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At least 937 records · Page 52

Evaluation of Models and Measurements to Estimate Solar Radiation for 1-Axis Tracking Modules at NREL’s SRRL

Solar radiation reaching photovoltaic (PV) modules on a 1-axis tracking system can be measured by reference cells or thermopiles. The former is often biased due to the reflection of solar radiation by the glass cover of the PV. The uncertainty can be moderated by applying a correction factor, as a function of solar incident angle and the refractive index of the glass, to the measurement. On the other hand, solar radiation on the inclined PV panels can be computed by transposition models using global horizontal irradiance (GHI) observations from thermopiles. This study examines the models and measurements to estimate solar radiation for 1-axis tracking modules at the National Renewable Energy Laboratory’s (NREL’s) Solar Radiation Research Laboratory (SRRL). The 1-minute plane-of-array (POA) irradiances from 2019 are computed using the observed GHIs and a transposition model developed by Perez et al. The POA irradiances are compared with the observation by an IMT reference cell and a Kipp & Zonen CM Pyranometer 22 (CMP22) thermopile. For the SRRL’s 1-axis tracking system with an annual solar energy of 2323.9 kWh/m 2 , the POA irradiance is overestimated by ~70 kWh/m 2 using the transposition model. This bias is reduced by more than 50% using the IMT measurements calibrated by a correction factor for a PV surface of antireflection coated glass.

POA irradiance↗

Quantifying Uncertainty in PV Energy Estimates Final Report

Uncertainty in PV energy estimates is "one of the most critical areas of lack of understanding" according to independent engineers, financiers, PV model developers, and other industry stakeholders. The primary problem is a lack of rigorous, transparent, widely accepted methods for quantifying uncertainty in energy production estimates. Uncertainty in energy production estimates arises from variability of the solar resource, inexact PV performance models and their parameters, and system reliability considerations. Uncertainty in annual energy production is frequently calculated for larger projects in order to quantify financial risk. Key statistics for energy, such as the P-values "P50" and "P90" (the annual energy values that are exceeded in future years with 50\% and 90\% probability, respectively) are used by financing institutions to calculate the repayment risk for the project. The current methods to estimate these statistics are typically proprietary, specialized, and involve significant post-processing of commercial performance model results. This black-box approach leads to inconsistent P-value estimates from different parties, which reduces investors' confidence in the results. Since the financial community bases its risk assessment on these estimates, reduced confidence increases perceived project risk, and consequently financing costs. The goal of this project was to establish a set of best practices for quantifying uncertainty in energy production estimates, including identifying what sources of uncertainty must be considered with clear definitions and metrics, determining which sources are the biggest drivers of uncertainty, and providing a computationally efficient framework for combining different sources of uncertainty that is flexible enough to accommodate substitutions of data or methods when better information is available. We engaged a wide set of stakeholders to ensure industry endorsement and adoption, and leveraged complementary projects investigating individual sources of uncertainty in great detail, as well as others' work that started down this path.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

Space Environment Testing of Photovoltaic Array Systems at NASA's Marshall Space Flight Center

To successfully operate a photovoltaic (PV) array system in space requires planning and testing to account for the effects of the space environment. It is critical to understand space environment interactions not only on the PV components, but also the array substrate materials, wiring harnesses, connectors, and protection circuitry (e.g. blocking diodes). Key elements of the space environment which must be accounted for in a PV system design include: Solar Photon Radiation, Charged Particle Radiation, Plasma, and Thermal Cycling. While solar photon radiation is central to generating power in PV systems, the complete spectrum includes short wavelength ultraviolet components, which photo-ionize materials, as well as long wavelength infrared which heat materials. High energy electron radiation has been demonstrated to significantly reduce the output power of III-V type PV cells; and proton radiation damages material surfaces - often impacting coverglasses and antireflective coatings. Plasma environments influence electrostatic charging of PV array materials, and must be understood to ensure that long duration arcs do not form and potentially destroy PV cells. Thermal cycling impacts all components on a PV array by inducing stresses due to thermal expansion and contraction. Given such demanding environments, and the complexity of structures and materials that form a PV array system, mission success can only be ensured through realistic testing in the laboratory. NASA's Marshall Space Flight Center has developed a broad space environment test capability to allow PV array designers and manufacturers to verify their system's integrity and avoid costly on-orbit failures. The Marshall Space Flight Center test capabilities are available to government, commercial, and university customers. Test solutions are tailored to meet the customer's needs, and can include performance assessments, such as flash testing in the case of PV cells.

Phillips, Brandon S.↗

Solar Electric System

Heat Pipe Technology, Inc. undertook the development of a PV system that could bring solar electricity to the individual home at reasonable cost. His system employs high efficiency PV modules plus a set of polished reflectors that concentrate the solar energy and enhance the output of the modules. Dinh incorporated a sun tracking system derived from space tracking technology. It automatically follows the sun throughout the day and turns the modules so that they get maximum exposure to the solar radiation, further enhancing the system efficiency.

Source record↗

Follow-Up from the Photovoltaic Reliability Workshop (PVRW): Cost Modeling Capabilities to Evaluate Trends in PV Technologies

NREL's Solar and Storage Techno-Economic Analysis (TEA) team reviews live polling results from the Photovoltaic Reliability Workshop (PVRW) related to module technology trends believed to have the greatest reliability impacts. Then, the team reviews the publicly available tools and inputs necessary for evaluating reliability tradeoffs between initial module and system costs, degradation profiles, and levelized cost of energy (LCOE). These tools include the online Detailed Cost Analysis Models (DCAM) and the DuraMAT LCOE calculator.

cost modeling↗

DuraMAT FY 2023 Annual Report: Toward Reliability Forecasting

The Durable Module Materials Consortium (DuraMAT) launched in November 2016 with five years of funding from the U.S. Department of Energy s (DOE's) Solar Energy Technologies Office (SETO). The program renewed in 2022 for an additional 6 years. DuraMAT is a multi-lab consortium led by the National Renewable Energy Laboratory, with Sandia National Laboratories (Sandia) and Lawrence Berkeley National Laboratory (LBNL) as core research labs. DuraMAT's overarching goal is to accelerate a sustainable, just, and equitable transition to zero-carbon electricity generation by 2035. 2023 has been a wild ride in the solar industry. Photovoltaic (PV) manufacturing is coming back to the United States, and deployment is booming again. DuraMAT has a unique opportunity to support flourishing manufacturing and deployment over the next couple of years.

durable module↗

Data-Driven Model for Photovoltaic Generation: Comparison with Physical Models Using a Microgrid in Puerto Rico

Photovoltaic (PV) generation is a critical component of microgrids, but its accurate modeling is challenging due to the complex and dynamic interactions between solar irradiance, temperature, and PV system installation. This paper develops a multilayer perceptron (MLP) model that inputs solar irradiance and temperature to estimate the PV generation, and it compares the proposed data-driven model’s performance to two well-known physical models: the single-diode model and the inverter model. The results demonstrate that all the models can reach high levels of accuracy. However, the MLP model outperforms the physical models on average by 4.5 to 6.6 percent in R squared scores and 220 to 290 Watts in RMSE scores, and it does not require physical system parameters. Moreover, the data-driven model can overcome the limitations of the lack of real-time PV generation data.

R pesante colón, Marcos↗

Intermediate-phase engineering via dimethylammonium cation additive for stable perovskite solar cells

Achieving the long-term stability of perovskite solar cells is arguably the most important challenge required to enable widespread commercialization. Understanding the perovskite crystallization process and its direct impact on device stability is critical to achieving this goal. The commonly employed dimethyl-formamide/dimethyl-sulfoxide solvent preparation method results in a poor crystal quality and microstructure of the polycrystalline perovskite films. In this work, we introduce a high-temperature dimethyl-sulfoxide-free processing method that utilizes dimethylammonium chloride as an additive to control the perovskite intermediate precursor phases. By controlling the crystallization sequence, we tune the grain size, texturing, orientation (corner-up versus face-up) and crystallinity of the formamidinium (FA)/caesium (FA) y Cs 1-y Pb(I x Br 1-x )3 perovskite system. A population of encapsulated devices showed improved operational stability, with a median T80 lifetime (the time over which the device power conversion efficiency decreases to 80% of its initial value) for the steady-state power conversion efficiency of 1,190 hours, and a champion device showed a T80 of 1,410 hours, under simulated sunlight at 65 degrees C in air, under open-circuit conditions. In conclusion, this work highlights the importance of material quality in achieving the long-term operational stability of perovskite optoelectronic devices.

14 SOLAR ENERGY↗

Houston, We Have a Problem-and a Solution: Solar Performance Initiative Helps Federal Building Boost Rooftop Production

In 2014, the Mickey Leland Federal Building in Houston, Texas installed a 192 kW PV system on top of its parking structure. To monitor and optimize its performance, the General Services Administration, which manages the site, responded to the Federal Energy Management Program’s request for federal agency participation in the Federal Energy Management Program Solar PV Performance Initiative.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Field Performance of South-Facing and East-West Facing Bifacial Modules in the Arctic

This paper presents the first systematic comparison between south-facing monofacial and bifacial photovoltaic (PV) modules, as well as between south-facing bifacial and vertical east-west facing bifacial PV modules in Alaska. The state’s solar industry, driven by the high price of energy and dropping equipment costs, is quickly growing. The challenges posed by extreme sun angles in Alaska’s northern regions also present opportunities for unique system designs. Annual bifacial gains of 21% were observed between side by side south-facing monofacial and bifacial modules. Vertical east-west bifacial modules had virtually the same annual production as south-facing latitude tilt bifacial modules, but with different energy production profiles.

14 SOLAR ENERGY↗

Solar Photovoltaic Module Recycling: A Survey of U.S. Policies and Initiatives

Industry stakeholders, regulators, and policymakers in the United States are starting to develop policies for PV module recycling. Well-designed policies could reduce negative environmental impacts and resource constraints while opening new market and employment opportunities. This paper summarizes drivers, barriers, and enablers related to PV module recycling, which might be addressed via policy. It then analyzes existing and proposed U.S. policies that may affect PV module recycling. Among the global and national voluntary industry stewardship standards related to EoL PV management, this paper discusses a Solar Energy Industries Association program encouraging PV recycling among its U.S. membership. The paper concludes with a synthesis of policy-related factors that may encourage effective EoL PV module management.

14 SOLAR ENERGY↗

On-Orbit Measurement of Next Generation Space Solar Cell Technology on the International Space Station

Measurement is essential for the evaluation of new photovoltaic (PV) technology for space solar cells. NASA Glenn Research Center (GRC) is in the process of measuring several solar cells in a supplemental experiment on NASA Goddard Space Flight Center's (GSFC) Robotic Refueling Mission's (RRM) Task Board 4 (TB4). Four industry and government partners have provided advanced PV devices for measurement and orbital environment testing. The experiment will be on-orbit for approximately 18 months. It is completely self-contained and will provide its own power and internal data storage. Several new cell technologies including four- junction (4J) Inverted Metamorphic Multijunction (IMM) cells will be evaluated and the results compared to ground-based measurements.

solar cell↗

Opportunities for Solar Industrial Process Heat in the United States

This presentation summarizes the first national analysis of opportunities for solar technologies to provide industrial process heat (IPH) in the United States. The industrial sector is a major end-user of energy and IPH constitutes a majority of industrial fuel energy. New disaggregations of IPH demands are made at the temporal, geographic, and operational levels. Solar heat generation by seven solar thermal technologies and PV-connected electrotechnologies are modeled using county solar resources and land availability and matched to relevant IPH demands. Parabolic trough collectors (PTC), when combined with thermal energy storage (TES), not only have the largest opportunity in terms of distribution over geography and time, but also in terms of applicable IPH demands. PTC with TES represents the displacement of nearly 2,500 trillion Btus of combustion fuels, which corresponds to 137 million metric tons of CO2, or about 15% of all industrial combustion CO2 emissions. TES, along with site-level analysis, are identified as areas of further analysis.

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

The National Climate Database (NCDB): An Unbiased 100-Year Dataset for PV Modeling

In this study, we develop a statistical technique to downscale the future projection of solar irradiance for photovoltaics (PV) energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the downscaling method, a summary of the 100-year dataset from 2001-2100, and future extension of this research.

bias correction↗

Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)

Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.

14 SOLAR ENERGY↗

Do solar panels contain PFAS?

The presence and potential leaching of PFAS (Per- and Polyfluoroalkyl Substances) from solar panels are increasingly mentioned in news articles, raising public concerns. Such concerns may slow the adoption of photovoltaic (PV) technology, despite its central role in the renewable energy sector. The limited transparency from manufacturers about fluorinated materials used in PV modules, along with the scarcity of publicly available testing data, contributes to uncertainty and speculation. This perspective aims to clarify the current state of PFAS presence in solar PV. Although certain fluoropolymers are used in PV manufacturing, the scientific consensus on their toxicity indicates they should not be classified as PFAS. Portraying fluoropolymers as toxic PFAS unnecessarily amplifies concerns and unfairly undermines the perceived environmental sustainability of PV technology.

environmental impact↗

Optimization of Carbon-Nanotube-Reinforced Composite Gridlines Towards Commercialization

Solar cells in PV modules crack during field operation from environmental stressors, including extreme weather events, such as hailstorms and hurricanes. These cracks can lead to gradual or immediate acute power degradation. To directly address cell-crack-induced degradation, we have formulated a carbon nanotube additive for commercial screen printed silver pastes. We have shown in previous work that these metal matrix composites have little to no effect on the cell’s efficiency while enhancing the metallization’s fracture toughness and electrical gap-bridging capability. In this work, we focus on optimizing the composite metallization to achieve the best possible performance. We discover that reducing carbon nanotube agglomerations in the paste not only improves the printability for narrow gridlines, but also increases the modulus of toughness of the metallization by over 500%.

carbon nanotubes↗