is made on the basis of their "net present value" (NPV), the difference of life-time savings and installation cost, rather than their SIR. This has been shown to be the more correct criterion on which to base the selection between two measures, both of which cannot be installed. The audit computes and reports to the user the energy savings, discounted dollar savings, installation cost, and SIR for each measure considered cost-effective. For those with SIR greater than the user-designated cutoff, a materials list gives the material name, type, and quantity required for installation of the measure. Weatherization Assistant permits entry of pre-retrofit billing data for gas or electrically heated homes or homes with electric air-conditioning. The user may then make the decision to have the savings of the measures adjusted to reflect the difference in billed consumption and that predicted by the program.
The adoption of high-performance triple-pane windows that significantly reduce heat transfer has been slow, in part because they are thicker, heavier, and more costly than double-pane windows. One path to increase adoption of triple-pane windows is to replace the conventional double-glazing insulated glass unit (IGU) with a modified triple-glazing design that uses a very thin central pane of glass. This thinner triple-pane IGU can then be “dropped in” to the double-pane IGU pocket without requiring major modifications to frame design. The Department of Energy sponsored laboratory and field testing of thin triple-pane windows by Pacific Northwest National Laboratory. This article presents findings from both the Lab Homes study and subsequent field demonstrations carried out over a 3-year period (2020–2023). The laboratory and field studies demonstrated the manufacturing and distribution feasibility of thin triple-pane windows, successfully installed at multiple sites, using double-pane frames from four different manufacturers and thin triple-pane IGUs from two different manufacturers. Compared to a home with double-pane, clear-glass windows, testing demonstrated average whole-home heating energy savings of 12% and cooling energy savings of 27% for thin triple-pane windows. Improvements in comfort, sound insulation, and condensation potential were noted in both laboratory and field studies.
A smart thermostat is an internet-connected device that controls home heating, ventilation, and air-conditioning (HVAC) equipment and can automatically adjust temperature set points to optimize performance and achieve energy savings. Smart thermostat features often include two way communication, occupancy detection (such as geofencing and occupancy sensors), schedule learning, and seasonal optimization algorithms. Smart thermostats can control most conventional HVAC systems, including central air conditioners, heat pumps, and forced air furnaces. Several types of residential utility programs offer smart thermostats as replacements measures. Working with smart thermostat vendors, utilities can offer separate optimization programs to produce energy savings beyond those achieved by installing a smart thermostat. From an evaluation perspective, smart thermostat programs have several noteworthy features. First, the energy savings from a smart thermostat may change over the life of the device. As a smart thermostat is connected to the internet, original equipment manufacturers can update the thermostat software to improve the thermostat's energy efficiency. Likewise, users can adjust the thermostat settings and schedules over time in response to changes in weather, thermal comfort, energy prices, or preferences for energy efficiency. Additionally, many thermostat manufacturers offer seasonal optimization programs that recommend changes or make minor, automated adjustments to the thermostat settings to improve energy efficiency. These opt-in programs are now standard offerings for many smart thermostat manufacturers and provided at no additional cost to users. The potential for software updates and continuous optimization and the evolving nature of user interactions mean future energy savings may differ from first-year savings and the energy savings of smart thermostats may need to be evaluated more than once. Second, smart thermostats often have small unit energy savings relative to a home's total energy consumption, especially in comparison to whole- home retrofit programs. This can make it difficult to detect the smart thermostat savings in billing or advanced metering infrastructure (AMI) meter consumption data. For example, as cooling loads in many regions average about 20% of annual electricity consumption, smart thermostat savings of 10% of cooling energy use would equate to a 2% reduction in home electricity consumption. Evaluators should use regression analysis of whole-home billing consumption or advanced metering infrastructure (AMI) meter consumption data to evaluate smart thermostat savings because, as explained at greater length below , these data are usually available to evaluators and regression can control for the impacts of weather and other potentially confounding factors on a home's energy consumption. Finally, as with other energy efficiency programs, participation in smart thermostat programs is self-selective. As discussed at greater length below , smart thermostat participants tend to be, among other things, younger, higher-income, and more likely to adopt electric vehicles (EVs) and internet connected devices than nonparticipants. These differences are often unobservable to the evaluator and correlated with a home's energy consumption, creating the potential for bias in estimating savings. Due to the small unit savings of thermostats, errors and biases from self-selection that may not be very consequential when evaluating a whole- home retrofits (e.g., ±2% of home electricity consumption) can have a major impact when evaluating the savings and cost-effectiveness of smart thermostat programs. A percentage point change in the estimated savings could affect the cost-effectiveness of a program. This means it is important for evaluators to assess and to minimize the potential for error from selection bias in estimating smart thermostat program savings. The Uniform Methods Project provides model protocols for determining energy savings and demand reductions that result from specific energy efficiency measures implemented through state and utility programs. In most cases, the measure protocols are based on a particular option identified by the International Performance Verification and Measurement Protocol ; however, this work provides a more detailed approach to implementing that option. Each chapter is written by technical experts in collaboration with their peers, reviewed by industry experts, and subject to public review and comment. The UMP protocols can be used by utilities, program administrators, public utility commissions, evaluators, and other stakeholders for both program planning and evaluation.
The use of wood as a fuel for home heating is a concern from an environmental health and safety perspective as biomass combustion appliances emit high concentrations of particulate matter. Wood burning significantly contributes to wintertime particulate matter concentrations in many states in the northern United States. Of particular concern are outdoor wood-fired hydronic heaters. These devices are concerning as they tend to have very large combustion chambers and typical use patterns can result in long periods of low output, which result in an increased particulate matter emission rate relative to high heat output operating conditions. In this study, the performance of two hydronic heaters operating under different combustion conditions, including four different heat output categories approximately corresponding to categories I–IV denoted in Environmental Protection Agency Method 28 Outdoor Wood-fired Hydronic Heaters, and during start-up and reloading events were investigated. Measurements of flue gas particulate number concentration and size for particles with aerodynamic diameters between 0.006 and 10 µm were made using a dilution sampling system. The measured particle number concentration in the flue gas was between 0.71 and 420 million particles per cubic centimeter and was dependent on fuel loading and heat output. For each hydronic heater tested, the highest average particle concentration was found at the beginning of each test during the cold-start condition. Additionally, the majority of the particles had aerodynamic diameters less than 0.100 µm (particles of this size made up between 64% and 97% of all particles) and less than 1% of all particles had aerodynamic diameters greater than 1 µm for all phases. For particles in the accumulation mode, between 0.100 and 1 µm, the mean particle diameter was dependent on fuel loading and heat output.