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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Airport and Heliport Setbacks

This dataset represents a first-order quantification of airport and heliport setback requirements based on the Federal Aviation Administration (FAA) 14 CFR Part 77.9. It defines the following FAA notice criteria that we use to create runway buffers. Runways longer than 3,200 feet receive a 20,000 foot buffer, runways less than 3,200 feet long receive a buffer of 10,000 feet, and heliports receive a buffer of 5,000 feet. A setback requirement is a minimum distance from an airport or heliport that an energy project may be developed. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

airport↗
DOE OSTI2024

Agrivoltaic system design tools for managing trade-offs between energy production, crop productivity and water consumption

Abstract Agrivoltaic systems that locate crop production and photovoltaic energy generation on the same land have the potential to aid the transition to renewable energy by reducing the competition between food, habitat, and energy needs for land while reducing irrigation requirements. Experimental efforts to date have not adequately developed an understanding of the interaction among local climate, array design and crop selection sufficient to manage trade-offs in system design. This study simulates the energy production, crop productivity and water consumption impacts of agrivoltaic array design choices in arid and semi-arid environments in the Southwestern region of the United States. Using the Penman–Monteith evapotranspiration model, we predict agrivoltaics can reduce crop water consumption by 30%–40% of the array coverage level, depending on local climate. A crop model simulating productivity based on both light level and temperature identifies afternoon shading provided by agrivoltaic arrays as potentially beneficial for shade tolerant plants in hot, dry settings. At the locations considered, several designs and crop combinations exceed land equivalence ratio values of 2, indicating a doubling of the output per acre for the land resource. These results highlight key design axes for agrivoltaic systems and point to a decision support tool for their development.

Environmental Sciences & Ecology↗
DOE OSTI2023

Blind photovoltaic modeling intercomparison: A multidimensional data analysis and lessons learned

The Photovoltaic (PV) Performance Modeling Collaborative (PVPMC) organized a blind PV performance modeling intercomparison to allow PV modelers to blindly test their models and modeling ability against real system data. Measured weather and irradiance data were provided along with detailed descriptions of PV systems from two locations (Albuquerque, New Mexico, USA, and Roskilde, Denmark). Participants were asked to simulate the plane-of-array irradiance, module temperature, and DC power output from six systems and submit their results to Sandia for processing. The results showed overall median mean bias (i.e., the average error per participant) of 0.6% in annual irradiation and –3.3% in annual energy yield. While most PV performance modeling results seem to exhibit higher precision and accuracy as compared to an earlier blind PV modeling study in 2010, human errors, modeling skills, and derates were found to still cause significant errors in the estimates.

14 SOLAR ENERGY↗
DOE OSTI2024

Low-cost Manufacturing of Semitransparent CdTe PV for Building Integration

Solar has been demonstrated to be a robust renewable energy source, constituting a significant portion of the United States’ renewable energy portfolio. Despite its growth across residential, commercial, and utility sectors over the past decades, it remains a small fraction of the overall energy infrastructure. Challenges persist in fully harnessing solar power to meet the nation's escalating energy demands. Among these challenges lies the hurdle of efficiently distributing large quantities of solar-generated electricity to densely populated regions with the highest energy needs and costs. Traditional utility-scale arrays demand extensive land, a luxury often unavailable in metropolitan areas. Consequently, installations must be situated at a distance, necessitating additional infrastructure for electricity transmission to service areas. While metropolitan landscapes lack sprawling open spaces suitable for conventional utility-scale solar deployment, they offer a different resource: windows. Semitransparent photovoltaic window technology has the potential to not only bolster the grid's energy capacity, but to also provide HVAC and economic advantages to building owners. However, commercial availability of building-integrated photovoltaic windows remains limited. Silicon based photovoltaics currently dominate the solar market but adapting them for use in windows poses a variety of engineering and economic challenges such as relatively low power density, high costs associated with custom manufacturing, and aesthetic considerations. Addressing these challenges, this project explored the use of laser ablation patterning to manufacture cost-effective, high-efficiency, semitransparent Cadmium Telluride photovoltaic modules. Results showcased the potential of this methodology in developing photovoltaic windows and other innovative semitransparent PV applications. The ablation manufacturing technique demonstrated great versatility in achieving different patterns and levels of visible light transmission, and the power loss due to ablation was nearly directly proportional to the amount of material removed. Furthermore, the manufacturing process for Cadmium Telluride modules already has established advantages in material and energy efficiency, and the conversion of a standard submodule to semitransparent essentially requires a single additional process step, ensuring scalability. It is important to note that during this work, Toledo Solar experienced substantial organizational upheaval stemming from a lawsuit with First Solar. An external investigation led the board of directors to remove and replace the previous management team, and several other members of the staff elected to depart as well, including the then acting Principle Investigator on this project. The remaining Toledo Solar team attempted to recover from the disruption and deliver on the remaining tasks, but upon its own review, the Department of Energy ruled the project in default and terminated the contract in December 2023.

14 SOLAR ENERGY↗
DOE OSTI2024

Performance Assessment of Photovoltaic Panels Using Impedance Spectroscopy

The goal of this project was to develop a technique for measuring internal characteristics of a PV module using light modulation under a fixed voltage bias while measuring the resulting alternating current. This technique, light-intensity modulated impedance spectroscopy (LIMIS), has the promise of detecting early signs of panel aging and degradation that could be used for example by solar farm operators to have early warnings to repair or replace panels to maintain reliability of the overall PV array. LIMIS would be complementary with the previously developed electrochemical impedance spectroscopy (EIS), which uses an alternating voltage applied electrically to a solar cell with a similar alternating current measurement. EIS has mostly been developed for individual PV cells rather than whole modules. The project was intended to assess what different information could be revealed by LIMIS, which may in some cases be more scalable to larger modules and potentially more practical to apply in field measurements without needing to electrically disconnect PV modules. We began with small 10 W PV modules and built a testbed capable of oscillating the light intensity with frequencies up to 50 kHz. In parallel, we built a large testbed for testing large 250 W PV modules. Meanwhile, we developed procedures for established measurement techniques: current–voltage (I–V), EIS, and electroluminescence (EL) imaging, where panels are subjected to forward bias while their infrared emission is recorded using a camera modified to be sensitive to IR wavelengths. In addition, we developed protocols for accelerated aging of PV modules in two ways. Thermal cycling from –40°C to +90°C simulates the diurnal temperature cycles on a rooftop. Mechanical stress by dropping a 227 g ball from a height of 1 m simulates damage such as that due to hail impacts.

14 SOLAR ENERGY↗
DOE OSTI2026

PV Systems Modelling with Python

PVSC tutorial demonstrating how to download irradiance data and sun position for a specific location, determine the orientation of a single-axis tracker system, calculate Plane of Array irradiance, and estimate the power output of a PV system.

14 SOLAR ENERGY↗
DOE OSTI2021

Cost Analysis of Annual and Monthly Net Zero Energy Performance for Multifamily Buildings in the United States

As the United States continues its progress toward sustainable construction, net zero building design is becoming an increasingly important and popular topic. Two definitions of net zero energy performance, monthly and annual, provide different levels of energy autonomy and efficiency within a building. This article analyzes the viability and incremental cost for two-, three-, and four-story multifamily apartment buildings to reach both annual and monthly net zero energy performance throughout four climate zones in the United States using baseline reference buildings that represent current construction practices. Building size plays a large role in determining the capability for a building model to reach annual or monthly net zero. Two-story buildings are capable of reaching annual net zero with an increase in construction cost of about 4.4–5.6%. Three-story buildings in warmer climates can achieve annual net zero with an increase of about 5.1%, but models in colder climates cannot reach annual net zero performance. Four-story buildings cannot achieve net zero, owing to insufficient building area for solar arrays to produce electricity. Monthly net zero energy performance was significantly harder to achieve, with the only case reaching this goal being the two-story Houston based model, at an added cost of 8.2%. Generally speaking, only small buildings in warm climates will be able to achieve monthly net zero without vastly oversizing photovoltaic systems and increasing costs without adequate payback.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Maximizing Yield with Improved Single-Axis Backtracking on Cross-Axis Slopes: Preprint

Many tracking PV systems avoid row-to-row shading by backtracking in morning and afternoon. Because the common single-axis backtracking implementation assumes the array is in a horizontal plane, it does not fully prevent row-to-row shading in arrays installed on cross-axis slopes. This paper simulates the effect of reduced self-shading on annual production with two modified backtracking strategies. Depending on the array geometry and the steepness of the cross-axis grade, using a modified backtracking strategy improved annual yield by 3-10%.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2022

Panel-Segmentation: A Python Package for Automated Solar Array Metadata Extraction Using Satellite Imagery

The NREL Python Panel-Segmentation package is a toolkit that automates the process of extracting accurate and valuable metadata related to solar array installations, using publicly available Google Maps satellite imagery. Previously published work includes automated azimuth estimation for individual solar installations in satellite images. Our continued research focuses on automated detection and classification of solar installation mounting configuration (tracking or fixed-tilt; rooftop, ground, or carport). Specifically, a Faster-RCNN Resnet-50 feature pyramid network (FPN) model was trained and validated on 862 manually labeled satellite images. This model was used to perform object detection on satellite imagery, locating and classifying individual solar installations' mounting configuration and type. Model results showed a mean average precision score (mAP) of 77.79%, with the model strongest at detecting fixed-tilt ground mount and fixed-tilt carport installations. The object detection model and its outputs have been incorporated into the Panel-Segmentation package's automated metadata extraction pipeline, which returns the mounting configuration and azimuth for individual solar arrays in satellite imagery. The complete image data set with labels has been released on the U.S. Department of Energy (DOE) DuraMAT DataHub, to encourage further research in this area.

deep learning↗
DOE OSTI2022

OPALCO - Decatur Island Solar and Energy Storage Project: An Assessment of Battery Technical Performance

Orcas Power & Light Cooperative (OPALCO) is a member-owned, nonprofit cooperative utility that provides energy services to approximately 11,200 customers across 20 islands in San Juan County, Washington. OPALCO’s mostly hydroelectric power is generated by Bonneville Power Administration and delivered to the islands by submarine cables. In 2016, as part of the second round of funding from the Washington state Clean Energy Fund, OPALCO received a $1 million matching grant to support a project that deployed a 504-kW LG community photovoltaic (PV) system in combination with a 1 MW/2 MWh lithium-iron-phosphate battery energy storage system (BESS) on Decatur Island, Washington. The Decatur Island Substation is essential to ensuring reliable energy for the residents of the San Juan Islands as it is the point of interconnection with the mainland transmission system. The BESS, in combination with the community solar array, will deliver an innovative method to both defer the costly upgrade of the transmission system and allow for other high-value applications intended to benefit the utility and its customers. In 2018, Pacific Northwest National Laboratory (PNNL) completed a preliminary economic assessment for several identified use cases in collaboration with OPALCO. Between August 2021 and May 2022, extensive testing was conducted, and the results were used to assess the technical performance of the BESS subjected to actual field operations. Both reference performance and use case tests were performed: (a) Reference performance tests assess the general technical capabilities of the BESS, such as energy capacity, round-trip efficiency (RTE), ramp rate, and signal tracking capability. These are the first tests performed (baseline) and are repeated after use case tests (post cycle). A standardized U.S. Department of Energy (DOE) energy storage performance protocol was used to characterize the BESS, including representative duty cycle profiles, test procedure guidance, and calculation guidance for determining key characteristics. (b) Use case tests examine the performance of the BESS for specific use cases using duty cycles developed by PNNL in collaboration with OPALCO. Four use cases were selected for testing: 1) demand charge reduction, 2) load shaping, 3) outage mitigation, and 4) transmission deferral. The use case duty cycles were developed based on utility and site-specific characteristics in addition to the technical characteristics and physical capabilities of the BESS. Use case tests were performed between the baseline and post cycle tests. This report describes the BESS and its components, presents testing and performance analysis results, and shares key insights and lessons learned from this project. Outcomes of the tests and analyses will help OPALCO understand the performance of the Decatur Island BESS in its current state and design appropriate operational strategies for this and other BESSs over the long term.

14 SOLAR ENERGY↗
DOE OSTI2021

Solar Transposition Modeling via Deep Neural Networks With Sky Images

This article presents a notable advance toward the development of a new method of increasing the single-axis tracking photovoltaic (PV) system power output by improving the determination and near-term prediction of the optimum module tilt angle. The tilt angle of the plane receiving the greatest total irradiance changes with Sun position and atmospheric conditions including cloud formation and movement, aerosols, and particulate loading, as well as varying albedo within a module's field of view. In this article, we present a multi-input convolutional neural network that can create a profile of plane-of-array irradiance versus surface tilt angle over a full 180° arc from horizon to horizon. As input, the neural network uses the calculated solar position and clear-sky irradiance values, along with sky images. The target irradiance values are provided by the multiplanar irradiance sensor (MPIS). In order to account for varying irradiance conditions, the MPIS signal is normalized by the theoretical clear-sky global horizontal irradiance. Using this information, the neural network outputs an N -dimensional vector, where N is the number of points to approximate the MPIS curve via Fourier resampling. The output vector of the model is smoothed with a Gaussian kernel to account for error in the downsamping and subsequent upsampling steps, as well as to smooth the unconstrained output of the model. Furthermore, these profiles may be used to perform near-term prediction of angular irradiance, which can then inform the movement of a PV tracker.

42 ENGINEERING↗
DOE OSTI2024

Quantifying spectral albedo effects on bifacial photovoltaic module measurements and system model predictions

We provide a comprehensive analysis of the effect of spectral albedo on photovoltaic (PV) module measurements and system model predictions. We demonstrate how to account for albedo in indoor bifacial device measurements by adjusting the applied irradiance using the scaled rear irradiance method, exemplified on fabricated silicon heterojunction (SHJ) modules. System model performance is studied using a detailed 3D finite-element model, DUET, for fixed-tilt and horizontal single-axis tracked (SAT) arrays between 15 and 75°N. Spectral effects cause variations in measured SHJ module short-circuit current up to 2% and efficiency variation up to 0.3% abs. We further demonstrate that rear-side spectral mismatch factors (SMMs) resulting from including or omitting spectral albedo in PV system modeling vary between ±13%, while total (front+rear) SMMs vary up to 3%, depending on the deployment configuration and latitude. SAT array SMMs are weakly correlated with latitude, while fixed-tilt array SMMs increase with latitude, driven by an increasing proportion of ground-reflected light on the front-side of modules. Ground-reflections can constitute between 2% and 32% of total incident module irradiance, with notably high (>10%) contributions for fixed-tilt arrays at high latitude. Effects of spectral albedo are most significant for: (1) fixed-tilt deployments at high latitudes, (2) wide bandgap technologies such as perovskite and cadmium telluride cells, (3) albedos which vary steeply over the technology's absorption range, and (4) high albedo ground covers. Overall, we demonstrate that omitting spectral albedo effects can result in PV measurement and system-level modeling uncertainties on the order of several percent in these cases.

14 SOLAR ENERGY↗
DOE OSTI2022

What Would It Take to Manufacture Perovskite Solar Cells in Space?

Imagine: Astronauts land on the moon. They verify their arrival with mission control and perform system checks and validations. After the dust settles, they open the airlock of the landing vehicle and venture outside. A side hatch opens, and a flexible substrate slowly unfurls on a boom. A series of printer heads raster, hovering over the substrate and sequentially vapor-depositing the constituent layers of a perovskite solar module. In time, a 1-megawatt array has been manufactured on the moon and can now be connected to supply power to the Artemis Base Camp. This ambitious vision could someday become a reality.

14 SOLAR ENERGY↗
DOE OSTI2022

bifacialVF - Bifacial PV View Factor model 2022 [SWR 17-58]

bifacialvf is a self-contained view factor (or configuration factor) model which replicates a 5-row PV system of infinite extent perpendicular to the module rows. Single-axis tracking is supported, and hourly output files based on TMY inputs are saved. Spatial nonuniformity is reported, with multiple rear-facing irradiances collected on the back of each module row. Bilinear interpolation code add-on to bifacialvf (description below) to pre-generate IV arrays and bifacial coefficients, and to examine the energy production with back side irradiance mismatch for either a portrait or landscape module. Included are IV curves and bifacial info for a Yingli (standard) module. Based on the publication: "A Practical Irradiance Model for Bifacial PV Modules" B. Marion, S. MacAlpine, C. Deline, A. Asgharzadeh, F. Toor, D. Riley, J. Stein, C. Hansen 2017 IEEE Photovoltaic Specialists Conference, Washington DC, 2017 URL: https://www.nrel.gov/docs/fy17osti/67847.pdf

Deline, Chris↗
DOE OSTI2023

Acceleration Factors for Combined‐Accelerated Stress Testing of Photovoltaic Modules

Combined‐accelerated stress testing (C‐AST) is developed to establish the durability of photovoltaic (PV) products, including for degradation modes that are not a priori known or examined in standardized tests. C‐AST aims to comprehensively represent the sample, stress factors, and their combinations using levels at the statistical tails of the natural environment. Acceleration factors for relevant climate sequences within the C‐AST cycle with respect to the Florida USA climate are estimated for selected degradation mechanisms. It is found that for degradation of the outer backsheet polymer layer, the acceleration factor of the tropical climate sequence (the longest of the climate sequences) is f ( T , G ) = 17.3 with ultraviolet photodegradation; for polyethylene terephthalate hydrolysis (backsheets), f ( T , RH ) = 426; for electrochemical corrosion (PV cell), f ( I ) = 14.1; and for PbSn solder fatigue f (Δ T , r ( T )) = 17.3. Here, T is the module temperature, G is the broadband spectrum irradiance on the plane of array of the module, RH is the relative humidity on the module surface, I is the leakage current through the module packaging, and r ( T ), the number of temperature reversals. The methods discussed herein are generally applicable for evaluating acceleration factors in other accelerated test methods.

14 SOLAR ENERGY↗
DOE OSTI2021

High-Fidelity Models and Fast EMT Simulation Algorithms for Isolated Multi-port Autonomous Reconfigurable Solar power plant (MARS)

The integration of hybrid photovoltaic (PV) and energy storage system (ESS) based plants has become a promising way of solving the intermittency of PV plants and providing frequency support to the power grid. The multi-port autonomous reconfigurable solar power plant (MARS) can integrate the PV systems and ESSs to an ac grid and dc lines. The proposed isolated MARS incorporates an isolated converter that connects to the PV arrays and is based on the dual active bridge (DAB) converter. The high frequency switching in the DAB and the means to control the DAB converter using delays between switching signals lead to the need for a small timestep in simulations. Moreover, several hundreds of modules that include a DAB converter are present in the MARS. The small timestep and the presence of several hundreds of modules lead to a significant rise in the overall simulation time. To address this issue, simulation algorithms like numerical stiffness-based hybrid discretization and the hysteresis relaxation technique are applied to the switched system model of isolated MARS. Additionally, an event-driven interpolating method is introduced to help increase the minimum timestep to simulate the conventional DAB converter model while maintaining high accuracy in the simulation results. The developed model is validated by comparison with its reference model built in the PSCAD/EMTDC and MATLAB software environments using library components.

Xia, Qian↗
DOE OSTI2025

Advanced Photovoltaic Module Characterization: Using Image Transformers for Current–Voltage Curve Prediction From Electroluminescence Images

Individual photovoltaic (PV) module health monitoring can be a daunting task for operation and maintenance of solar farms. Modules can be inspected through luminescence, thermal imaging, and current–voltage (I–V) curve analyzes for identification of damage and power loss. I–V curves provide easily interpretable data to determine module health as they directly provide electrical performance metrics. However, in order to obtain these curves, modules must be disconnected from the array and either removed to a solar simulator or characterized in situ with corrections for module temperature, the incident solar spectrum, and intensity. Luminescence or thermal images of a module are relatively easy to acquire in situ. Electroluminescence (EL) images highlight physical defects in the modules but do not provide easily interpretable features to correlate with electrical performance. This work presents a SWin transformer network to predict I–V curves for PV modules from their corresponding EL images. The predicted I–V curves allow the accurate prediction of the maximum power point (MPP), short-circuit current I sc , and open-circuit voltage V oc with a mean error less of than 1%. Comparing single diode model (SDM) parameters extracted from the predicted curves to those extracted from the true curves, the series resistance R s demonstrates a mean error of 5.19%, and the photocurrent I a mean error of 0.197%. The shunt resistance R sh and dark current Io parameters are predicted with larger errors because of their sensitivity to small changes in the I–V curve.

Byford, Brandon K. [New Mexico State Univ., Las Cr↗
DOE OSTI2021

2021 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

Starting in 2015 NREL has presented the Annual Technology Baseline (ATB) in an Excel workbook that contains detailed cost and performance data, both current and projected, for renewable and conventional technologies. The workbook includes a spreadsheet for each technology. This version of the workbook provides the final updates to data for the 2021 ATB. In 2019 and 2020, NREL has also provided selected data in Tableau workbooks and structured summary csv files. The data for 2015 - 2020 is located on https://data.nrel.gov. In 2021 and going forward, the data is cloud optimized and provided in the OEDI data lake. A website documents this and future data at https://atb.nrel.gov.

Array↗