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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Energy Efficiency and Conservation Block Grant (EECBG) - Better Buildings Neighborhood Program at Greater Cincinnati Energy Alliance: Home Performance with Energy Star® and Better Buildings Performance

The Greater Cincinnati Energy Alliance (Energy Alliance) is a nonprofit economic development agency dedicated to helping Greater Cincinnati and Northern Kentucky communities reduce energy consumption. The Energy Alliance has launched programs to educate homeowners, commercial property owners, and nonprofit organizations about energy efficiency opportunities they can use to drive energy use reductions and financial savings, while extending significant focus to creating/retaining jobs through these programs. The mission of the Energy Alliance is based on the premise that investment in energy efficiency can lead to transformative economic development in a region. With support from seven municipalities, the Energy Alliance began operation in early 2010 and has been among the fastest growing nonprofit organizations in the Greater Cincinnati/Northern Kentucky area. The Energy Alliance offers two programs endorsed by the Department of Energy: the Home Performance with ENERGY STAR® Program for homeowners and the Better Buildings Performance Program for commercial entities. Both programs couple expert guidance, project management, and education in energy efficiency best practices with incentives and innovative energy efficiency financing to help building owners effectively invest in the energy efficiency, comfort, health, longevity, and environmental impact of their residential or commercial buildings. The Energy Alliance has raised over $23 million of public and private capital to build a robust market for energy efficiency investment. Of the $23 million, $17 million was a direct grant from the Department of Energy Better Buildings Neighborhood Program (BBNP). The organization’s investments in energy efficiency projects in the residential and commercial sector have led to well over $50 million in direct economic activity and created over 375,000 hours of labor created or retained. In addition, over 250 workers have been trained through the Building Performance Training Center, a program that was developed and funded by the Energy Alliance and housed at Cincinnati State Technical and Community College. Nearly 100 residential and commercial contractors currently participate in the Energy Alliance’s two major programs, which have together served over 2,800 residential and 100 commercial customers. Additionally, the Energy Alliance established loan programs for homeowners, nonprofits and commercial businesses. The GC-HELP program was established to provide up to ten year low interest, unsecured loans to homeowners to cover the energy efficiency products they purchased through the Energy Alliance approved contractor base. To date the Energy Alliance has financed over $1 million in energy efficiency loans for homeowners, without any loans written off. The nonprofit business community is offered five year, fixed-interest rate loans through the Building Communities Loan Fund of $250,000. Additionally, the Energy Alliance has developed GC-PACE, a commercial financing tool that enables buildings owners to finance their energy upgrades through voluntary property assessments deploying low-interest extended-term capital from the bond market. The Energy Alliance and its partners are actively evaluating additional market-based financing solutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Structural Code Considerations for Solar Rooftop Installations

Residential rooftop solar panel installations are limited in part by the high cost of structural related code requirements for field installation. Permitting solar installations is difficult because there is a belief among residential permitting authorities that typical residential rooftops may be structurally inadequate to support the additional load associated with a photovoltaic (PV) solar installation. Typical engineering methods utilized to calculate stresses on a roof structure involve simplifying assumptions that render a complex non-linear structure to a basic determinate beam. This method of analysis neglects the composite action of the entire roof structure, yielding a conservative analysis based on a rafter or top chord of a truss. Consequently, the analysis can result in an overly conservative structural analysis. A literature review was conducted to gain a better understanding of the conservative nature of the regulations and codes governing residential construction and the associated structural system calculations.

Dwyer, Stephen F.↗
DOE OSTI2014

Calculating Impacts of Energy Standards on Energy Demand in U.S. Buildings under Uncertainty with an Integrated Assessment Model: Technical Background Data

This report presents data and assumptions employed in an application of PNNL’s Global Change Assessment Model with a newly-developed Monte Carlo analysis capability. The model is used to analyze the impacts of more aggressive U.S. residential and commercial building-energy codes and equipment standards on energy consumption and energy service costs at the state level, explicitly recognizing uncertainty in technology effectiveness and cost, socioeconomics, presence or absence of carbon prices, and climate impacts on energy demand. The report provides a summary of how residential and commercial buildings are modeled, together with assumptions made for the distributions of state–level population, Gross Domestic Product (GDP) per worker, efficiency and cost of residential and commercial energy equipment by end use, and efficiency and cost of residential and commercial building shells. The cost and performance of equipment and of building shells are reported separately for current building and equipment efficiency standards and for more aggressive standards. The report also details assumptions concerning future improvements brought about by projected trends in technology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Fayette County Better Buildings Initiative

The Fayette County Better Buildings Initiative represented a comprehensive and collaborative approach to promoting and implementing energy efficiency improvements. The initiative was designed to focus on implementing energy efficiency improvements in residential units, while simultaneously supporting general marketing of the benefits of implementing energy efficiency measures. The ultimate goal of Fayette County’s Better Buildings Initiative was to implement a total of 1,067 residential energy efficiency retrofits with a minimum 15% estimated energy efficiency savings per unit. Program partners included: United States Department of Energy, Allegheny Power, and Private Industry Council of Westmoreland-Fayette, Fayette County Redevelopment Authority, and various local partners. The program was open to any Fayette County residents who own their home and meet the prequalifying conditions. The level of assistance offered depended upon household income and commitment to undergo a BPI – Certified Audit and implement energy efficiency measures, which aimed to result in at least a 15% reduction in energy usage. The initiative was designed to focus on implementing energy efficiency improvements in residential units, while simultaneously supporting general marketing of the benefits of implementing energy efficiency measures. Additionally, the program had components that involved recruitment and training for employment of persons in the energy sector (green jobs), as well as marketing and implementation of a commercial or community facilities component. The residential component of Fayette County’s Better Buildings Initiative involved a comprehensive approach, providing assistance to low- moderate- and market-rate homeowners. The initiative will also coordinate activities with local utility providers to further incentivize energy efficiency improvements among qualifying homeowners. The commercial component of Fayette County’s Better Building Initiative involved grants and loans to assist up to $15,000 projects per commercial structure with a mixture of a grant and financing at 0% for up to three – (3) years. The maximum award can be a $5,000 grant and a $10,000 loan. For projects less than $15,000, the award will have a ratio of 1/3 grant and 2/3 loan.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Benchmarking Non-Hardware Balance-of-System (Soft) Costs for U.S. Photovoltaic Systems Using a Bottom-Up Approach and Installer Survey

This report presents results from the first U.S. Department of Energy (DOE) sponsored, bottom-up data-collection and analysis of non-hardware balance-of-system costs—often referred to as “business process” or “soft” costs—for residential and commercial photovoltaic (PV) systems. Annual expenditure and labor-hour-productivity data are analyzed to benchmark 2010 soft costs related to the DOE priority areas of (1) customer acquisition; (2) permitting, inspection, and interconnection; (3) installation labor; and (4) installer labor for arranging third-party financing. Annual expenditure and labor-hour data were collected from 87 PV installers. After eliminating outliers, the survey sample consists of 75 installers, representing approximately 13% of all residential PV installations and 4% of all commercial installations added in 2010. Including assumed permitting fees, in 2010 the average soft costs benchmarked in this analysis total $1.50/W for residential systems (ranging from $0.66/W to $1.66/W between the 20th and 80th percentiles). For commercial systems, the median 2010 benchmarked soft costs (including assumed permitting fees) are $0.99/W for systems smaller than 250 kW (ranging from $0.51/W to $1.45/W between the 20th and 80th percentiles) and $0.25/W for systems larger than 250 kW (ranging from $0.17/W to $0.78/W between the 20th and 80th percentiles). Additional soft costs not benchmarked in the present analysis (e.g., installer profit, overhead, financing, and contracting) are significant and would add to these figures. The survey results provide a benchmark for measuring—and helping to accelerate—progress over the next decade toward achieving the DOE SunShot Initiative’s soft-cost-reduction targets. We conclude that the selected non-hardware business processes add considerable cost to U.S. PV systems, constituting 23% of residential PV system price, 17% of small commercial system price, and 5% of large commercial system price (in 2010). These processes present significant opportunities for further cost reductions and labor-productivity gains.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Low-E Retrofit Demonstration and Educational Program

The objective of this project was to demonstrate the capability of low-emissivity (low-E) storm windows / panels and low-E retrofit glazing systems to significantly and cost effectively improve the energy efficiency of both existing residential and commercial buildings. The key outcomes are listed below: RESIDENTIAL CASE STUDIES: (a) A residential case study in two large multifamily apartment buildings in Philadelphia showed a substantial 18-22% reduction in heating energy use and a 9% reduction in cooling energy use by replacing old clear glass storm windows with modern low-E storm windows. Furthermore, the new low-E storm windows reduced the overall apartment air leakage by an average of 10%. (b) Air leakage testing on interior low-E panels installed in a New York City multifamily building over windows with and without AC units showed that the effective leakage area of the windows was reduced by 77-95%. (c) To study the use of low-E storm windows in a warmer mixed climate with a balance of both heating and cooling, 10 older homes near Atlanta with single pane windows were tested with three types of exterior storm windows: clear glass, low-E glass with high solar heat gain, and low-E glass with lower solar heat gain. The storm windows significantly reduced the overall home air leakage by an average of 17%, or 3.7 ACH50. Considerably high variability in the data made it difficult to draw strong conclusions about the overall energy usage, but for heating periods, the low-E storm windows showed approximately 15% heating energy savings, whereas clear storm windows were neutral in performance. For cooling periods, the low-E storm windows showed a wide range of performance from 2% to over 30% cooling energy savings. Overall, the study showed the potential for significantly more energy savings from using low-E glass versus no storm window or clear glass storm windows in warmer mixed climates, but it is difficult to conclusively say whether one type of low-E performed better than the other. COMMERCIAL CASE STUDIES: (a) A 12-story office building in Philadelphia was retrofitted by adding a double-pane low-E insulating glass unit to the existing single pane windows, to create a triple glazed low-E system. A detailed side-by-side comparison in two pairs of perimeter offices facing north and east showed a 39-60% reduction in heating energy use, a 9-36% reduction in cooling energy use, and a 10% reduction in peak electrical cooling demand. An analysis of utility bills estimated the whole building heating and cooling energy use was reduced by over 25%. Additionally, the retrofit window temperatures were commonly 20 degrees warmer on winter days, and 10-20 degrees cooler on summer days, leading to increased occupant comfort. (b) Two large 4-story office buildings in New Jersey were retrofitted with a similar system, but using two low-E coatings in the retrofit system. The energy savings are being monitored by a separate GPIC project; this work quantified the changes in glass surface temperatures, thermal comfort, and potential glass thermal stress. The low-E retrofit panels greatly reduced daily variations in the interior window surface temperatures, lowering the maximum temperature and raising the minimum temperature by over 20F compared to the original single pane windows with window film. The number of hours of potential thermal discomfort, as measured by deviation between mean radiant temperature and ambient air temperature by more than 3F, were reduced by 93 percent on the south orientation and over two-thirds on the west orientation. Overall, the low-E retrofit led to substantially improved occupant comfort with less periods of both overheating and feeling cold. (c) No significant thermal stress was observed in the New Jersey office building test window when using the low-E retrofit system over a variety of weather conditions. The surface temperature difference only exceeded 10F (500 psi thermal stress) for less than 1.5% of the monitored time, and in all cases, the maximum surface temperature difference never exceeded 35F (1,750 psi thermal stress). LOW-E STORM WINDOW OUTREACH AND EDUCATION PROGRAM: (a) The project team assisted the State of Pennsylvania in adding low-E storm windows as a cost effective weatherization measure on its priority list for the state weatherization assistance program. (b) No technical barriers that could hinder widespread application were identified in the case studies. However, educational barriers have been identified, in that weatherization personnel commonly misunderstand how the application of low-E storm windows is very different than much more expensive full window replacement. (c) A package of educational materials was developed to help communicate the benefits of low-E storm windows and retrofits as a cost effective tool for weatherization personnel. (d) Using detailed thermal simulations, more accurate U-factor and solar heat gain coefficient (SHGC) values were determined for low-E storm windows installed over different primary windows. IN SUMMARY, this work confirmed the potential for low-E storm windows, panels, and retrofit systems to provide significant energy savings, reductions in air leakage, and improvements in thermal comfort in both residential and commercial existing buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Guidelines for Posting Soil Contamination Areas

All soil guidelines were determined using RESRAD, version 6.1. All offsite guidelines are based on 15 mrem/year. This dose rate is sufficiently low to protect human health and is in accordance with DOE guidance and the proposed EPA 40-CFR-196 regulations for members of the public (never promulgated). For those onsite areas where general employees (non-radiological workers) could have routine access, soil concentrations should be based on a dose rate of 30 mrem/year (approximately one-third of the onsite LANL non-radiological worker dose of 100 mrem/year). In this case, soil concentration guidelines may be obtained by doubling the 15 mrem/year guidelines. Several scenarios were developed to provide maximum flexibility for application of the guidelines. The offsite guidelines were developed using: residential scenarios for both adults and children; a construction worker scenario; a resource user (e.g., a hunter) scenario; a child playing within canyon reaches scenario, a trail using jogger within canyon reaches scenario, and a trail using hiker within canyon reaches scenario. The residential guidelines represent the lowest values from both the adult residential scenario and the child residential scenario.

58 GEOSCIENCES↗
DOE OSTI2016

The Advancement of Cool Roof Standards in China from 2010 to 2015

Since the initiation of the U.S.-China Clean Energy Research Center-Building Energy Efficiency (CERC-BEE) cool roof research collaboration between the Lawrence Berkeley National Laboratory Heat Island Group and Chinese institutions in 2010, new cool surface credits (insulation trade- offs) have been adopted in Chinese building energy efficiency standards, industry standards, and green building standards. JGJ 75-2012: Design Standard for Energy Efficiency of Residential Buildings in Hot Summer and Warm Winter Zone became the first national level standard to provide cool surface credits. GB/T 50378-2014: Assessment Standard for Green Building is the first national level green building standard that offers points for heat island mitigation. JGJ/T 359-2015: Technical Specification for Application of Architectural Reflective Thermal Insulation Coating is the first industry standard that offers cool coating credits for both public and residential buildings in all hot-summer climates (Hot Summer/Cold Winter, Hot Summer/Warm Winter). As of December 2015, eight provinces or municipalities in hot-summer regions have credited cool surfaces credits in their residential and/or public building design standards; five other provinces or municipalities in hot-summer regions recommend, but do not credit, the use of cool surfaces in their building design standards. Cool surfaces could be further advanced in China by including cool roof credits for residential and public building energy efficiency standards in all hot-summer regions; developing a standardized process for natural exposure and aged-property rating of cool roofing products; and adapting the U.S.-developed laboratory aging process for roofing materials to replicate solar reflectance changes induced by natural exposure in China.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

2016 End of the year South Carolina PV soft cost and workforce development

A solar industry survey was given to professional installers who serve the South Carolina market in order to determine trends in costing, work force needs, and business demographics at the end of 2016. It was found that 70% of the respondents serve the residential sector, while only 7% of the total exclusively serves the residential market. The average size of residential installations remain near 9 kW-DC, while the average size of commercial and utility scale installations continue to grow to 378 kW-DC and 14.8 MW-DC, respectively. The total cost of these residential systems has hovered around $3.50/W-DC since the end of 2015, while commercial installations have dropped to $2.45/W-DC and utility scale installations have dropped to $1.49/W-DC. It is expected that the cost of utility scale installations will continue to drop as there are publically reported utility scale installations with contracted PPAs for less than 4¢/kWh. 52-60% of the cost is associated with hardware only depending upon sector.

14 SOLAR ENERGY↗
DOE OSTI2018

The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures: January 2012 - September 2016

This is the complete set of Uniform Methods Project protocols for determining energy efficiency savings for specific measures, all within one report. The report includes the following chapters: Chapter 1: Introduction. Chapter 2: Commercial and Industrial Lighting Evaluation Protocol. Chapter 3: Commercial and Industrial Lighting Controls Evaluation Protocol. Chapter 4: Small Commercial and Residential Unitary and Split System HVAC Cooling Equipment-Efficiency Upgrade Evaluation Protocol. Chapter 5: Residential Furnaces and Boilers Evaluation Protocol. Chapter 6: Residential Lighting Evaluation Protocol. Chapter 7: Refrigerator Recycling Evaluation Protocol. Chapter 8: Whole-Building Retrofit with Consumption Data Analysis Evaluation Protocol. Chapter 9: Metering Cross-Cutting Protocol. Chapter 10: Peak Demand and Time-Differentiated Energy Savings Cross-Cutting Protocol. Chapter 11: Sample Design Cross-Cutting Protocol. Chapter 12: Survey Design and Implementation for Estimating Gross Savings Cross-Cutting Protocol. Chapter 13: Assessing Persistence and Other Evaluation Issues Cross-Cutting Protocol. Chapter 14: Chiller Evaluation Protocol. Chapter 15: Commercial New Construction Evaluation Protocol. Chapter 16: Retrocommissioning Evaluation Protocol. Chapter 17: Residential Behavior Evaluation Protocol. Chapter 18: Variable Frequency Drive Evaluation Protocol. Chapter 19: HVAC Controls (DDC/EMS/BAS) Evaluation Protocol. Chapter 20: Data. Center IT Efficiency Measures Evaluation Protocol. Chapter 21: Estimating Net Savings - Common Practices. Chapter 22: Compressed Air Evaluation Protocol. Chapter 23: Combined Heat and Power Evaluation Protocol. Chapter 24: Strategic Energy Management (SEM) Evaluation Protocol

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Agent-Based Coordination Scheme for PV Integration (ABC4PV)

Renewables and especially photovoltaics (PV) have benefitted significantly from a host of incentives and policies targeted toward enhanced integration and adoption of specific energy technologies. However, with the push to move forward into a subsidy-free market framework, behind-the-meter residential PV applications have generally struggled to retain their value (unlike utility scale and commercial projects) [1]. This project focused on developing control-theoretic solutions aimed at improving the integration and interaction of behind-the-meter residential PV with other distribution system assets (controllable and non-controllable) to enhance the integrated value of residential PV. To this end, a suite of decentralized control methodologies have been developed to enable effective coordination and control of behind-the-meter residential load customers’ PV, battery storage systems (BSS), controllable loads and other similar assets within a distribution feeder. This interaction aims at procuring energy savings and, thus, energy bill savings. The main source of savings is drawn from reducing the effect of demand charge pricing and is realized at the feeder level, assuming community level interaction and management among the aforementioned assets. Optimal control of the assets is implemented with a distributed optimization methodology, leveraging consensus-based algorithms. The results gathered from the optimal control simulations demonstrates that the savings can be duly achieved and the algorithm decision times (to dynamically control asset set points, for example) are fast. As for the overall efficiency of PV+BSS systems, to procure energy savings from curtailment of the demand charge pricing effects, the optimal control is set up so as to minimize the variance of the load for all customers, throughout a feeder and throughout time in a rolling horizon scheduling with model predictive control. The control takes into account inter-temporal electrochemical storage (battery) degradation costs: specifically, we have developed a long-term lifetime model for the BSS that weighs in the effect of the degradation factor in the dispatch formulations, thus, a considerable operating cost that affects energy decision making. The levelized cost of energy (LCOE – redefined for the purpose of quantifying asset integration effectiveness through the customers’ energy cost) is shown to be below the threshold set for the combined PV+BSS topology of $ 0.14/kWh for multiple cases of PV penetration all the way up to 50%, provided that a policy of shared ownership of and savings is in place. Further, the LCOE calculated for the case before the deployment PV+BSS systems is also achievable, i.e. the deployment of PV+BSS, if planned and scheduled optimally. will have no effect on customers’ energy costs. From the control methodology viewpoint, the developed consensus-based algorithms are shown to converge for a wide range of problem cases (spanning normal operating scenarios and contingencies), guaranteeing dispatch solutions under forecasting errors, communication break-downs and cyber-security attacks. The proposed control solutions are scalable and real-time implementable, with dispatch computations and device set-point updates converging in less than 2s in most practical instances of the above events.

14 SOLAR ENERGY↗
DOE OSTI2021

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmark: Q1 2021 [Slides]

Our benchmarking method includes bottom-up accounting for all necessary system and projectdevelopment costs incurred when installing residential, commercial, and utility-scale systems, and it models the Q1 2021 costs for such systems, excluding any previous supply agreements or contracts. In general, we attempt to model the typical installation techniques and business operations from an installed-cost perspective, and our benchmarks are national averages. The residential PV-only benchmark and the commercial rooftop PV-only benchmark average costs by inverter type (string inverters, string inverters with direct current [DC] optimizers, and microinverters), weighted by inverter market share. The residential PV-only benchmark is further averaged across small installer and national integrator business models, weighted by market share. All benchmarks include variations—accounting for the differences in size, equipment, and operational use (particularly for storage)—that are currently available in the marketplace. All benchmarks assume nonunionized construction labor; residential and commercial PV systems predominantly use nonunionized labor, and the type of labor required for utility-scale PV systems depends heavily on the development process. All benchmarks assume the use of monofacial monocrystalline silicon PV modules. Benchmarks using cadmium telluride or bifacial modules could result in significantly different results. The data in this annual benchmark report inform the formulation of and track progress toward the U.S. Department of Energy (DOE) Solar Energy Technologies Office’s Government Performance and Reporting Act cost targets.

14 SOLAR ENERGY↗
DOE OSTI2022

Guide to Determining Climate Zone by County: Building America and IECC 2021 Updates

This report describes the climate zone designations used by the U.S. Department of Energy (DOE) Building America Program. The report aims to help residential building stakeholders identify the appropriate climate zone designation for each county in the United States, including Hawaii and Alaska. Identifying the correct climate zone is important for many activities including residential construction projects, code compliance, energy analysis and modeling, and other analytical activities where climate zones impact the energy and moisture performance of residential buildings. This report supersedes the previous Building America publication: Guide to Determining Climate Regions by County, published in 2010. This report reflects climate designations used by the International Code Council (ICC) in the 2021 versions of the International Energy Conservation Code (IECC), the International Residential Code (IRC), and other codes produced by ICC. The information provided here and associated data should be used for the most up-to-date information regarding climate zone designations in the United States.

2021 IECC↗
DOE OSTI2021

American Homeowner Perceptions and Choices for Energy Efficiency: Summary of Technology Adoption – Census Division Level

In 2020 a nationwide survey of homeowners was conducted to determine what energy efficiency upgrades homeowners had made to their homes and which ones they would make in the near future. The survey also included results on respondent financials about energy efficiency home upgrades/retrofits and perceptions of the value of energy efficiency/who should support improving the energy efficiency of the residential sector. The Department of Energy’s goal for this survey is to inform ongoing work in the residential energy efficiency research portfolio on the human dimensions of residential energy systems transformation. In addition, DOE envisions this work supports efforts by industry, non-profits, and other government partners in informing programming, customer discovery, and policy writ large. This report provides a general summary of the nationwide results as they pertain to the following three issues: (1) how much did respondents indicate spending on energy efficiency-related home upgrades, (2) what upgrades/improvements had they made to their homes, and (3) which upgrades/improvements do they believe have the most significant impact on energy efficiency. The results provided are segmented by census division as specific regions demonstrated unique preferences for energy efficiency and willingness to expend family resources to achieve those goals. As such, the goal of this report is not to analyze the data nor draw cross-cutting conclusions but to serve as a resource for any groups interested in reviewing national trends about residential energy efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States (2023 Edition) [Slides]

Berkeley Lab’s annual Tracking the Sun report describes trends among grid-connected, distributed solar photovoltaic (PV) and paired PV+storage systems in the United States. For the purpose of this report, distributed solar includes residential systems, roof-mounted non-residential systems, and ground-mounted systems up to 5 MW-AC. Ground-mounted systems larger than 5 MW-AC are covered in Berkeley Lab’s companion annual report, Utility-Scale Solar. The latest edition of the report is based on 3.2 million systems installed through year-end 2022, representing more than 80% of systems installed to date. The report describes and discusses key trends related to: -Project characteristics, including system size, module efficiencies, prevalence of paired PV with storage, use of module-level power electronics, third-party ownership, mounting configurations, panel orientation, and non-residential customer segmentation ownership -Median installed-price trends, both nationally and by state -Variability in pricing according to system size, state, installer, equipment type, and other factors, relying on both descriptive and econometric analysis The report also includes a multi-variate regression analysis to estimate the effects of key pricing drivers for residential systems installed in 2022.

14 SOLAR ENERGY↗
DOE OSTI2025

Wind Turbine Sound Setbacks and Supply Curves: Ordinances and Extrapolated Trends, 110 Hub Height, 130 Rotor Diameter

This dataset provides a comprehensive set of wind turbine sound setbacks from every residential structure in the contiguous United States (CONUS). A sound setback is defined as the minimum required distance between a residential structure and a hypothetical turbine installation site to ensure that modeled sound levels received at the residence do not exceed local sound ordinances, which are commonly expressed in A-weighted decibels (dBA). Therefore, sound setbacks are a local spatial assessment combining multiple factors, including the sound pressure curve as a function of the observer location (distance and direction) relative to the turbine, local sound regulations, and the geographical distribution of residential structures. The dataset is organized into multiple scenario-based products, detailed as follows: 1. Existing and extrapolated sound setbacks. An existing scenario characterizes sound setbacks only in states or counties that have implemented sound regulations as of 2022. The extrapolated scenarios extend a constant sound threshold to counties that lack explicit sound regulations, with thresholds ranging from 35 to 60 dBA, in 5-dBA increments reflecting the variation observed in current sound ordinances. 2. Sound setbacks in directional and worst scenarios. The directional scenario accounts for the distance and orientation of residential structures relative to a hypothetical turbine location, utilizing the turbine's sound emissions in that specific direction. In contrast, the worst scenario takes loudest sound level at each distance step from the turbine, irrespective of directional considerations, which aligns with current industry practice. 3. Supply curves for Open and Reference Access scenarios. This dataset includes supply curves generated by the reV model, which integrates each of the above sound setbacks into both Open and Reference siting scenarios. In addition, two Open and Reference baselines scenarios were included which do not consider sound setbacks for comparative analysis. All sound setback data are stored in TIF files, with partial maps of the data provided in PNG format. The values in the sound setback raster range from 0 to 1, representing the fraction of developable land within a 90 meter by 90 meter pixel due to sound ordinances. A value of 0 indicates areas where wind energy development is prohibited, while a value of 1 signifies areas fully permissible. The wind turbine parameters used in the sound modeling are based on the land-based turbine from International Energy Agency (IEA), featuring a rated electrical power of 3.4 MW, a rotor diameter of 130 meters, and a hub height of 110 meters. The atmospheric conditions, including wind speed/direction, turbulence, air temperature, relative humidity, and air pressure, that drive the sound generation are obtained from the WIND Toolkit dataset.

Array↗
DOE OSTI2023

EUI Benchmarks for Net-Zero Energy Buildings in India

In our study we present EUI benchmarks for NZEBs for six building types across residential and non-residential typologies and for India's five climate zones. This approach is similar to the simulation-based benchmarks used by the B3 program in Minnesota, the Cal-Arch methodology in California, and the US Solar Decathlon approach, which combine simulations with actual building data. Of the six building types we explore one in detail with a range of operation scenarios, specifically narrowing down the EUI benchmarks for mixed-mode building operation and for variable temperature set-points as prescribed in the National Building Code of India.The contribution of this work is to provide rigorous end-use level EUI benchmarks for six building types, and to describe a method for simulation-based EUI benchmarks for mixed-mode operation with variable setpoints to highlight the difference between the standard approach used for the five building types and the On-Site Construction Worker Housing which additionally has the mixed-mode variable setpoint approach.On-Site Construction Worker Housings are typically poorly constructed temporary structures, without adequate thermal comfort, It is critical to provide adequate thermal comfort to protect people from the warming effects of climate change, and to discover super efficient and cost-effective ways to do so.The methodology used for the On-Site Construction Worker Housing (CWH) results in an 80% acceptability according to the India Model for Adaptive Comfort in the National Building Code of India. EUIs of all six buildings are 60% lower than the minimum compliance with India's Energy Conservation Building Codes, providing benchmarks for efficiency levels. The end-use level EUI benchmarks are now provided to over 1800 Solar Decathlon India participants so that they can compare the performance of their NZEB designs.In particular, the CWH results provide an insight into the importance of the mixed-mode operation with variable temperature set-points. The results from the simulation study show that for an NZEB target, the EUI with standard thermal comfort model and without mixed operation is 58.26 kWh/m2*year, while that with the variable set-points of the adaptive model with mixed mode operation is 24.23 kWh/m2*year. This is a 58% reduction in EUI. Given that many building types including residential, and non-residential operate in mixed mode, it is important to take this work further to develop mixed-mode operation NZEB benchmarks so that the carbon intensity of these buildings could be lower than the standard thermal comfort model approach.

benchmarking↗
DOE OSTI2020

A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): an application of the Community Emissions Data System (CEDS)

Global anthropogenic emission inventories remain vital for understanding the sources of atmospheric pollution and the associated impacts on the environment, human health, and society. Rapid changes in today's society require that these inventories provide contemporary estimates of multiple atmospheric pollutants with both source sector and fuel type information to understand and effectively mitigate future impacts. To fill this need, we have updated the open-source Community Emissions Data System (CEDS) (Hoesly et al., 2019) to develop a new global emission inventory, CEDSGBD-MAPS. This inventory includes emissions of seven key atmospheric pollutants (NOx; CO; SO2; NH3; non-methane volatile organic compounds, NMVOCs; black carbon, BC; organic carbon, OC) over the time period from 1970–2017 and reports annual country-total emissions as a function of 11 anthropogenic sectors (agriculture; energy generation; industrial processes; on-road and non-road transportation; separate residential, commercial, and other sectors (RCO); waste; solvent use; and international shipping) and four fuel categories (total coal, solid biofuel, the sum of liquid-fuel and natural-gas combustion, and remaining process-level emissions). The CEDSGBD-MAPS inventory additionally includes monthly global gridded (0.5°?×?0.5°) emission fluxes for each compound, sector, and fuel type to facilitate their use in earth system models. CEDSGBD-MAPS utilizes updated activity data, updates to the core CEDS default scaling procedure, and modifications to the final procedures for emissions gridding and aggregation. Relative to the previous CEDS inventory (Hoesly et al., 2018), these updates extend the emission estimates from 2014 to 2017 and improve the overall agreement between CEDS and two widely used global bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the most contemporary global emission estimates to date for these key atmospheric pollutants and is the first to provide global estimates for these species as a function of multiple fuel types and source sectors. Dominant sources of global NOx and SO2 emissions in 2017 include the combustion of oil, gas, and coal in the energy and industry sectors as well as on-road transportation and international shipping for NOx. Dominant sources of global CO emissions in 2017 include on-road transportation and residential biofuel combustion. Dominant global sources of carbonaceous aerosol in 2017 include residential biofuel combustion, on-road transportation (BC only), and emissions from the waste sector. Global emissions of NOx, SO2, CO, BC, and OC all peak in 2012 or earlier, with more recent emission reductions driven by large changes in emissions from China, North America, and Europe. In contrast, global emissions of NH3 and NMVOCs continuously increase between 1970 and 2017, with agriculture as a major source of global NH3 emissions and solvent use, energy, residential, and the on-road transport sectors as major sources of global NMVOCs. Due to similar development methods and underlying datasets, the CEDSGBD-MAPS emissions are expected to have consistent sources of uncertainty as other bottom-up inventories. The CEDSGBD-MAPS source code is publicly available online through GitHub: https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS (last access: 1 December 2020). The CEDSGBD-MAPS emission inventory dataset (both annual country-total and monthly global gridded files) is publicly available under https://doi.org/10.5281/zenodo.3754964 (McDuffie et al., 2020c).

Mcduffie, Erin↗