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DOE OSTI2022

Updated U.S. Low-Temperature Heating and Cooling Demand by County and Sector

This dataset includes U.S. low-temperature heating and cooling demand at the county level in major end-use sectors: residential, commercial, manufacturing, agricultural, and data centers. Census division-level end-use energy consumption, expenditure, and commissioned power database were dis-aggregated to the county level. The county-level database was incorporated with climate zone, numbers of housing units and farms, farm size, and coefficient of performance (COP) for heating and cooling demand analysis. This dataset also includes a paper containing a full explanation of the methodologies used and maps. Residential data were updated from the latest Residential Energy Consumption Survey (RECS) dataset (2015) using 2020 census data. Commercial data were baselined off the latest Commercial Building Energy Consumption Survey (CBECS) dataset (2012). Manufacturing data were baselined off the latest Manufacturing Energy Consumption Survey (MECS) dataset (2021).

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

DOE Deep Energy Retrofit Cost Survey

A survey was conducted by the Lawrence Berkeley National Laboratory on deep energy retrofit (DER) market drivers, opportunities, and challenges. The survey was part a research study sponsored by the U.S. Department of Energy to gather information on the costs of DER from home performance contractors and stakeholders. Cost data was gathered from DER projects that use a comprehensive, whole-home approach to drastically reduce energy use and improve performance. DER projects often aim at reducing energy use by 50% or more. In addition, these projects can improve home comfort and potentially benefiting occupant health. Yet, market adoption of DER has been limited. Major limiting factors include complex projects, high costs, perceived risks, extensive disruption, and unfamiliar work scopes to some contractors. In order to better understand what motivates and deters DER projects in today’s market, a survey was conducted to gather this information, and to learn about promising approaches and technologies from the industry perspective. Past surveys on homeowners and home energy performance professionals have studied the motivations and barriers of energy efficiency retrofits. Two surveys of home energy performance professionals were conducted in recent years. The Resources for the Future (RFF) Home Energy Audit and Retrofit Survey was conducted in 2011 by recruiting energy auditors and retrofit installers through members of Efficiency First and Building Performance Institute (BPI) accredited contractors. The survey asked about the business and services that respondents provide, how often homeowners follow their recommendations to retrofit their homes, and the respondents’ opinion on barriers faced by the industry. The survey found that not enough homeowners know about energy audits, but more importantly, it is the high cost of retrofits compared to low energy prices that is responsible for few energy audits and retrofits being completed. The RESNET Deep Retrofit Industry Stakeholder Survey was conducted shortly after launching of the EnergySmart Home Performance Team program. The EnergySmart Team program involves a formal agreement among allied contractors who are engaged in high performance retrofits. Using this allied team approach, teams can pool their expertise and provide each other with customer referrals. The survey asked EnergySmart Team members and outside stakeholders on questions about market and technical barriers in performing home energy retrofits. Survey respondents identified lack of consumer awareness and lack of affordable financing for consumers as the leading market barriers to home energy retrofits. In their written comments, many survey respondents also echoed that the high costs of retrofit compared to low energy prices is a market barrier. Respondents found “certain housing characteristics that prevent effective retrofit” and “energy analysis software inaccuracy or limitations” are the two leading technical barriers. Their choices for technical barriers were reflective of the energy rater/auditor role played by the majority (78%) of the survey respondents. In comparison to past surveys, this work aimed to gather inputs from a broader segment of the home performance industry to identify the opportunities and barriers faced by DERs from all perspectives. The survey asks for project costs to help breakdown the high costs of DERs. This survey is also motivated by a need to better understand the role of DERs in reducing energy use by the residential sectors and meeting climate goals. The survey is designed towards obtaining more substantive inputs from survey respondents by encouraging written comments, rather than setting the goal to reach a large number of respondents. We took this approach because DER is currently still a niche market, so it is more valuable to gather in-depth inputs from individuals who are performing this work rather than getting to the masses.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Implementation Strategy - Efficiency Standards and Labeling Programs in Uganda

In 2016, the development of an Energy Efficiency Roadmap (USAID, 2017) undertaken by Agency for International Development (USAID) showed that an energy-saving potential of 310 MW by 2030 was possible at a cost lower than the current supply of electricity. However, the energy efficiency potential is spread out across many technologies and requires the establishment of enabling policies to stimulate efficient use of energy. Chief among these is the establishment of energy- efficiency standards and labeling (EESL) for electric equipment as indicated by Uganda national energy policy legislation (MEMD, 2002). This report first includes an assessment of energy consumption in the residential sector to identify priority products of focus for the EESL program followed by an assessment of the legal and administrative capacity needs of Ugandan institutions to operate and enforce Uganda’s EESL program.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

South Africa’s Appliance Energy Efficiency Standards and Labeling Program

Electricity consumption in South Africa comes with a hefty environmental cost to the society. For every kilowatt-hour (kWh) produced, 1 kilogram (kg) of carbon dioxide (CO 2 ) is emitted, 1.4 liters of water are used, and 0.37 grams of particulate emissions are released in the atmosphere. These environmental implications result from the large share of electricity produced from coal (91 percent in 2015). While planned new capacity will ramp up renewable energy, the integrated resource plan for the country still projects the share of col to be 64 percent in 2030. Energy savings provide environmental benefits as well as economic benefits. Energy efficiency standards and labeling (S&L) programs are a policy measure proven to save energy. Such programs have been implemented in many countries to remove inefficient technologies and transform markets to more efficient technologies. In this study, we describe the methodology, assumptions and results of a stock turnover modeling tool that estimates the energy savings achievable by South Africa’s S&L program in the residential sector. We show that if regulations are passed in 2020 and effective in 2021 for 10 major end-use adopting international standards best practices, 6 terawatt-hours (TWh) will be saved in 2030 and 9.5 TWh will be saved in 2040, representing a CO 2 mitigation of 3.7 megatonnes (Mt) in 2030 and 5.8 Mt in 2040, which will contribute to the South African government’s international engagement in fighting against climate change through its National Determined Contribution (NDC). Additional environmental benefits include saving of 6.5 billion liters of water in 2030, representing approximately 100 liters per capita in 2030. Air quality will also improve, as 4 kilotons (kt) of particulate emissions will be avoided, as well as 4.3 Mt of sulfur oxides (SOx) and 23 kt of nitrogen oxides (NOx) in 2030.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Large-scale offshore wind farm effects on weather and climate in Puerto Rico (Final Technical Report)

Puerto Rico’s current electricity generation heavily relies on imported fossil fuels. This results in an average cost of electricity higher than the U.S. mainland average in all sectors (residential, commercial, and industrial), despite abundant local offshore wind resources, which have the potential to provide secure, low-cost energy generation and consequent economic prosperity. However, effects on atmospheric and oceanic circulation resulting from large-scale deployments of offshore wind farms have not been previously studied at tropical latitude. This project addressed this knowledge gap through a computational modeling effort designed to capture the coupled dynamics of the atmosphere and the ocean in presence of offshore wind farms. Results indicate that wind farm wakes can alter wind stress, generate Ekman-driven vertical transport, and potentially affect nutrient distribution. While full model coupling remains challenging, progress in parameterization and large-eddy simulations provides a foundation for future research. The project contributes to DOE’s Earth System modeling efforts and supports STEM workforce development.

17 WIND ENERGY↗

NASA NTRS1978

Using coal inside California for nonelectric applications

A review of present energy consumption patterns in the manufacturing, transportation, and residential sectors is presented. The properties of coal that affect its substitution into these market sectors are discussed. Specific needs and concerns of Californians are delineated. Present nonelectric consumptive uses of coal in California are outlined. Current world-wide progress concerning increased industrial use of coal is shown. An overview is given of the options to protect the environment from the direct use of coal, especially from the standpoint of sulfur control; and a time frame for commercialization is projected. Possible desired changes in energy use patterns over the next fifty years are proposed.

Oxley, J. H.↗

DOE OSTI2020

RL-HEMS: Reinforcement Learning Based Home Energy Management System for HVAC Energy Optimization

Heating, ventilation, and air conditioning (HVAC) is one of the major energy consumers in the residential sector. It is important to be able to monitor and control the energy consumed to provide utility services such as load shaping while satisfying the comfort and economic constraints of the homeowner. The objective of this work is to create the optimal schedule for HVAC operation to reduce the cost while satisfying the home-owner and equipment’s constraints using a model-free Reinforcement Learning (RL)-based optimization. The specific goal is to find the right balance between reducing energy cost, consumption, and customer comfort level. Our research effort addresses this optimization problem using multiple components: the development of initial learning test-bed and implementation of RL techniques on a real home. This will enable the rapid evaluation of the RL techniques and provide an early baseline to train before implementation on site. The RL algorithm is designed to learn the energy use patterns and generate the optimized schedule for HVAC within an acceptable time-interval to satisfy the homeowner’s comfort and minimize the energy usage. Our preliminary results are promising and we have observed a 17% reduction in the total cost and a 15% reduction in the power utilization using our RL-based HVAC model—RL-HEMS.

Kotevska, Olivera↗

DOE OSTI2020

Deciphering Degradation: Machine Learning on Real-World Performance Data

The solar investment community is in need of up-to-date and data-derived system degradation rates to use in financial models that calculate the risk and expectation of energy revenue. To date, financial models choose degradation rates from past studies that are limited and may not be representative of solar projects in development today. As the solar industry expands in all sectors (residential, commercial, and utility), there is a growing amount of energy generation data available to analyze. With the help of the open source degradation analysis code (RdTools) it is now possible to derive degradation on an ongoing basis and continuously provide up-to-date durability statistics to the investment community. Ongoing and accurate statistics of fielded photovoltaic systems allows financial stakeholders to constrain energy revenue projections, lower financial risk, and increase the bankability of solar. This presentation will provide a mid-term progress update on a 2 year SETO-funded degradation project that involves applying RdTools analysis on kWh Analytics’ industry database. With results from the RdTools analysis in hand, machine learning methods are employed to quantify how much variance of system performance degradation can be explained by predictor variables such as environmental factors, equipment bill of materials characteristics, and system design information. The goal of this presentation is to promote the usage of RdTools on an ongoing to data owners and to solicit feedback from researchers and stakeholders on how to maximize impact of the SETO-funded kWh Analytics degradation project.

14 SOLAR ENERGY↗

DOE OSTI2020

Building the Efficiency Workforce: Preprint

Demand for high-performance homes and buildings is growing due to their marketability, environmental benefits, and increasing affordability. Growth for energy efficient technologies and building upgrades has driven expansion across many traditional industries including construction trades (which added almost 21,000 jobs) and professional services (which added 35,000 employees) in 2018, according to the 2019 U.S. Energy Employment Report (USEER). As buildings become more automated, digitized and interconnected, the workforce that supports the design, build, operations and maintenance of these buildings must evolve. The U.S. Department of Energy’s Building Technologies Office (BTO) has engaged NREL to provide a framework upon which BTO can develop their next generation workforce development strategy. The strategy will be designed to increase quantity of workers with the skills to adequately design, install, maintain and operate high- performance buildings across all building sectors (residential, commercial, industrial). This paper will summarize past BTO workforce development efforts, identify current skills gaps and hiring challenges, and present anticipated future workforce needs based on new technologies currently being developed by labs and industry. Through a literature review and a series of industry and academic workshops, NREL will present a framework that includes multiple options to best prepare the next generation workforce.

buildings↗

DOE OSTI2024

Proactive and Reactive Thermal Comfort Behaviors

The expansion of renewable electricity generation, growing demands due to electrification, greater prevalence of working from home, and increasing frequency and severity of extreme weather events, will place new demands on the electric supply and distribution grid. Broader adoption of demand response programs (DRPs) for the residential sector may help meet these challenges; however, experience shows that occupant overrides in DRPs compromises their effectiveness. There is a lack of formal understanding of how discomfort, routines, and other motivations affect DRP overrides and other related human building interactions (HBI). This paper reports preliminary findings from a study of 20 households in Colorado and Massachusetts, US over three months. Participants responded to ecological momentary assessments (EMA) triggered by thermostat interactions and at random times throughout the day. EMAs included Likert-scale questions of thermal preference, preference intensity, and changes to 7 different activity types that could affect thermal comfort, and an opened ended question about motivations of such actions. Twelve tags were developed to categorize motivation responses and analyzed statistically to identify associations between motivations, preferences, and HBI actions. Reactions to changes in the thermal environment were the most frequently observed motivation (118 of 220 responses). On the other hand, almost half (47%) responses were at least partially motivated by non-thermal factors, suggesting limited utility for occupant behavior models founded solely on thermal comfort. Changes in activity level and clothing were less likely to be reported when EMAs were triggered by thermostat interactions, while fan interactions were more likely. Windows, shades, and portable heater interactions had no significant dependence on how the EMA was triggered. These results suggest that better understanding of motivations for HBI may improve effectiveness of demand response programs.

Pathak, Maharshi↗

DOE OSTI2024

Geospatial characterization of low-temperature heating and cooling demand in residential, commercial, manufacturing, agricultural, and data center sectors for potential geothermal applications in the United States

Thermal demand for heating and cooling has been predominantly supplied by fossil fuel combustion in the United States, although low-carbon alternatives are extensively available including geothermal, solar thermal, and waste heat. Here, this study analyzed end-use energy consumption, fuel expenditure, and data center commissioned power data to geospatially characterize the U.S. low-temperature heating and cooling demand at the county level in residential, commercial, manufacturing, agricultural, and data center sectors and understand potential opportunities for geothermal applications. In the analysis, the regional-scale energy consumption data was incorporated with system efficiencies to address actual demand and was then disaggregated with weighting factors to the county level. The results indicated that total low-temperature heating and cooling demand is 16.7 EJ, combining heating demand of 10.8 EJ and cooling demand of 5.9 EJ. Overall, 59.9 % (10 EJ) of the low-temperature heating and cooling demand occurred in the residential sector. The heating and cooling demand visualized in maps represented that the geospatial distribution of heating and cooling demand in the residential and commercial sectors is governed by the number of housing units and climate zone designations, while heating and cooling demand in the manufacturing, agricultural, and data center sectors is dependent on the number and location of facilities. The results also demonstrated that geothermal heat pumps are broadly used in the residential and commercial sectors for heating and cooling in the U.S. Midwest, South, and Northeast regions but are limited in the West, implying great decarbonization potential in the future.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Long-term decarbonization impacts on residential energy security across income groups and US states

Abstract The impact of a transition to a net-zero economy on the residential energy sector across diverse income groups in the US remains uncertain. Here, we employ an integrated human-Earth system model, incorporating an expanded set of ten income groups in the residential energy sector, to examine the distributional impacts of long-term decarbonization scenarios on residential energy security at the state level through 2050. We use multiple metrics of energy security, including energy burden, energy satiation gap, and the distribution of energy service across income groups. Our findings show that the net-zero decarbonization scenarios affect residential energy security differently across income groups, with low-to-mid-income groups experiencing larger negative impacts on the dimensions studied here. Comparatively, climate change impact on residential energy security is minor through 2050 based on our model outcomes. Specifically, the net-zero decarbonization scenarios lead to increased energy burden across all income groups and states in 2050, where the lowest (highest) income group in each state shows an average of 0.6 (0.2) percentage point increase in energy burden, relative to the business-as-usual in 2050. The distribution of energy service consumption across income groups is also slightly more skewed under these scenarios. As incomes grow across all deciles in the future, residential energy security generally improves through 2050. Targeted interventions could mitigate the disproportionate impacts that some groups could incur under a transition to a net-zero economy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1975

Input-output analysis of some sector actions

Selected energy conservation actions previously discussed in depth but separately in the areas of the energy industry, the industry sector, the transportation sector, and the residential and commercial sector, were brought together and assessed as a group. Particular emphasis was devoted to identifying secondary or indirect impacts and multiple interactions. Preliminary results obtained from the ECASTAR energy input-output model suggest that the impacts of energy conservation actions can be grossly misrepresented if secondary impacts are not included in the assessment. A methodology which stresses the importance of secondary and multiple interactions permeates the underlying philosophy of this discussion.

Source record↗

DOE OSTI2024

Cost-Benefit Analysis For Indonesia Building Sector: Whole-Building Cooling Solutions

The Net Zero World (NZW) Initiative Collaborative Work Program with the Government of Indonesia (GoI) includes technical assistance and investment mobilization facilitation to accelerate deployment of energy efficiency technologies and solutions for the building sector. A February 2023 U.S.–Indonesia Joint Workshop on Decarbonizing the Building Sector yielded a NZW Indonesia Building Decarbonization Working Group (NZW IBDWG) with four sub-working groups (SWG): SWG-A National Center, SWG-B Capacity Building, SWG-C Investment and Financing, and SWG-D Pilot Projects. Technical analysis of whole-building cooling solutions for tropical climates of Indonesia was conducted by SWG-A to quantify energy savings, carbon dioxide reductions, and comfort improvements offered by 12 passive or low-energy cooling strategies: ceiling fans with and without thermostat setbacks; cool roofs; cool walls; exterior awnings; exterior shades; interior shades; insulated roofs; insulated walls; low-e windows; solar window films; and natural ventilation. Leveraging the results from SWG-A, cost-benefit analysis (CBA) was conducted by SWG-C to assess the consumer and national costs and impacts associated with these 12 cooling solutions. The evaluation involved estimating life-cycle costs (LCC), payback period (PBP), net present values (NPV), annual electricity burden change for low-income households, and reduced national annual power-sector generation demand by 2030, 2040, 2050, and 2060. This evaluation can help guide Indonesia’s Just Energy Transition Partnership (JETP) investments in policies and programs to advance research, development, deployment, and commercial adoption (RDDCA) of efficient residential building sector cooling technologies and solutions in Indonesia. Four key energy conservation measures (ECM) have been identified to reduce air-conditioning (AC) energy demand in single-family housing in Indonesia: ceiling fan with temperature setback (to 28.1 °Celcius from 25 °C); insulated walls; insulated roof; and cool roof. This study found that low-income households with AC installations in Indonesia currently face a high energy cost burden of approximately 10%. However, by implementing a ceiling fan with temperature setback, this burden could decrease to 2.5% today and further reduce to 1.3% by the year 2060. The PBP for a ceiling fan with temperature setback is one year, indicating one of the lowest LCC and best NPV. In the planned upcoming phase of CBA, a series of building cooling improvement scenarios can be further defined, incorporating more than one ECM in combination with socio-economic factors evaluated in the initial CBA phase. Additionally, the analysis of ECM effects in multifamily housing can be expanded. This broader national analysis aims to encompass a holistic and comprehensive system-level perspective, including factors such as avoided power sector infrastructure investments, domestic job creation, domestic manufacturing job creation, and gross domestic product (GDP) growth.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Geospatial Characterization of Low-Temperature Heating and Cooling Demand in the United States: Preprint

Geothermal resources at temperatures below 150 degrees C have great potential as energy sources for various direct-use applications including heating and cooling in residential and commercial buildings. This study geospatially quantifies U.S. heating and cooling demand in residential, commercial, and manufacturing sectors; heating demand in the agricultural sector; and cooling demand in data centers at the county level through end-use energy consumption, expenditure, and commissioned power analyses. Heating and cooling demand in the residential sector was estimated using energy consumption data obtained from the U.S. Energy Information Administration accounting for different U.S. climate zones. For commercial sector analysis, the end-use major fuel energy intensity at the census division level was disaggregated to the county level with respect to principal building activities. Heating and cooling demand analysis for the manufacturing sector was based on end-use energy consumption for direct-use total process categorized by the North America Industry Classification System. Fuel expenditures in the U.S. Department of Agriculture Farm Production Expenditures were examined for heating demand analysis in the agricultural sector, particularly for the greenhouse, nursery, and floriculture production category. Lastly, commissioned power for data centers in the United States were explored for cooling demand analysis. Results indicated a significant fraction of U.S. primary energy consumption is used for low-temperature heating and cooling applications. Heating and cooling demand in residential and commercial sectors is significantly affected by the number of housing units and climate zone designations, while heating and cooling demand in manufacturing and agricultural sectors and data centers are mainly dependent on the number of facilities and their locations. Maps were generated visualizing where heating and cooling demand is high and, overlain with geothermal resource maps, can indicate locations where geothermal energy can supply this heating and cooling demand.

cooling demand↗

DOE OSTI2023

Geospatial Characterization of Low-Temperature Heating and Cooling Demand in the United States

cooling demand↗

DOE OSTI2022

Implications of different income distributions for future residential energy demand in the U.S.

Abstract Future income distribution will affect energy demand and its interactions with various societal priorities. Most future model simulations assume a single average consumer and thus miss this important demand determinant. We quantify long-term implications of alternative future income distributions for state-level residential energy demand, investment, greenhouse gas, and pollutant emission patterns in the United States (U.S.) by incorporating income quintiles into the residential energy sector of the Global Change Analysis Model with 50-state disaggregation. We find that if the income distribution within each U.S. state becomes more egalitarian than present, what means that the difference on income between the richest and poorest decreases over time, residential energy demand could be 10% (4%–14% across states) higher in 2100. This increase of residential energy demand will directly reduce energy poverty, with a very modest increment on economywide CO 2 emissions (1%–2%). On the other hand, if U.S. states transition to a less equitable income distribution than present, with the difference between richest and poorest increasing over time, residential energy demand could be 19% (12%–26% across states) lower. While this study focuses on a single sector, we conclude that to improve understanding of synergies and tradeoffs across multiple societal goals such as energy access, emissions, and investments, future model simulations should explicitly consider subregional income distribution impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Stochastic simulation of occupant-driven energy use in a bottom-up residential building stock model

The residential buildings sector is one of the largest electricity consumers worldwide and contributes disproportionally to peak electricity demand in many regions. Strongly driven by occupant activities, household energy consumption is stochastic and heterogeneous in nature. However, most residential energy models applied by industry use homogeneous, deterministic activity schedules, which work well for predictions of annual energy consumption, but can result in unrealistic hourly or sub-hourly electric load profiles, with exaggerated or muted peaks. The increasing proportion of variable renewable energy generators means that representing the heterogeneity and stochasticity of occupant behavior is now crucial for reliable planning at both bulk-power and distribution-system scales. This work presents a novel and open-source occupancy simulation approach that can simulate a diverse set of individual occupant and household event schedules for all major electricity, fuel, and hot water end uses. To accomplish this, we evaluated three alternative occupant activity simulation approaches before selecting a hybrid combining time-inhomogeneous Markov chains and probability-sampling of event durations and magnitudes. Further, we integrated the stochastic occupancy simulation with an open-source bottom-up physics-simulation building stock model and published a set of 550,000 diverse household end-use activity schedules representing a national housing stock. The simulator was verified against time-use survey data, and simulation results were validated against measured end-use electricity data for accuracy and reliability. While we use data for the United States, our application demonstrates how similar approaches could be applied using the time-use survey data collected in many countries around the world.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗