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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Community Solar Value Project

The Community Solar Value Project (CSVP) is designed to assist electric utilities in designing better community solar programs. Better programs seek new sources of value to promote “win-win” solutions between utilities and their customers. The CSVP focused on five “challenge areas” in identifying new sources of value: - Strategic solar design for community solar projects (including technology choices, siting, orientation, and related issues) - Market research and targeted marketing approaches (for program design and for customer recruitment) - Procurement and financing (for establishing best practices that can bring economies of scale and economies of expertise) - Integration of “companion measures” (such as storage and demand-response options that can benefit customer and utility net load shapes) - Pricing in program design (including best practices for integration of identified value in program prices or credits) The CSVP directly engaged the Sacramento Municipal Utility District (SMUD), the Public Service Company of New Mexico (PNM), and more than a dozen other utilities to develop improved community solar program designs. The outcomes include a plan at SMUD for over 100 MW or more of community and shared solar and support for new or expanded programs at 15 other utilities so far. Resulting best-practice solutions have not only informed program applications, but also have generated discussion among experts and industry associations about the new opportunities and challenges CSVP has brought forth. In these ways, the CSVP has impacted community solar programs and DER plans, competitive innovations and policies nationwide. The CSVP team has been led by Extensible Energy under John Powers, President and CEO. Jill Cliburn, of Santa Fe, NM-based Cliburn and Associates, has served as Principal Investigator. The team also benefitted from expertise from Navigant, Olivine Inc. and Millennium Energy, LLC, in addition to the collaborative and cost-sharing contributions of its utility partners. The CSVP team participated fully in the Solar Market Pathways Program, which was initiated under the U.S. Department of Energy SunShot program and reports to the U.S. Department of Energy Solar Energy Technologies Office. This report summarizes a multi-disciplinary project that took place over 33 months from January, 2015 through September, 2017.

14 SOLAR ENERGY↗
DOE OSTI2020

Using Behavioral Science to Target LMI and High-Value Solar Installations (Final Technical Report)

This project is a data-driven analysis of approaches to facilitate solar adoption in LMI communities and areas with high potential benefits to the electric grid. The cornerstone of the project was two waves of randomized field experiments. The first wave involved novel approaches to reaching LMI communities based on insights from literature. The second wave involved areas of high potential of solar to the electricity grid, as determined in collaboration with the local utilities in Connecticut. Both waves were followed by surveys to develop insight into the effectiveness of different approaches. A third key element of the project is the development of new agent-based models of solar energy diffusion that explicitly incorporate the real spatial and temporal constraints that influence solar diffusion, based on real-world data on solar adoption. The project also involved outreach and dissemination of key findings to relevant stakeholders, including a guidebook on strategies to accelerate solar deployment to low and moderate income communities, multiple academic publications, and numerous presentations of the research findings.

14 SOLAR ENERGY↗
DOE OSTI2017

U.S. Solar Market Value Report: Further Evidence that Solar Adds Value to Real Estate

Solar photovoltaic systems provide cost savings to the property owner in terms of avoided electricity costs that accrue over the system lifetime. From an investment standpoint, the equipment and the value of the energy generated can potentially increase the underlying property value. This first-of-a-kind study presents real market data collected from real estate appraisers using the PV Value® tool to develop a market value for solar as part of a property sale or refinance. Aggregated results at the state level are discussed for California, Arizona and Massachusetts, using 2015 and 2016 data where appraisers used the income capitalization approach to develop a market value for solar. Additional data collection using future transaction data could reveal market-specific trends and insights at the zip code, city and metropolitan statistical area (MSA) levels.

14 SOLAR ENERGY↗
DOE OSTI2017

Data Challenges in Estimating the Capacity Value of Solar Photovoltaics

We examine the robustness of solar capacity-value estimates to three important data issues. The first is the sensitivity to using hourly averaged as opposed to subhourly solar-insolation data. The second is the sensitivity to errors in recording and interpreting load data. The third is the sensitivity to using modeled as opposed to measured solar-insolation data. We demonstrate that capacity-value estimates of solar are sensitive to all three of these factors, with potentially large errors in the capacity-value estimate in a particular year. If multiple years of data are available, the biases introduced by using hourly averaged solar-insolation can be smoothed out. Multiple years of data will not necessarily address the other data-related issues that we examine. Our analysis calls into question the accuracy of a number of solar capacity-value estimates relying exclusively on modeled solar-insolation data that are reported in the literature (including our own previous works). Our analysis also suggests that multiple years' historical data should be used for remunerating solar generators for their capacity value in organized wholesale electricity markets.

14 SOLAR ENERGY↗
DOE OSTI2021

Quantifying Rooftop Solar Benefits: A State-Level Value of Solar Analysis for India

Analyses that quantify the costs and benefits associated with rooftop solar (RTS) adoption and operation can inform decision-makers in the development and evaluation of RTS policies. One such analysis is a Value of Solar (VOS) study, which quantifies select costs and benefits surrounding RTS based on the electricity system context. These studies can drive changes to existing policies towards fairer, more cost-reflective RTS compensation or alternatively can provide confidence for the decision-maker to stay the course and largely maintain existing policies. This report provides a VOS analysis for two states in India: Gujarat and Jharkhand and provides details related to the methodology and key findings.

14 SOLAR ENERGY↗
DOE OSTI2015

Estimation of missing values in solar radiation data using piecewise interpolation methods: Case study at Penang city

The solar radiation values have been composed by automatic weather station using the device that namely pyranometer. The device is functions to records all the radiation values that have been dispersed, and these data are very useful for it experimental works and solar device’s development. In addition, for modeling and designing on solar radiation system application is needed for complete data observation. Unfortunately, lack for obtained the complete solar radiation data frequently occur due to several technical problems, which mainly contributed by monitoring device. Into encountering this matter, estimation missing values in an effort to substitute absent values with imputed data. This paper aimed to evaluate several piecewise interpolation techniques likes linear, splines, cubic, and nearest neighbor into dealing missing values in hourly solar radiation data. Then, proposed an extendable work into investigating the potential used of cubic Bezier technique and cubic Said-ball method as estimator tools. As result, methods for cubic Bezier and Said-ball perform the best compare to another piecewise imputation technique.

14 SOLAR ENERGY↗
DOE OSTI2016

NOMINAL VALUES FOR SELECTED SOLAR AND PLANETARY QUANTITIES: IAU 2015 RESOLUTION B3

In this brief communication we provide the rationale for and the outcome of the International Astronomical Union (IAU) resolution vote at the XXIXth General Assembly in Honolulu, Hawaii, in 2015, on recommended nominal conversion constants for selected solar and planetary properties. The problem addressed by the resolution is a lack of established conversion constants between solar and planetary values and SI units: a missing standard has caused a proliferation of solar values (e.g., solar radius, solar irradiance, solar luminosity, solar effective temperature, and solar mass parameter) in the literature, with cited solar values typically based on best estimates at the time of paper writing. As precision of observations increases, a set of consistent values becomes increasingly important. To address this, an IAU Working Group on Nominal Units for Stellar and Planetary Astronomy formed in 2011, uniting experts from the solar, stellar, planetary, exoplanetary, and fundamental astronomy, as well as from general standards fields to converge on optimal values for nominal conversion constants. The effort resulted in the IAU 2015 Resolution B3, passed at the IAU General Assembly by a large majority. The resolution recommends the use of nominal solar and planetary values, which are by definition exact and are expressed in SI units. These nominal values should be understood as conversion factors only, not as the true solar/planetary properties or current best estimates. Authors and journal editors are urged to join in using the standard values set forth by this resolution in future work and publications to help minimize further confusion.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2014

The Impact of Different Absolute Solar Irradiance Values on Current Climate Model Simulations

Simulations of the preindustrial and doubled CO2 climates are made with the GISS Global Climate Middle Atmosphere Model 3 using two different estimates of the absolute solar irradiance value: a higher value measured by solar radiometers in the 1990s and a lower value measured recently by the Solar Radiation and Climate Experiment. Each of the model simulations is adjusted to achieve global energy balance; without this adjustment the difference in irradiance produces a global temperature change of 0.48C, comparable to the cooling estimated for the Maunder Minimum. The results indicate that by altering cloud cover the model properly compensates for the different absolute solar irradiance values on a global level when simulating both preindustrial and doubled CO2 climates. On a regional level, the preindustrial climate simulations and the patterns of change with doubled CO2 concentrations are again remarkably similar, but there are some differences. Using a higher absolute solar irradiance value and the requisite cloud cover affects the model's depictions of high-latitude surface air temperature, sea level pressure, and stratospheric ozone, as well as tropical precipitation. In the climate change experiments it leads to an underestimation of North Atlantic warming, reduced precipitation in the tropical western Pacific, and smaller total ozone growth at high northern latitudes. Although significant, these differences are typically modest compared with the magnitude of the regional changes expected for doubled greenhouse gas concentrations. Nevertheless, the model simulations demonstrate that achieving the highest possible fidelity when simulating regional climate change requires that climate models use as input the most accurate (lower) solar irradiance value.

climate change↗
DOE OSTI2015

Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis

This paper intends to reveal the ability of the linear interpolation method to predict missing values in solar radiation time series. Reliable dataset is equally tends to complete time series observed dataset. The absence or presence of radiation data alters long-term variation of solar radiation measurement values. Based on that change, the opportunities to provide bias output result for modelling and the validation process is higher. The completeness of the observed variable dataset has significantly important for data analysis. Occurrence the lack of continual and unreliable time series solar radiation data widely spread and become the main problematic issue. However, the limited number of research quantity that has carried out to emphasize and gives full attention to estimate missing values in the solar radiation dataset.

42 ENGINEERING↗
DOE OSTI2015

Endogenous Assessment of the Capacity Value of Solar PV in Generation Investment Planning Studies

There exist several different reliability-and approximation-based methods to determine the contribution of solar resources toward resource adequacy. However, most of these approaches require knowing in advance the installed capacities of both conventional and solar generators. This is a complication since generator capacities are actually decision variables in capacity planning studies. In this paper, we study the effect of time resolution and solar PV penetration using a planning model that accounts for the full distribution of generator outages and solar resource variability. We also describe a modification of a standard deterministic planning model that enforces a resource adequacy target through a reserve margin constraint. Our numerical experiments show that at least 50 days worth of data are necessary to approximate the results of the full-resolution model with a maximum error of 2.5% on costs and capacity. We also show that the amount of displaced capacity of conventional generation decreases rapidly as the penetration of solar PV increases. We find that using an exogenously defined and constant capacity value based on time-series data can yield relatively accurate results for small penetration levels. For higher penetration levels, the modified deterministic planning model better captures avoided costs and the decreasing value of solar PV.

14 SOLAR ENERGY↗
DOE OSTI2014

Endogenous Assessment of the Capacity Value of Solar PV in Generation Investment Planning Studies. Draft

There exist several different reliability- and approximation-based methods to determine the capacity contribution of solar resources towards resource adequacy. However, most of these approaches require knowing in advance the installed capacities of both conventional and solar generators. This is a complication since generator capacities are actually decision variables in capacity planning studies. In this article we study the effect of time resolution and solar PV penetration using a capacity planning model that accounts for the full distribution of generator outages and solar resource variability. We also describe a modification of a standard deterministic planning model that enforces a resource adequacy target through a reserve margin constraint. Our numerical experiments show that at least 50 days worth of data are necessary to approximate the results of the full-resolution model with a maximum error of 2.5% on costs and capacity. We also show that the amount of displaced capacity of conventional generation decreases rapidly as the penetration of solar PV increases. We find that using an exogenously defined and constant capacity factor based on time-series data can yield relatively accurate results for small penetration levels (less than 5%). For higher penetration levels (up to 20%), the modified deterministic planning model better captures avoided costs and the decreasing value of solar PV. Although our results are not general, they highlight the importance of accounting for the variation in both energy and capacity value of solar resources endogenously in capacity planning models. A11 numerical experiments are performed using the IEEE Reliability Test System and 7 years worth of demand and solar data from a utility in Arizona.

14 SOLAR ENERGY↗
DOE OSTI2015

Analysis of Solar Census Remote Solar Access Value Calculation Methodology

The costs of photovoltaic (PV) system hardware (PV panels, inverters, racking, etc.) have fallen dramatically over the past few years. Nonhardware (soft) costs, however, have failed to keep pace with the decrease in hardware costs, and soft costs have become a major driver of U.S. PV system prices. Upfront or 'sunken' customer acquisition costs make up a portion of an installation's soft costs and can be addressed through software solutions that aim to streamline sales and system design aspects of customer acquisition. One of the key soft costs associated with sales and system design is collecting information on solar access for a particular site. Solar access, reported in solar access values (SAVs), is a measurement of the available clear sky over a site and is used to characterize the impacts of local shading objects. Historically, onsite shading studies have been required to characterize the SAV of the proposed array and determine the potential energy production of a photovoltaic system.

14 SOLAR ENERGY↗
DOE OSTI2025

A Review of Value of Solar Studies In Theory and In Practice

This brief summarizes a collection of state- and utility-commissioned value-of-solar (VoS) studies and related literature, with a focus on who commissioned the study, which value and cost categories were discussed and/or quantified, and the methods used. Our objective is to compile information on prior VoS studies to inform state regulators and other stakeholders that may pursue related studies or integrate findings into rate design. The brief is organized into three parts: 1) an introduction to distributed solar photovoltaic (DPV) compensation; 2) a review of theoretical research on VoS; and 3) a review of VoS studies. The vast majority of VoS studies have served an informational role of quantifying the net benefits of PV. Three studies were commissioned in states or utility service territories that subsequently implemented VoS tariffs in California, New York, and Austin, Texas. When applied as a tariff, VoS aims to compensate PV output as efficiently as possible by doing so at rates that reflect the marginal benefits and costs of PV through value and cost categories that may vary temporally and/or geographically. This could lead to higher compensation in locations and times where more PV output is more valuable and consequently drive adoption in those locations to provide more societal benefits. Value and cost factors can be broadly grouped into five categories: generation, transmission, distribution, other utility, and other social categories. Those conducting VoS studies must weigh various tradeoffs when deciding which categories to include and quantify. Tradeoffs include prioritizing values based on their magnitude of value or cost impact, as well as taking into account the feasibility of data collection and accurate quantification. Values of higher magnitude and estimation feasibility are quantified in the majority of studies, including the earliest of studies conducted in the 2000s and 2010s. Additionally, some values of higher magnitude but low feasibility in the earliest of studies have become quantifiable in recent years. There are some values with low average system-wide levels but very high magnitude in specific locations or hours. The value magnitude in some cases can be tied to DPV penetration with low value in areas with little congestion and/or low penetration and vice versa. In these cases, values that are easier to quantify are often incorporated, while those that are more difficult are often addressed via a placeholder value. The placeholder value is paired with a discussion around data needs and methods to improve future estimates, as well as a conversation about when these value categories may increase in magnitude and necessitate more rigorous quantification. This brief summarizes findings from two meta-analyses of VoS studies that took place between 2005 and 2018, as well as findings from four additional studies published from 2018 to 2023. Table ES-1 summarizes the various value and cost categories included in each respective study and whether they were quantified, discussed, or omitted. Values such as avoided energy, capacity, transmission capacity, line losses, and avoided environmental costs are quantified in every study. Some categories were deemed harder to quantify and less impactful at the time of the study, so they were discussed but not quantified (e.g., ancillary services). Other categories, including many at the distribution level, were very locationally and/or temporally specific and dependent on high DPV penetration. These were sometimes quantified and at other times discussed. Notably, when it came to utility costs, integration costs were discussed in all cases, though they were deemed to have a small impact. Other utility costs were omitted for the most part; however, the utility-commissioned study (by NorthWestern Energy in Montana) included both lost utility revenue and programmatic/administrative cost categories. While there are some similarities across studies, each had fairly unique methods that are detailed in the body of this brief.

14 SOLAR ENERGY↗
NASA NTRS1988

Total solar irradiance values determined using Earth Radiation Budget Experiment (ERBE) radiometers

During the October 1984 through January 1988 period, the ERBE solar monitors on the NASA Earth Radiation Satellite and on the National Oceanic and Atmospheric Administration NOAA 9 and NOAA 10 spacecraft were used to obtain mean total solar irradiance values of 1365, 1365, and 1363 W/sq m, respectively. Secular variations in the solar irradiance have been observed, and they appear to be correlated with solar activity.

Lee, Robert B., III↗
DOE OSTI2015

Value of Solar. Program Design and Implementation Considerations

Here, we present an analysis that assesses the potential market type that might form in the United States under a VOS rate, given current national average solar costs and various incentive scenarios, for the most populous city in each state. Three hypothetical VOS tariffs were developed, based on assumptions of avoided fuel costs, avoided capacity, environmental benefits, and line losses, to represent a of range of possible VOS rates. The levelized cost of solar in 50 locations is calculated using NREL’s System Advisor Model (SAM) using input assumptions regarding system size, resource quality, avoided capacity (aka capacity factor) and a variety of incentives. Comparing the solar costs with the hypothetical VOS rates illustrates the various market types that may form under a VOS program, in different locations.

14 SOLAR ENERGY↗
DOE OSTI2014

Representation of the Solar Capacity Value in the ReEDS Capacity Expansion Model: Preprint

An important emerging issue is the estimation of renewables' contributions to reliably meeting system demand, or their capacity value. While the capacity value of thermal generation can be estimated easily, assessment of wind and solar requires a more nuanced approach due to resource variability. Reliability-based methods, particularly, effective load-carrying capacity (ELCC), are considered to be the most robust techniques for addressing this resource variability. The Regional Energy Deployment System (ReEDS) capacity expansion model and other long-term electricity capacity planning models require an approach to estimating CV for generalized PV and system configurations with low computational and data requirements. In this paper we validate treatment of solar photovoltaic (PV) capacity value by ReEDS capacity expansion model by comparing model results to literature for a range of energy penetration levels. Results from the ReEDS model are found to compare well with both comparisons--despite not being resolved at an hourly scale.

14 SOLAR ENERGY↗