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Each quarter, the National Renewable Energy Laboratory (NREL) conducts the Quarterly Solar Industry Update, a presentation of technical trends within the solar industry Each presentation focuses on global and U.S. supply and demand, module and system price, investment trends and business models, and updates on U.S. government programs supporting the solar industry.
Each quarter, the National Renewable Energy Laboratory (NREL) conducts the Quarterly Solar Industry Update, a presentation of technical trends within the solar industry Each presentation focuses on global and U.S. supply and demand, module and system price, investment trends and business models, and updates on U.S. government programs supporting the solar industry.
This is the First Quarterly Report for the newly reconstituted Aerospace Safety Advisory Panel (ASAP). The NASA Administrator rechartered the Panel on November 18,2003, to provide an independent, vigilant, and long-term oversight of NASA's safety policies and programs well beyond Return to Flight of the Space Shuttle. The charter was revised to be consistent with the original intent of Congress in enacting the statute establishing ASAP in 1967 to focus on NASA's safety and quality systems, including industrial and systems safety, risk-management and trend analysis, and the management of these activities.The charter also was revised to provide more timely feedback to NASA by requiring quarterly rather than annual reports, and by requiring ASAP to perform special assessments with immediate feedback to NASA. ASAP was positioned to help institutionalize the safety culture of NASA in the post- Stafford-Covey Return to Flight environment.
Each quarter, the National Renewable Energy Laboratory (NREL) conducts the Quarterly Solar Industry Update, a presentation of technical trends within the solar industry, to the solar office staff. Each presentation focuses on global and U.S. supply and demand, module and system price, investment trends and business models, and updates on U.S. government programs supporting the solar industry.
Each quarter, the National Renewable Energy Laboratory (NREL) conducts the Quarterly Solar Industry Update, a presentation of technical trends within the solar industry, to the solar office staff. Each presentation focuses on global and U.S. supply and demand, module and system price, investment trends and business models, and updates on U.S. government programs supporting the solar industry.
The overarching goal of this project was to deepen the understanding of the social and economic aspects of solar adoption, with a specific eye towards any pathways or barriers that could be identified that directly impact low and moderate-income households. Specific objectives included (1) identifying and assessing significant non-economic barriers that complicate the ability of LMI households to adopt and benefit from solar, even under scenarios with low economic barriers; (2) assessing the differential ability of groups to benefit from solar adoption based on their ability to invest in different solar innovations; (3) explaining why some LMI communities nonetheless experience significantly higher rates of solar adoption and benefit than others; (4) developing a methodological model for generating data addressing key issues to the project; and (5) designing and developing an interactive web portal that aggregates existing datasets, provides researchers trend analysis capabilities, standardizes project protocols for other states and communities; provides the opportunities for researchers using the same protocol in other communities to upload their results; and engages with the general public by providing them the ability to upload their own perspectives and stories of solar technology adoption. Through a common framework for conducting semi-structured field interviews. In partnership with cooperative extension services, in conjunction with survey research and the aggregation of existing solar adoption datasets, this study has identified that currently ,there is a strong values alignment and knowledge access challenge that continues to affect solar adoption. Participants in this study – many of whom are either low or moderate-income and/or live in underserved rural communities do not believe solar is an option where they live or believe solar is appropriate for their lifestyle. This perception challenge is further exacerbated by the absolute dearth of adopters in most communities and a total lack of local marketing for solar energy. What marketing that does exist is geared towards audiences other than those in the participant's community, reinforcing a perception that 22% of survey respondents (n = 1,551) have: that solar energy is not meant for them and their community. Overcoming these serious human challenges pertaining to knowledge and marketing are critical to reducing the customer acquisition costs incurred amongst LMI communities and especially those in rural America where the opportunities solar provides to increase local energy resilience, security, all while engaging in personal stewardship of the planet could align with local values. Community-Based Social Marketing, built in partnership with community leaders and geared towards meeting local visions of ideal life, is a near term opportunity to bridge the gap between local priorities and national market and policy imperatives for solar while moving towards the administration's goals for renewable energy as part of a just and equitable decarbonization program. The tools and methods developed for this study can serve as a template for identifying other specific local challenges for solar adoption in other state, and provide the opportunity for a common data framework for understanding system-wide trends and barriers to achieving uptake of residential solar in communities that may, ultimately, benefit the most from the technology.
The following sections are included: Introduction, Historical to Present Day, Projecting the Future, Ambitious Goals, Lagging Implementation, Sustainable Urban Energy Transitions, and References.
The paper discusses the need for increased awareness in space law due to advances in space technology and a trend toward commercialization of space. A list of national and international treaties, conventions, agreements, laws, and regulations relevant to space activities is presented. NASA lawyers specialize in international and municipal laws that affect the NASA space mission; an example of the lawyers working with insurance companies in negotiating the first Space Shuttle liability policy is provided. The increased participation of the public sector in space activities, for example, the commercialization of the Space Shuttle transportation system, is examined.
In situ processing aims to alleviate the growing gap between computation and I/O capabilities by performing data processing close to the data source. In situ processing is widely used to process data generated by multiple data sources, including observation data from edge devices or scientific observational facilities and the simulation data generated by scientific computation on a high-performance computing (HPC) platform. For a scientific workflow that is run on an HPC platform and composed of a simulation program and an in situ data analytics or visualization (abbreviated as ana/vis) task, there is an implicit assumption that the computing resources assigned to the workflow keep static during the workflow execution. However, with the converging trend between the HPC and cloud computing platform, running the in situ ana/vis task in an elastic way is promising to decrease its overhead and improve its resource utilization rate. Resource elasticity represents the ability to change resource configurations such as the number of computing nodes/processes during workflow execution. An elastic job may dynamically adjust resource configurations; it may use a few resources at the beginning and more resources toward the end of the job when interesting data appear. However, it is hard to predict a priori how many computing nodes/processes need to be added/removed during the workflow execution to adapt to changing workflow needs. How to efficiently guide elasticity operations, such as growing or shrinking the number of processes used for in situ analysis during workflow execution, is an open-ended research question. In this article, we present adaptive elasticity policies that adopt workflow runtime information collected during workflow execution to predict how to trigger the addition/removal of processes in order to minimize in situ processing overhead. Taking in situ visualization tasks as an example, we integrate the presented elasticity policies into a staging-based elastic workflow and evaluate its efficiency in multiple elasticity scenarios. Compared with the situation without elasticity or with a static elasticity policy that uses a fixed number of processes for each rescaling operation, the adaptive elasticity policy can save overhead in finding a proper resource configuration and improve resource utilization efficiency. Furthermore, one experiment illustrates that the adaptive elasticity policy saves 41% of core-hours compared with the situation without the resource elasticity.
This presentation presents a brief overview of the collection of information about the US government's fleet of motor vehicles using the Federal Automotive Statistical Tool (FAST), discusses the makeup and operation of the vehicle fleet during FY 2021, discusses quality of the submitted data, and touches on future aspects of fleet data collection and reporting. FAST is a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles; FAST is developed, maintained, and supported by DOE's Idaho National Laboratory (INL).
The Land-Based Wind Market Report: 2021 Edition provides an overview of developments and trends in the U.S. wind power market.
Foot-and-mouth disease (FMD) is one of the most economically important livestock diseases worldwide. Following the clinical phase of FMD, a large proportion of ruminants remain persistently infected for extended periods. Although extinction of this carrier state occurs continuously at the animal and population levels, studies vary widely in their estimates of the duration of persistent infection. There is a need for robust statistical models to capture the dynamics of persistent infection for the sake of guiding FMD control and trade policies. The goal of the current study was to develop and assess statistical models to describe the extinction of FMD virus (FMDV) persistent infection using data from primary longitudinal studies of naturally infected cattle and Asian buffalo in Vietnam and India. Specifically, accelerated failure time (AFT) models and generalized linear mixed models (GLMM) were developed to predict the probability of persistent infection in seropositive animals and identified carriers at the individual animal level at sequential time points after outbreaks. The primary studies were analyzed by country and combined using an individual-participant data meta-analysis approach. The models estimated similar trends in the duration of persistent infection for the study/species groups included in the analyses, however the significance of the trends differed between the models. The overall probabilities of persistent infection were similar as predicted by the AFT and GLMM models: 6 months: 99% (AFT) /80% (GLMM), 12 months: 51% (AFT) /32% (GLMM), 18 months: 6% (AFT) /5% (GLMM), 24 months: 0.8% (AFT) /0.6% (GLMM). These models utilizing diverse and robust data sets predict higher probabilities of persistence than previously published, suggesting greater endurance of carriers subsequent to an outbreak. This study demonstrates the utility of statistical models to investigate the dynamics of persistent infection and the importance of large datasets, which can be achieved by combining data from several smaller studies in meta-analyses. Results of this study enhance current knowledge of the FMDV carrier state and may inform policy decisions regarding FMDV persistent infection.
Hydrogen is a rapidly growing focus for countries seeking to develop green industries, but there are many questions about how the nascent global hydrogen economy will develop, and what this implies for equitable sharing of benefits and burdens between nations. In this perspective we summarize emerging trends in national hydrogen strategies and develop recommendations for researchers and policymakers to center equity in hydrogen development. This will require integrating innovation and development perspectives on international technology transfer, developing more detailed representation of hydrogen trade in systems models, building equity considerations into national and international planning processes, and establishing robust technology transfer efforts. In conclusion, policymakers will also need to grapple with the difficulties of verifying life cycle emissions of hydrogen if hydrogen trade emerges as a significant trend, potentially requiring new methods of emissions accounting and trade reforms that prioritize international equity.
Background: Microsimulation models are mathematical models that simulate event histories for individual members of a population. They are useful for policy decisions because they simulate a large number of individuals from an idealized population, with features that change over time, and the resulting event histories can be summarized to describe key population-level outcomes. Model calibration is the process of incorporating evidence into the model. Calibrated models can be used to make predictions about population trends in disease outcomes and effectiveness of interventions, but calibration can be challenging and computationally expensive. Methods: This paper develops a technique for sequentially updating models to take full advantage of earlier calibration results, to ultimately speed up the calibration process. A Bayesian approach to calibration is used because it combines different sources of evidence and enables uncertainty quantification which is appealing for decision-making. We develop this method in order to re-calibrate a microsimulation model for the natural history of colorectal cancer to include new targets that better inform the time from initiation of preclinical cancer to presentation with clinical cancer (sojourn time), because model exploration and validation revealed that more information was needed on sojourn time, and that the predicted percentage of patients with cancers detected via colonoscopy screening was too low. Results: The sequential approach to calibration was more efficient than recalibrating the model from scratch. Incorporating new information on the percentage of patients with cancers detected upon screening changed the estimated sojourn time parameters significantly, increasing the estimated mean sojourn time for cancers in the colon and rectum, providing results with more validity. Conclusions: A sequential approach to recalibration can be used to efficiently recalibrate a microsimulation model when new information becomes available that requires the original targets to be supplemented with additional targets.
The report describes income, demographic, and other socio-economic trends among U.S. residential rooftop solar adopters. The report is based on address-level data for roughly 2.8 million residential rooftop solar systems installed through 2021, representing 86% of all U.S. systems. With its unique size, geographic scope, and level of detail, this report is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and researchers. Key findings include the following: -Median solar adopter income was about $\$110$k/year in 2021, compared to a U.S. median of about $\$63$k/year for all households and $\$79$k/year for all owner-occupied households -The degree of income skew varies significantly across all states, but all states exhibit some positive income skew, with median solar-adopter incomes ranging from 131-168% of the respective county-median income for all households -Notwithstanding the fact that solar adopter incomes skew high, a substantial share of adopters could be considered low-to-moderate income (LMI), with 22% of all 2021 adopters earning less than 80% of area median income, and an additional 21% between 80% and 120% of area median income. -Solar-adopter incomes are declining over time, with median incomes dropping from $\$129$k in 2010 to $\$110$k in 2021, as adoption becomes more proportionately distributed across the population and has started to broaden into low- and middle-income states since 2016. -Solar-adopter incomes are consistently higher for systems paired with battery storage, for host-owned systems, and for systems installed on single-family homes; higher income adopters also consistently install larger systems. -Solar adopters tend to live in Census Tracts not identified as “disadvantaged communities” (using the U.S. Department of Energy’s interim definitions developed March 2022), making up 11% of adopters compared to 18% of U.S. households. -Compared to the broader population, solar adopters tend to: identify as Non-Hispanic White, be primarily English-speaking, have higher education levels, be middle-aged, work in business and finance-related occupations, and live in higher-value homes In conjunction with the report, Berkeley Lab has published an updated accompanying set of online data visualizations that allow users to further explore the underlying data. Berkeley Lab is also offering related analytical support to states, local agencies, and other organizations on issues related to solar adoption among low-to-moderate income households; requests for analytical support may be submitted through this online form.
The report describes income, demographic, and other socio-economic trends among U.S. residential rooftop solar adopters. The report is based on address-level data for roughly 3.4 million residential rooftop solar systems installed through 2022, representing 86% of all U.S. systems. With its unique size, geographic scope, and level of detail, this report is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and researchers. Key findings include the following: (1) Median solar adopter income was about $\$117$k/year in 2022, compared to a U.S. median of about $\$69$k/year for all households and $\$86$k/year for all owner-occupied households; (2) The degree of income skew varies significantly across all states, but all exhibit some positive income skew relative to all households in the state, with median solar-adopter incomes ranging from 108-180% of the respective state-median income for all households; (3) Roughly 45% of solar adopters in 2022 had incomes below 120% of their area median income (AMI), a threshold sometimes used to define “low-and-moderate income” (or LMI), while 23% were below 80% of AMI, often used to define “low-income”; (4) Solar adoption continues to shift toward less affluent households, with the median current income of solar adopters dropping from $\$140$k for households that installed systems in 2010 to $\$117$k in 2022; (5) PV systems installed in 2022 by households earning less than $50k had a median size of 6.1 kW, 34% were third-party owned, and 5% included battery storage, compared to corresponding values of 7.6%, 17%, and 15% for households earning more than 200 dollars k; and (6) Compared to all households in their respective state, solar adopters tend to be negligibly more rural; have higher home values; and are more likely to be college educated, identify as non-Hispanic white, live outside a disadvantaged community (DAC), be middle-aged, work in a business or financial occupation, and own a single-family home In conjunction with the report, Berkeley Lab has published an updated accompanying set of online data visualizations that allow users to further explore the underlying data. Berkeley Lab is also offering related analytical support to states, local agencies, and other organizations on issues related to solar adoption among low-to-moderate income households.
Bangladesh is aiming to limit emissions, and gain access to cleaner, more efficient technologies to support economic growth as the nation strives to achieve high-income status by 2041. Bangladesh identified that it has a potential for offshore wind energy, especially at hub heights of 140 to 160 meters, which is pivotal in diversifying the country's energy mix and ensuring energy security. This one-day webinar is funded by the United States Agency for International Development (USAID) through two projects: (1) Reinforcing Advanced Energy Systems (RAES) project, implemented by the U.S. Department of Energy's National Renewable Energy Laboratory (NREL), and (2) Bangladesh Advancing Development and Growth through Energy (BADGE) project, implemented by Tetra Tech.
The report describes income, demographic, and other socio-economic trends among U.S. residential rooftop solar adopters. The report is based on address-level data for roughly 4.1 million residential rooftop solar systems installed through 2023, representing 87% of all U.S. systems. With its unique size, geographic scope, and level of detail, this report is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and researchers. Key findings include the following: -The median income of households that installed solar in 2023 was about $\$$115k/year, compared to a U.S. median of $\$$75k/year for all households and $\$$94k/year for all U.S. owner-occupied households. -Compared to owner-occupied households in the same state, 2023 solar-adopter incomes were 7% higher in the median case, and in 10 states, median solar-adopter incomes were below the corresponding median income for all owner-occupied households. -Roughly 49% of solar adopters in 2023 had incomes below 120% of their area median income (AMI), a threshold sometimes used to define “low-and-moderate income” (or LMI), while 26% were below 80% of AMI, often used to define “low-income”. -Solar adoption continues to shift toward less affluent households over time, with the median present-day income of solar adopters dropping from $\$$141k for households that installed systems in 2010 to $\$$115k in 2023. -PV systems installed in 2023 by households earning less than $\$$50k had a median size of 6.4 kW, 33% were third-party owned, and 6% included battery storage, compared to corresponding values of 8.0 kW, 18%, and 14% for households earning more than $\$$200k. -Compared to all households in their respective state, solar adopters in 2023 were slightly more likely to be college educated and to live in rural areas; had higher home values; and were more likely to live outside a disadvantaged community (DAC), be middle-aged, identify as non-Hispanic white, work in a business or financial occupation, and own a single-family home. In conjunction with the report, Berkeley Lab has published an updated accompanying set of online data visualizations that allow users to further explore the underlying data. Berkeley Lab is also offering related analytical support to states, local agencies, and other organizations on issues related to solar adoption among low-to-moderate income households; requests for analytical support may be submitted through this online form.