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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

IMoFi (Intelligent Model Fidelity): Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration Updated Accomplishments

This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO), including some updates from the previous report SAND2022-0215, to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.

14 SOLAR ENERGY↗
DOE OSTI2020

Task 12 PV Sustainability - Life Cycle Inventories and Life Cycle Assessments of Photovoltaic Systems

Life Cycle Assessment (LCA) is a structured, comprehensive method of quantifying material- and energy-flows and their associated impacts in the life cycles of products (i.e., goods and services). One of the major goals of IEA PVPS Task 12 is to provide guidance on assuring consistency, balance, transparency and quality of LCA to enhance the credibility and reliability of the results. The current report presents the latest consensus life cycle inventories among the authors, PV LCA experts in North America, Europe, Asia and Australia. At this time consensus is limited to four technologies for which there are well-established and up-to-date life cycle inventory (LCI) data (mono- and multi-crystalline Si, CdTe, CIGS, as well as one emerging technology (perovskite silicon tandem). LCIs are necessary for LCA and the availability of such data is often the greatest barrier for conducting LCA. The Task 12 LCA experts have put great efforts in gathering and compiling the LCI data presented in this report. These include detailed inputs and outputs during manufacturing of cell, wafer, module, and balance-of-system (i.e., structural and electrical components) that were estimated from actual production and operation facilities. In addition, data are presented to enable analyses of various types of PV installations; these include operational data of rooftop and ground-mount PV systems and country-specific PV-mixes. The LCI datasets presented in this report are the latest that are available to the public describing the status in 2018 for crystalline Si (some manufacturing data from 2011 were not updated), 2015 and 2017-2018 for CdTe, 2010 for CIGS, 2010 for HCPV, and 2017 for perovskite silicon tandem technology.

14 SOLAR ENERGY↗
DOE OSTI2024

PV Lifetime Project (2024 NREL Annual Report)

DOE’s PV Lifetime project was initiated in 2016 with the goal of accurately characterizing the early-life evolution of photovoltaic (PV) field performance. Different PV cell and module technologies result in different initial degradation rates due to effects like light-induced degradation (LID) and light & elevated temperature-induced degradation (LeTID). To accurately characterize the initial field degradation of maximum power (Pmp) requires the use of high-accuracy indoor IV curve measurements at standard test conditions. Therefore, PV modules involved in this study are removed from the field once or twice per year and brought indoors for measurement under constant temperature and irradiance conditions.

14 SOLAR ENERGY↗
DOE OSTI2026

Fundamentals of Solar PV Bolted Joint Loosening and Prevention

The photovoltaic (PV) industry has long reported anecdotal accounts of systems exhibiting intermittent or chronic fastener loosening, including joints that fail to maintain preload despite multiple re-tightening attempts. These occurrences are frequently, and often incorrectly, attributed to installer errors, vibration, or loading beyond design expectations (e.g., extreme weather events). Loose fasteners have serious implications and can significantly impact solar PV systems’ performance, reliability, and safety. However, effective bolted joint design and proper assembly practices can mitigate or eliminate loosening. Until the US Department of Energy’s Solar Energy Technologies Office (SETO) funded research on fasteners and solar PV structures, there was a notable gap in understanding the causes of loosening in solar PV systems.

14 SOLAR ENERGY↗
DOE OSTI2026

Annual Supply Chain for Photovoltaics (ASC-PV) in the United States: 2024 in Review

This report analyzes U.S. PV and BESS supply chains and costs in 2024, for PV module and battery technologies, structural and electrical balance of system (BOS) components, as well as PV recycling. The report concludes with an analysis of technology installation trends, government support for domestic manufacturing, manufacturing jobs, and the domestic content of PV systems installed in the United States in 2024.

14 SOLAR ENERGY↗
DOE OSTI2026

PV Operations Software Transparency: A PVMAC Industry Snapshot

The rapid growth of photovoltaic (PV) deployment has increased reliance on software platforms for monitoring, workflow automation, diagnostics, and performance analytics. As these tools play a central role in asset management and operations and maintenance (O&M), greater transparency in methodologies, data handling, and validation practices benefits the broader PV ecosystem. To better understand current practices and identify opportunities for improved clarity and interoperability, 24 software providers contributed detailed responses through the PV O&M Analytics Collaborative (PVMAC) initiative, the first structured questionnaire of its kind in the industry, covering onboarding, interoperability, data quality, diagnostics, AI/ML, and other operational categories. These providers represent over 1.1 TW of solar assets under management. The analysis shows broad adoption of digital twins, AI/ML, and API integrations, but also highlights challenges in onboarding processes, inconsistent definitions and methodologies, variability in key performance indicator (KPI) calculations, and limited independent validation. Greater standardization, clearer documentation, and stronger validation frameworks could improve transparency, comparability, and trust across PV operations software platforms.

14 SOLAR ENERGY↗
DOE OSTI2026

Education for PV Modeling Professionals: Survey of Educators

We report a survey of instructors at universities offering courses that address PV performance modeling. We confirm our earlier finding that most courses lack the level of detail sought by the professional community. We recommend that the PV Performance Modeling Collaborative (PVPMC), or a university, sponsor a committee to produce a curriculum outline for PV system performance modeling, and that the PVPMC solicit industry for well-documented examples of PV system designs and accompany

Hansen, Clifford [Sandia National Laboratories (SN↗
DOE OSTI2023

PV Module Operating Temperature - Data and Resources

The Photovoltaic Systems Evaluation Laboratory (PSEL) at Sandia National Laboratories (SNL) in Albuquerque, NM has an extensive test site where PV modules and other system components are deployed and monitored for testing and evaluation. For this dataset PV Performance Labs has assembled one year of measurements from the Systems Long-Term Evaluation (SLTE) project (formerly known as PV Lifetime) providing the main variables needed to investigate and validate PV module operating temperature models: irradiance, ambient temperature, wind speed and back-of-module temperature. For use with more advanced thermal modeling, an estimate of down-welling long-wave radiation is also included.

14 SOLAR ENERGY↗
DOE OSTI2023

Digital Twin Empowered PV Power Prediction

The accurate prediction of photovoltaic (PV) power generation is significant to ensure the economic and safe operation of power systems. To this end, the paper proposes a new digital twin (DT) empowered PV power prediction framework that is capable of ensuring reliable data transmission and employing the DT to achieve high accuracy of power prediction. With this framework, considering potential data contamination in the collected PV data, a generative adversarial network is employed to restore the historical data set, which offers a prerequisite to ensure accurate mapping from the physical space to the digital space. Further, a new DT empowered PV power prediction method is proposed. Therein, we model a DT that encompasses a digital physical model for reflecting the physical operation mechanism and a neural network model (i.e., a parallel network of convolution and bidirectional long-short-term memory model) for capturing the hidden spatial-temporal features. The proposed method enables the use of the DT to take advantages of the digital physical model and the neural network model, resulting in enhanced prediction accuracy. Finally, a real data set is conducted to access the effectiveness of the proposed method.

14 SOLAR ENERGY↗
NASA NTRS1983

Evolution of integrated panel structural design and interfaces for PV power plants

The evolution of integrated photovoltaic (PV) panel design at ARCO Solar is discussed. Historically, framed PV modules of about 1 x 4-ft size were individually mounted in the field on fixed support structures and interconnected electrically with cables to build higher-power arrays. When ARCO Solar saw the opportunity in 1982 to marry its PV modules with state-of-the-art heliostat trackers developed by ARCO Power Systems, it became obvious that mounting individual modules was impractical. For this project, the framed modules were factory-assembled into panels and interconnected with cables before being mounted on the trackers. Since then, ARCO Solar made considerable progress and gained substantial experience in the design and fabrication of large PV panels. Constraints and criteria considered in these design activities included static and dynamic loads; assembly and transportation equipment and logistics, structural and electrical interfaces, and safety and grounding concerns.

Arnett, J. C.↗
NASA NTRS1989

Space shuttle Production Verification Motor 1 (PV-1) static fire

All inspection and instrumentation data indicate that the PV-1 static test firing conducted 18 Aug. 1988 was successful. With the exception of the intentionally flawed joints and static test modifications, PV-1 was flight configuration. Fail-safe flaws guaranteeing pressure to test the sealing capability of primary O-rings were included in the aft field joint, case-to-nozzle joint, and nozzle internal Joint 5. The test was conducted at ambient conditions, with the exception of the field joints and case/nozzle joints which were maintained at a minimum of 75 F. Ballistics performance values were within specification requirements. The PV-1 motor exhibited chamber pressure oscillations similar to previously tested Space Shuttle redesigned solid rocket motors, particularly QM-7. The first longitudinal mode oscillations experienced by PV-1 were the strongest ever measured in a Space Shuttle motor. Investigation into this observation is being conducted. Joint insulation performed as designed with no evidence of gas flow within unflawed forward field joints. The intentionally flawed center and aft case field joint insulation performance was excellent. There was no evidence of hot gas past the center field joint capture feature O-ring, the case-to-nozzle joint primary O-ring, or the aft field joint primary O-ring. O-ring seals and barriers with assured pressure at the flaws showed erosion and heat effect, but all sealed against passage of hot gases with the exception of the aft field joint capture feature O-ring. There was no evidence of erosion, heat effect, or blowby on any O-ring seals or barriers at the unflawed joints. Nozzle performance was nominal with typical erosion. Post-test examination revealed that the forward nose ring was of the old high performance motor design configuration with the 150-deg ply angle. All nozzle components remained intact for post-test evaluation. The thrust vector control system operated correctly. The water deluge system, CO2 quench, and other test equipment performed as planned during all required test operations.

Source record↗
NASA NTRS2000

PV Theories For Planetary Atmospheric Circulations

Potential vorticity (or PV) has become an important tool for the diagnosis and modeling of the Earth's atmospheric and oceanic circulations. More recently, the application of PV thinking to numerical simulations and spacecraft observations of other atmospheres, including those of Mars, Venus, and Titan, has encouraged the hope for a unified understanding of planetary circulation regimes encompassing a wide range of rotation, stratification, and forcing parameters. Specifically, the accumulated evidence suggests that zonal-mean winds and temperatures at upper tropospheric levels approximate a state of zero potential vorticity within the bounding latitudes of the westerly jets, while the poleward regions of cyclonic shear conform to a PV state that is well mixed with respect to its polar limit. This review of the prospects for conceptual planetary circulation models will explore the possibility that the zonal-mean state of an atmosphere can be calculated in terms of a simple link between the latitudinal PV and potential temperature variation at an upper baroclinic steering level.

Allison, Michael↗
DOE OSTI2017

Studying the Impact of Distributed Solar PV on Power Systems using Integrated Transmission and Distribution Models: Preprint

This paper presents the results of a distributed solar PV impact assessment study that was performed using a synthetic integrated transmission (T) and distribution (D) model. The primary objective of the study was to present a new approach for distributed solar PV impact assessment, where along with detailed models of transmission and distribution networks, consumer loads were modeled using the physics of end-use equipment, and distributed solar PV was geographically dispersed and connected to the secondary distribution networks. The highlights of the study results were (i) increase in the Area Control Error (ACE) at high penetration levels of distributed solar PV; and (ii) differences in distribution voltages profiles and voltage regulator operations between integrated T&D and distribution only simulations.

14 SOLAR ENERGY↗
DOE OSTI2018

Finite Element Simulation of Mixed-Mode PV Encapsulant Delamination Based on Cohesive Zone Model: Preprint

A finite element model (FEM) was developed to simulate the mixed-mode delamination failure at the encapsulant interface within PV modules under mixed-mode loading condi- tions. Parameters to characterize the bilinear traction-separation constitutive behavior of cohesive elements were determined by testing the pure mode I critical fracture energy of the photovotaic(PV) cell interface using the width-tapered beam and fitting the simulated load-displacement curve with the tested curve. This developed FEM can be used to predict the critical temperature changes, at which delamination would initiate, of PV modules with different sizes and provide guidance for the design of PV module with better reliability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Optimal Sizing of an Electric Vehicle Charging Station with Integration of PV and Energy Storage

This paper proposes an optimization model for the optimal configuration of an grid-connected electric vehicle (EV) extreme fast charging station considering integration of photovoltaic (PV) and energy storage. The proposed model minimizes the annualized net cost (i.e., maximizes the annualized net profit) of the extreme fast charging station, including investment and maintenance cost of charging ports, PV and energy storage, net cost of purchasing energy from utility and selling energy to EV customers, degradation cost of energy storage and demand charge. The decision variables are number of charging ports, capacity of invested PV and the power and energy ratings of invested energy storage. The Erlang-loss system is adopted to model the EV mobility. Results of numerical simulations indicate that investment of PV and energy storage could increase the annualized profit of the extreme fast charging station. In addition, the impacts of various parameters on the optimal solution are investigated by sensitivity analysis.

Liu, Guodong↗
DOE OSTI2022

Phase Identification in Real Distribution Networks with High PV Penetration Using Advanced Metering Infrastructure Data: Preprint

Many distribution network monitoring and control applications - including state estimation, volt/VAR optimization, and network reconfiguration - rely on accurate network models; however, the network models maintained by utilities can become outdated because of restoration activities, network reconfiguration, and missing data. With the widespread deployment of advanced metering infrastructure (AMI), abundant measurement data from low-voltage secondary networks are available. The AMI measurement data can be used for phase identification to improve the network models. Although the existing phase identification techniques work well in passive distribution feeders that do not have photovoltaic (PV) generation, they can fail to accurately identify the phases in the presence of PV. This paper proposes a robust phase identification algorithm based on supervised machine learning that accurately identifies the AMI meter phase connectivity in the presence of significant PV generation. The proposed algorithm does not require network topology information or feeder head measurement data. The algorithm is validated using the AMI measurement data collected in the field and the field-validated phase connectivity database on two real distribution feeders from San Diego Gas & Electric Company that have significant PV generation.

advanced metering infrastructure↗
DOE OSTI2022

Phase Identification in Real Distribution Networks with High PV Penetration Using Advanced Metering Infrastructure Data

Many distribution network monitoring and control applications - including state estimation, Volt/VAr optimization, and network reconfiguration - rely on accurate network models; however, the network models maintained by utilities can become outdated because of restoration activities, network reconfiguration, and missing data. With the widespread deployment of advanced metering infrastructure (AMI), abundant measurement data from low-voltage secondary networks are available. The AMI measurement data can be used for phase identification to improve the network models. Although the existing phase identification techniques work well in passive distribution feeders that do not have photovoltaic (PV) generation, they can fail to accurately identify the phases in the presence of PV. This paper proposes a robust phase identification algorithm based on supervised machine learning that accurately identifies the AMI meter phase connectivity in the presence of significant PV generation. The proposed algorithm does not require network topology information or feeder-head measurement data. The algorithm is validated using the AMI measurement data collected in the field and the field-validated phase connectivity database on two real distribution feeders from San Diego Gas & Electric Company that have significant PV generation.

advanced metering infrastructure (AMI)↗
DOE OSTI2022

Automated Shift Detection in Sensor-Based PV Power and Irradiance Time Series

PV power and irradiance sensor-based measurements are prone to error, resulting in issues such as abrupt time series data shifts. These shifts, which are usually unintentional, may be caused by software or hardware configuration changes on a PV system, and do not reflect an actual change in overall system performance. Locating these shifts and segmenting the associated time series aids in more accurate future PV analysis. In this research, an offline changepoint detection (CPD) algorithm that automatically detects these abrupt data shifts in sensor-based time series is introduced. Data shift periods in 101 daily PV power and irradiance time series were labeled manually by two solar experts. These data streams represent sensor-based measurements, and display a variety of data shift behaviors. A changepoint detection algorithm was tuned using the 101 labeled data streams, with each model configuration's ability to detect labeled changepoints benchmarked using metrics such as F1-score, recall, and Rand Index. Best performing models on seasonality-corrected data streams include the Pruned Exact Linear (PELT) method, the Binary Segmentation method, and the Bottom-Up method, all scoring an average F1-score of 0.76 or greater at detecting labeled changepoints within a 30-day window for the labeled data sets. To promote further research in this space, we are releasing the labeled data shift sets on U.S. Department of Energy's (DOE) DuraMAT Data Hub, and the associated algorithm in the Python PVAnalytics package.

changepoint detection↗