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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Reduction of Fermi level pinning and recombination at polycrystalline CdTe surfaces by laser irradiation

Laser processing of polycrystalline CdTe is a promising approach that could potentially increase module manufacturing throughput while reducing capital expenditure costs. For these benefits to be realized, the basic effects of laser irradiation on CdTe must be ascertained. In this study, we utilize surface photovoltage spectroscopy (SPS) to investigate the changes to the electronic properties of the surface of polycrystalline CdTe solar cell stacks induced by continuous-wave laser annealing. The experimental data explained within a model consisting of two space charge regions, one at the CdTe/air interface and one at the CdTe/CdS junction, are used to interpret our SPS results. The frequency dependence and phase spectra of the SPS signal are also discussed. To support the SPS findings, low-temperature spectrally-resolved photoluminescence and time-resolved photoluminescence were also measured. The data show that a modest laser treatment of 250 W/cm{sup 2} with a dwell time of 20 s is sufficient to reduce the effects of Fermi level pinning at the surface due to surface defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Reassessing Hybrid Vigor or Hybrid Dysfunction Using Physiological Trade-Offs in an Endangered Salamander System

Fitness of interspecific hybrids can be higher or lower than that of their parental genotypes, with major ramifications for evolution and conservation. A recent study found that hybrid tiger salamanders had higher metabolic rates than their parental forms. Specifically, the ratio of resting metabolic rate to water loss, which was used as a measure of performance, was greater in hybrids. Recent genetic research showed that over half of the experimental subjects in that study were genetically pure California tiger salamanders (Ambystoma californiense) misclassified as hybrids. We reanalyzed the data using the corrected identification of hybrids and parentals. As expected, updating the classification revealed even stronger evidence for differences between hybrids and parentals. Hybrids had higher resting metabolic rates and greater water loss than parentals. The ratio of resting metabolic rate to water loss was also higher in hybrids. However, we suggest that this ratio might not be a positive measure of salamander performance. Higher metabolic rate means higher energy expenditure, and higher water loss suggests increased risk of desiccation. Both are major challenges for terrestrial amphibians, especially salamanders, which are hypothesized to be low-energy, low-water-loss specialists. Under this hypothesis, the ratio of energy expenditure to water loss is a ratio of two costs rather than a ratio of benefit to cost. While our analyses corroborate and strengthen the previous statistical results, we suggest that high resting metabolic rate is better interpreted as hybrid dysfunction, not vigor. Here, both hypotheses are speculative, and specific research on the fitness effects of these physiological differences is needed to resolve this important ecological question.

Ambystoma californiense↗
DOE OSTI2015

SMAC: A soft MAC to reduce control overhead and latency in CDMA-based AMI networks

The utilization of state-of-the-art 3G cellular CDMA technologies in a utility owned AMI network results in a large amount of control traffic relative to data traffic, increases the average packet delay and hence are not an appropriate choice for smart grid distribution applications. Like the CDG, we consider a utility owned cellular like CDMA network for smart grid distribution applications and classify the distribution smart grid data as scheduled data and random data. Also, we propose SMAC protocol, which changes its mode of operation based on the type of the data being collected to reduce the data collection latency and control overhead when compared to 3G cellular CDMA2000 MAC. The reduction in the data collection latency and control overhead aids in increasing the number of smart meters served by a base station within the periodic data collection interval, which further reduces the number of base stations needed by a utility or reduces the bandwidth needed to collect data from all the smart meters. The reduction in the number of base stations and/or the reduction in the data transmission bandwidth reduces the CAPital EXpenditure (CAPEX) and OPerational EXpenditure (OPEX) of the AMI network. Finally, the proposed SMAC protocol is analyzed using markov chain, analytical expressions for average throughput and average packet delay are derived, and simulation results are also provided to verify the analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

ProFAST (Production Financial Analysis Scenario Tool) [SWR-23-88]

The Production Financial Analysis Scenario Tool (ProFAST) provides a quick and convenient in-depth financial analysis for production facilities. The model uses a generally accepted accounting principles analysis framework and provides annual projections of income statements, cash flow statements, and balance sheets. ProFAST allows users to calculate the levelized cost of the produced commodity by providing an expected financial performance, or on the other hand, calculate the financial performance based on an input price. Model inputs generally capital expenditures, operating expenditures, and financing structure. The programmatic approach of ProFAST allows users to easily perform large sensitivity analyses and integrates easily with other python tools.

Kee, Jamie↗
DOE OSTI2024

BioC2G Tool v1

The BioC2G tool provides an interface for running technoeconomic analyses and life-cycle assessments of biofuel and bioproduct production pathways. Models for the pathways are currently built into the tool: limonene, limonane, bisabolene, bisabolane, ethanol, isoprenol, DMCO, and HEFA. Additionally, a "Custom" option is available for analyzing a bioproduction pathway not included among the built-in examples. Users must supply key product properties and process parameters. Three types of model runs are available in the tool: minimum selling price (MSP), water consumption, and greenhouse gas (GHG) emissions. Running the MSP model yields a breakdown of MSP by major process stage of production, along with a a table of estimated capital expenditures (CAPEX) and annual operating expenditures (OPEX). Running the water consumption and GHG models yields a breakdown of water consumed and carbon emissions respectively, per unit of end product. A breakdown of these metrics by major process stage is also provided. Model run results can be viewed in the web interface numerically and graphically, as well as downloaded in CSV format. Detailed documentation on model methodology and assumptions is also available for download.

Huntington, Tyler↗
DOE OSTI2021

Household Transportation Energy Affordability by Region and Socioeconomic Factors

Transportation fuel is an important component of household budgets, as 3.3% of total household expenditures are for vehicle fuel nationwide and over 50% of annual household expenditures on energy are for transportation. These average values vary geographically, and higher energy cost burdens are faced by households with lower incomes. Defining transportation energy affordability burden as the percentage of annual household income spent on vehicle fuel, this study aims to quantify affordability as a function of household characteristics and geography. Here, through analysis at the census tract level, this study (i) projects annual household vehicle miles traveled (VMT) based on demographic factors using machine-learning techniques, (ii) estimates local differences in vehicle fuel economy and fuel price, and (iii) quantifies resulting transportation energy affordability by census tract. This study found that the average burden by tract varies from 0.15% to 8%. The variation in affordability can be largely explained by income level and vehicle fuel efficiency. Suburban and rural households spend more on transportation energy compared with urban households because of the usage of less fuel-efficient vehicle technologies and higher annual VMT. Lower-income groups have a wide distribution of the percentage of income spent on transportation energy, 1.2% to 8%, whereas the range for the highest income group ($125,000+) is from 0.15% to 3.9%. This detailed transportation energy affordability analysis provides a better understanding of regional variations in household travel behavior, helps to determine where fuel-efficient vehicle technologies are more likely to be used, and improves estimates of vehicle ownership costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Male Runners With Lower Energy Availability Have Impaired Skeletal Integrity Compared to Nonathletes

Abstract Context Female athletes, particularly runners, with insufficient caloric intake for their energy expenditure [low energy availability (EA) or relative energy deficiency] are at risk for impaired skeletal integrity. Data are lacking in male runners. Objective To determine whether male runners at risk for energy deficit have impaired bone mineral density (BMD), microarchitecture, and estimated strength. Design Cross-sectional. Setting Clinical research center. Participants 39 men (20 runners, 19 controls), ages 16–30 years. Main Outcome Measures Areal BMD (dual-energy x-ray absorptiometry); tibia and radius volumetric BMD and microarchitecture (high-resolution peripheral quantitative computed tomography); failure load (microfinite element analysis); serum testosterone, estradiol, leptin; energy availability. Results Mean age (24.5 ± 3.8 y), lean mass, testosterone, and estradiol levels were similar; body mass index, percent fat mass, leptin, and lumbar spine BMD Z-score (−1.4 ± 0.8 vs −0.8 ± 0.8) lower (P < .05); and calcium intake and running mileage higher (P ≤ .01) in runners vs controls. Runners with EA <median had lower lumbar spine (−1.5 ± 0.7, P = .028), while runners with EA ≥median had higher hip (0.3 ± 0.7 vs −0.4 ± 0.5, P = .002), BMD Z-scores vs controls. After adjusting for calcium intake and running mileage, runners with EA <median had lower mean tibial total and trabecular volumetric BMD, trabecular bone volume fraction, cortical porosity, and apparent modulus vs controls (P < .05). Appendicular lean mass and serum estradiol (R ≥ 0.45, P ≤ .046), but not testosterone, were positively associated with tibial failure load among runners. Conclusions Despite weight-bearing activity, skeletal integrity is impaired in male runners with lower caloric intake relative to exercise energy expenditure, which may increase bone stress injury risk. Lower estradiol and lean mass are associated with lower tibial strength in runners.

Haines, Melanie S. (ORCID:0000000310024754)↗
DOE OSTI2013

Dose-Response Relationship of Physical Activity to Premature and Total All-Cause and Cardiovascular Disease Mortality in Walkers

Purpose: To assess the dose-response relationships between cause-specific mortality and exercise energy expenditure in a prospective epidemiological cohort of walkers. Methods: The sample consisted of the 8,436 male and 33,586 female participants of the National Walkers’ Health Study. Walking energy expenditure was calculated in metabolic equivalents (METs, 1 MET = 3.5 ml O2/kg/min), which were used to divide the cohort into four exercise categories: category 1 (#1.07 MET-hours/d), category 2 (1.07 to 1.8 MET-hours/d), category 3 (1.8 to 3.6 MET-hours/d), and category 4 ($3.6 MET-hours/d). Competing risk regression analyses were use to calculate the risk of mortality for categories 2, 3 and 4 relative to category 1. Results: 22.9% of the subjects were in category 1, 16.1% in category 2, 33.3% in category 3, and 27.7% in category 4. There were 2,448 deaths during the 9.6 average years of follow-up. Total mortality was 11.2% lower in category 2 (P = 0.04), 32.4% lower in category 3 (P,10212) and 32.9% lower in category 4 (P = 10211) than in category 1. For underlying causes of death, the respective risk reductions for categories 2, 3 and 4 were 23.6% (P = 0.008), 35.2% (P,1025 ), and 34.9% (P = 0.0001) for cardiovascular disease mortality; 27.8% (P = 0.18), 20.6% (P = 0.07), and 31.4% (P = 0.009) for ischemic heart disease mortality; and 39.4% (P = 0.18), 63.8% (P = 0.005), and 90.6% (P = 0.002) for diabetes mortality when compared to category 1. For all related mortality (i.e., underlying and contributing causes of death combined), the respective risk reductions for categories 2, 3 and 4 were 18.7% (P = 0.22), 42.5% (P = 0.001), and 57.5% (P = 0.0001) for heart failure; 9.4% (P = 0.56), 44.3% (P = 0.0004), and 33.5% (P = 0.02) for hypertensive diseases; 11.5% (P = 0.38), 41.0% (P,1024 ), and 35.5% (P = 0.001) for dysrhythmias: and 23.2% (P = 0.13), 45.8% (P = 0.0002), and 41.1% (P = 0.005) for cerebrovascular diseases when compared to category 1. Conclusions: There are substantial health benefits to exceeding the current exercise guidelines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

The Relationship of Walking Intensity to Total and Cause-Specific Mortality. Results from the National Walkers’ Health Study

Purpose: Test whether: 1) walking intensity predicts mortality when adjusted for walking energy expenditure, and 2) slow walking pace (≥24-minute mile) identifies subjects at substantially elevated risk for mortality. Methods: Hazard ratios from Cox proportional survival analyses of all-cause and cause-specific mortality vs. usual walking pace (min/mile) in 7,374 male and 31,607 female recreational walkers. Survival times were left censored for age at entry into the study. Other causes of death were treated as a competing risk for the analyses of cause-specific mortality. All analyses were adjusted for sex, education, baseline smoking, prior heart attack, aspirin use, diet, BMI, and walking energy expenditure. Deaths within one year of baseline were excluded. Results: The National Death Index identified 1968 deaths during the average 9.4-year mortality surveillance. Each additional minute per mile in walking pace was associated with an increased risk of mortality due to all causes (1.8% increase, P=10-5), cardiovascular diseases (2.4% increase, P=0.001, 637 deaths), ischemic heart disease (2.8% increase, P=0.003, 336 deaths), heart failure (6.5% increase, P=0.001, 36 deaths), hypertensive heart disease (6.2% increase, P=0.01, 31 deaths), diabetes (6.3% increase, P=0.004, 32 deaths), and dementia (6.6% increase, P=0.0004, 44 deaths). Those reporting a pace slower than a 24-minute mile were at increased risk for mortality due to all-causes (44.3% increased risk, P=0.0001), cardiovascular diseases (43.9% increased risk, P=0.03), and dementia (5.0-fold increased risk, P=0.0002) even though they satisfied the current exercise recommendations by walking ≥7.5 metabolic equivalent (MET)-hours per week. Conclusions: The risk for mortality: 1) decreases in association with walking intensity, and 2) increases substantially in association for walking pace ≥24 minute mile (equivalent to <400m during a six-minute walk test) even among subjects who exercise regularly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Modeling energy balance while correcting for measurement error via free knot splines

Measurements of energy balance components (energy intake, energy expenditure, changes in energy stores) are often plagued with measurement error. Doubly-labeled water can measure energy intake (EI) with negligible error, but is expensive and cumbersome. An alternative approach that is gaining popularity is to use the energy balance principle, by measuring energy expenditure (EE) and change in energy stores (ES) and then back-calculate EI. Gold standard methods for EE and ES exist and are known to give accurate measurements, albeit at a high cost. We propose a joint statistical model to assess the measurement error in cheaper, non-intrusive measures of EE and ES. We let the unknown true EE and ES for individuals be latent variables, and model them using a bivariate distribution. We try both a bivariate Normal as well as a Dirichlet Process Mixture Model, and compare the results via simulation. Our approach, is the first to account for the dependencies that exist in individuals’ daily EE and ES. We employ semiparametric regression with free knot splines for measurements with error, and linear components for error free covariates. We adopt a Bayesian approach to estimation and inference and use Reversible Jump Markov Chain Monte Carlo to generate draws from the posterior distribution. Based on the semiparameteric regression, we develop a calibration equation that adjusts a cheaper, less reliable estimate, closer to the true value. Along with this calibrated value, our method also gives credible intervals to assess uncertainty. A simulation study shows our calibration helps produce a more accurate estimate. Furthermore, our approach compares favorably in terms of prediction to other commonly used models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

The impact of climate change on Korea’s agricultural sector under the national self-sufficiency policy

Evolving environmental conditions due to climate change have brought about changes in agriculture, which is required for human life as both a source of food and income. International trade can act as a buffer against potential negative impacts of climate change on crop yields, but recent years have seen breakdowns in global trade, including export bans to improve domestic food security. For countries that rely heavily on imported food, governments may institute policies to protect their agricultural industry from changes in climate-induced crop yield changes and other countries’ potential trade restrictions. This study assesses the individual and combined effects of climate impacts and food self-sufficiency policies in Korea, which is highly dependent on imports. We use the Global Change Analysis Model (GCAM), a global integrated assessment model, to explore (1) the direct impact of climate change on Korea’s agricultural yields, (2) the full impacts of global climate change on agricultural production, including trade-induced changes due to yield changes in other regions, (3) the impacts of food self-sufficiency policy, and (4) the interactive impact of climate change and self-sufficiency policies. We find that, in Korea, the direct impact of climate change on agricultural yields would be overshadowed by the impact of global climate change due to changing trade patterns. Second, global climate change leads to a rise (rice and wheat) or a decline (soybeans) in Korean producer revenues, while simultaneously raising consumer expenditures on both staples and non-staples. Third, implementing self-sufficiency policies for wheat and soybeans in Korea boosts the nation’s producer revenues, in conjunction with the effects of climate change, at the cost of additional increases in consumer expenditures for both staples and non-staples.

Science & Technology - Other Topics↗
DOE OSTI2016

Net Shape Fabricated Low Cost MHK Pass-Through the Hub Turbine Blades with Integrated Health Management Technology

The primary objective of this project is to develop a three-blade MHK rotor with low manufacturing and maintenance costs. The proposed program will design, fabricate and test a novel half-scale low cost, net shape fabricated single piece three-blade MHK rotor with integrated health management technology to demonstrate significant Capital Expenditures (CAPEX) and Operational Expenditures (OPEX) cost reductions due to the novel design and manufacturing process. The proposed project is divided into three major tasks: Task 1: Single Piece Three-blade Kinetic Hydropower System (KHPS) Rotor Full-Scale and Half-Scale Design; Task 2: Composite Manufacturing Trials and Half-Scale Prototype Rotor Fabrication; and Task 3: Material Characterization and Half-Scale Prototype Test and Evaluation. These three tasks include design and analysis of full-scale and half-scale three-blade rotor prototypes using computational fluid dynamics (CFD) and finite-element analysis (FEA), demonstration of a novel half-scale net shape fabrication process, determination of a fatigue threshold composite strain allowable, three-blade rotor mold design, manufacture of half-scale rotor clam shell mold, three-blade rotor test fixture design and fabrication, development of final manufacturing and test plans, manufacture of the half-scale net shape composite single blade and three-blade prototypes, and test and evaluation of the half-scale rotor.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

TEAMER: MADWEC Techno-Economic Analysis

The objective of this project was for the facility to conduct a techno-economic assessment (TEA) of the Maximal Asymmetric Drag Wave Energy Converter (MADWEC), developed by the University of Massachusetts Dartmouth (UMass Dartmouth). MADWEC is used for powering remote monitoring and Autonomous Underwater Vehicle (AUV) charging systems compared to other existing power supply options. The assessment estimates capital expenditures (CapEx), operational expenditures (OpEx), and power performance for 18 scenarios with the purpose of identifying key cost drivers, comparing total system cost, and comparing the power performance of the power supply options in terms of required installed capacity and estimated theoretical annual energy performance. The 18 assessed scenarios include two end-uses: 1) AUV charging and 2) offshore remote monitoring); three power sources: 1) MADWEC), 2) photovoltaic (PV) solar buoy, 3) and traditional battery swapping); and three locations; 1) nearshore, 2) far-offshore, and 3) high-latitude). In addition, other project goals included developing high level installation, operation, and maintenance plans for each scenario. The techno-economic model, created in Microsoft Excel, estimates CapEx, OpEx, and the power performance of each power supply source. The model has a dynamic format that allows custom inputs to accommodate future changes to the systems being assessed. This is a TEA for the MADWEC project, TEAMER RFTS 7 (request for technical support) program.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Smart Charging for Electric Ride-Hailing Vehicles using Renewables: A San Francisco Case Study

Charging large fleets of electric ride-hailing vehicles (ERVs) is a complex matter that could serve different objectives: lower carbon dioxide emissions, lower monetary expenditures, or maximize solar photovoltaics (PV) energy consumption. Currently, it is unclear how each of those objectives could impact the business and performance of a ride-hailing fleet. In order to fill this gap, this article employs a dynamic transportation model: a smart charging simulation that combines agent-based, discrete-event, and system dynamic modelling by comparing the above-mentioned objectives in separate scenarios. The results show that each scenario successfully manages to shift between 34% and 87% of all load to hours of the day when the objectives of those scenarios are met. Therefore, in comparison to the baseline, smart charging can save between 5% and 26% of monthly emissions and between 4% and 57% of monthly expenditures. The solar PV scenario, however, results in the highest savings, while ensuring profitable economics via net metering in the short- as well as long term. Finally, the sensitivity analysis points to important trade-offs between several fleet performance metrics. The article concludes by giving business and policy recommendations for maximising the economic, energy and environmental efficiency of large ERV fleets.

ADVANCED PROPULSION SYSTEMS,SOLAR ENERGY↗
DOE OSTI2011

Measuring the Economic Impacts of Federal Investments in Research

Measuring the Economic Impacts of Federal Investments in Research evaluates approaches to measuring the returns on federal research investments. This report identifies new methodologies and metrics that can be developed and used for assessing returns on research across a wide range of fields (biomedical, information technology, energy, agriculture, environment, and other biological and physical sciences, etc.), while using one or more background papers that review current methodologies as a starting point for the discussion. It focuses on tools that are able to exploit available data in the relatively near term rather than on methodologies that may require substantial new data collection. Over the last several years, there has been a growing interest in policy circles in identifying the payoffs from federal agency research investments, especially in terms of economic growth, competitiveness, and jobs. The extraordinary increase in research expenditures under the American Recovery and Reinvestment Act (ARRA) of 2009 and the President's commitment to science and technology (S&T) funding increases going forward have heightened the need for measuring the impacts of research investments. Without a credible analysis of their outcomes, the recent and proposed increases in S&T funding may not be sustained, especially given competing claims for federal funding and pressures to reduce projected federal budget deficits. Motivated by these needs and requirements, Measuring the Economic Impacts of Federal Investments in Research reviews and discusses the use of quantitative and qualitative data to evaluate the returns on federal research and development (R&D) investments. Despite the job-focused mandate of the current ARRA reporting requirements, the impact of S&T funding extend well beyond employment. For instance, federal funding in energy research may lead to innovations that would reduce energy costs at the household level, energy imports at the national level, and greenhouse gas emissions at the global level. In principle, these benefits can be measured as a return on research investments, with appropriate consideration of time lags to research outcomes and attribution to private as well as public expenditure. With appropriate metrics, the same could be true for benefits to public health, environmental quality, and food productivity and security. Federal funding of research leads to the development of human capital that is deployed in a variety of occupations with economic and social impacts. Research also produces information that is used in formal (e.g., regulatory and judicial) and informal (e.g., firm and consumer) decision making processes. In addition to reviewing the range of work (by academics, consultants, and research agencies themselves) that has been done in measuring research outcomes and providing a forum to discuss their methods, this report also considers the different methodologies used across fields of research (e.g., agriculture and energy research) to identifies which are applicable to a range of federal S&T funding.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

Missouri Agricultural Energy Saving Team-A Revolutionary Opportunity (MAESTRO)

The Missouri Agricultural Energy Saving Team-A Revolutionary Opportunity (MAESTRO) program brought together a team of representatives from government, academia, and private industry to enhance the availability of energy efficiency services for small livestock producers in the State of Missouri. The Missouri Department of Agriculture (MDA) managed the project via a subcontract with the University of Missouri (MU), College of Agriculture Food and Natural Resources, MU Extension, the MU College of Human Environmental Sciences, the MU College of Engineering, and the Missouri Agricultural and Small Business Development Authority (MASBDA). MU teamed with EnSave, Inc, a nationally-recognized expert in agricultural energy efficiency to assist with marketing, outreach, provision of farm energy audits and customer service. MU also teamed with independent home contractors to facilitate energy audits of the farm buildings and homes of these livestock producers. The goals of the project were to: (1) improve the environment by reducing fossil fuel emissions and reducing the total energy used on small animal farms; (2) stimulate the economy of local and regional communities by creating or retaining jobs; and (3) improve the profitability of Missouri livestock producers by reducing their energy expenditures. Historically, Missouri scientists/engineers conducted programs on energy use in agriculture, such as in equipment, grain handling and tillage practices. The MAESTRO program was the first to focus strictly on energy efficiency associated with livestock production systems in Missouri and to investigate the applicability and potential of addressing energy efficiency in animal production from a building efficiency perspective. A. Project Objectives The goal of the MAESTRO program was to strengthen the financial viability and environmental soundness of Missouri's small animal farms by helping them implement energy efficient technologies for the production facility, farm buildings, and the homes on these farms. The expected measurable outcomes of the project were to improve the environment and stimulate the economy by: • Reducing annual fossil fuel emissions by 1,942 metric tons of carbon dioxide equivalent, reducing the total annual energy use on at least 323 small animal farms and 100 farm homes by at least 8,000 kWh and 2,343 therms per farm. • Stimulating the economy by creating or retaining at least 69 jobs, and saving small animal farmers an average of $2,071 per farm in annual energy expenditures. B. Project Scope The MAESTRO team chose the target population of small farms because while all agriculture is traditionally underserved in energy efficiency programs, small farms were particularly underserved because they lack the financial resources and access to energy efficiency technologies that larger farms deploy. The MAESTRO team reasoned that energy conservation, financial and educational programs developed while serving the agricultural community could serve as a national model for other states and their agricultural sectors. The target population was approximately 2,365 small animal farm operations in Missouri, specifically those farms that were not by definition a confined animal feeding operation (CAFO). The program was designed to create jobs by training Missouri contractors and Missouri University Extension staff how to conduct farm audits. The local economy would be stimulated by an increase in construction activity and an increasing demand for energy efficient farm equipment. Additionally, the energy savings were deemed critical in keeping Missouri farms in business. This project leveraged funds using a combination of funds from the Missouri Department of Natural Resources’ Missouri Energy Center and its Soil and Water Conservation Program, from the state's Linked Deposits, MASBDA's agricultural loan guarantee programs, and through the in-kind contribution of faculty and staff time to the project from these agencies and MU. Several hundred Missouri livestock producers were contacted during the MAESTRO project. Of the livestock producers, 254 invited the team to conduct a farm energy assessment which complied with ASABE 612. A total of 147 livestock farm upgrades were implemented, representing 57.5 percent of the farms for which a farm energy assessment was completed. This represented a statewide average annual savings of 1,088,324 kWh and 75,516 therms. The team also reviewed the condition of the livestock producer’s home(s). A total of 106 home energy assessments were completed and 48 individual homes implemented their recommended upgrades, representing 45 percent of the farm homes for which an energy assessment was completed. This represented a statewide average annual savings of 323,029 kWh, and 769.4 therms. More of these farmers likely would have updated their homes but the funding to incentivize them fell short. In spite of the shortfall in incentive funds, some farmers still updated their homes as they saw the value in making these changes to their home.

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↗