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At least 163 records · Page 9

Validation of Photovoltaic Modeling Tool Solargraf Against Measured Data

Solargraf is a cloud-based 3D design tool by Enphase Energy that allows users to design solar and storage systems with a variety of elements. Through a Cooperative Research and Development Agreement (CRADA), Enphase Energy collaborated with the National Renewable Energy Laboratory (NREL) to validate Solargraf's 3D design simulation against measured PV system performance. This study follows the same methodology of similar validation studies completed at NREL. The predicted performance results from simulations in both Solargraf and NREL's System Advisor Model (SAM) tool were compared with measured data to evaluate performance predictions.

14 SOLAR ENERGY↗

Clear-sky detection for PV degradation analysis using multiple regression

A method is presented to detect clear-sky periods for plane-of-array irradiance time-averaged data that is based on the algorithm originally described by Reno and Hansen. Here we show this new method improves the state-of-the-art by providing accurate detection at longer data averaging intervals. Moreover, our new method detects clear periods in plane-of-array data, which is novel. The new method is developed by applying a Design of Experiment approach to optimize the parameters used in the Reno method, and Monte Carlo simulations are used to understand the robustness of the found parameters. Clear-sky detection accuracy is compared among four methods: the Reno method, the default clear-sky filter in RdTools, the Ellis method, and the method outlined in this work, using a hand-labeled two-year data set of 1-min plane-of-array irradiance for a fixed tilt system. The RdTools clear-sky filter is marred by excessive false positives. The other methods all perform well at 1-min data intervals; the method developed here provides more accurate detection at longer data averaging intervals. We show that the parameters are directly linked to the data frequency in the hope that these input variables may not have to be optimized for every data frequency and location. However, only a single fixed system in one location was carefully examined. Finally, we illustrate how accurate determination of clear-sky conditions helps to eliminate data noise and bias in the assessment of long-term performance of PV plants.

14 SOLAR ENERGY↗

bifacial_radiance: a python package for modeling bifacial solar photovoltaic systems

bifacial_radiance is a national-laboratory-developed, community-supported, open-source toolkit that provides a set of functions and classes for simulating the performance of bifacial photovoltaic (PV) systems. (Bifacial PV modules collect light on the front as well as the rear side.) bifacial_radiance automates calculations of PV system layout and performance to use along with the popular ray-tracing software tool RADIANCE (Ward, 1994). Specific algorithms include design and layout of PV modules, reflective ground surfaces, shading obstructions, and irradiance calculations throughout the system, among others. bifacial_radiance is an important component of a growing ecosystem of open-source tools for solar energy (William F Holmgren et al., 2018).

97 MATHEMATICS AND COMPUTING↗

Optimizing Repowering and Lifecycle Decisions with PV ICE and SAM

Should you repower or extend the life of your PV system? Are high-efficiency modules, durable modules, or recyclable modules the best option for your site and goals? Evaluating the trade-offs in design and lifecycle strategies can be complex. The PV in Circular Economy (PV ICE) tool is an open-source model designed to help developers, modelers, and decision-makers assess material flows, energy return on investment (EROI), and financial viability of PV systems. Now integrated with the System Advisor Model (SAM), PV ICE enables site-specific comparisons of lifecycle strategies - such as repowering benefits, module selection for reliability and recyclability, among others. This interactive tutorial will provide hands-on experience with PV ICE using Google Collab, exploring scenario-based analyses on these topics.

36 MATERIALS SCIENCE↗

Rooftop Solar PV Quality and Safety in Developing Countries - Key Issues and Potential Solutions

To scale solar photovoltaic (PV) deployment in developing countries, the technology must be safe and reliable, meeting both customer and utility expectations. However, challenges exist in achieving these goals. Because PV systems are novel and complex, the majority of consumers are unable to distinguish between low- and high-quality systems; many may invest based on price alone. Suboptimal PV system performance and safety incidents can have downstream impacts on the solar industry and customer adoption because of unmet expectations and negative publicity. Rooftop solar system components vary in quality, and inadequate training could lead to poor installation practices. And even if inspection checklists, certification procedures, and standards are available, they may not be widely used in countries if they are not mandatory, the workforce is not aware of them, or installers lack the technical capacity to comply. Despite the numerous solar quality and safety challenges developing countries may face, lessons learned and best practices from around the world can address them.

14 SOLAR ENERGY↗

Impact of soiling on Si and CdTe PV modules: Case study in different Brazil climate zones

Soiling, particulate accumulation on photovoltaic (PV) module surfaces, reduces the available solar resource and the resulting generated device power. This case-study summarizes initial results of 5-year research on the contrasting soiling conditions in the tropical, subtropical, and semi-arid climates in Brazil. A major objective is to present a case study of the effects of soiling on PV module performance in different Brazil climate zones that represent the primary areas for the current and expanding Brazil solar installations. For this, the paper presents methodologies to quantify the soiling ratio (SRatio) and soiling rate (SRate) for two representative commercial technologies, polycrystalline or multicrystalline silicon (mc-Si) and thin-film cadmium telluride (CdTe) modules, through soiling monitoring stations deployed in the selected climate regions. An aim is to add to the growing soiling-research knowledge base through addressing these key factors and their relationships to critical electrical, solar resource, thermal, and local meteorological and environmental parameters. This paper presents, evaluates, and compares soiling rates and losses in Belo Horizonte, Minas Gerais (Equatorial Tropical: 19.92° S, 43.99° W), Porto Alegre, Rio Grande do Sul (Humid-Subtropical: 30.05° S, 51.17° W), and Brotas de Macaúbas, Bahia (Semi-Arid: 12.00° S, 42.63° W). The results show that soiling is moderate in all 3-regions, for example with 0.1%/day < SRate < 0.2%/day for Belo Horizonte. Precipitation dominates the cleaning of the modules in the summertime in this climate zone, while it is the major factor year-round in Rio Grande do Sul. Wind is the major issue mitigating the soiling accumulation for the Bahia installation. The methodology incorporates several key refinements, including the normalization and adjustment for the meteorological parameters (temperature, irradiance, wind, precipitation). The evaluations include the region-specific differing effects of non-uniform soiling, natural cleaning, and ambient temperatures.

14 SOLAR ENERGY↗

Open‐source photovoltaic model pipeline validation against well‐characterized system data

Abstract All freely available plane‐of‐array (POA) transposition models and photovoltaic (PV) temperature and performance models in pvlib‐python and pvpltools‐python were examined against multiyear field data from Albuquerque, New Mexico. The data include different PV systems composed of crystalline silicon modules that vary in cell type, module construction, and materials. These systems have been characterized via IEC 61853‐1 and 61853‐2 testing, and the input data for each model were sourced from these system‐specific test results, rather than considering any generic input data (e.g., manufacturer's specification [spec] sheets or generic Panneau Solaire [PAN] files). Six POA transposition models, 7 temperature models, and 12 performance models are included in this comparative analysis. These freely available models were proven effective across many different types of technologies. The POA transposition models exhibited average normalized mean bias errors (NMBEs) within ±3%. Most PV temperature models underestimated temperature exhibiting mean and median residuals ranging from −6.5°C to 2.7°C; all temperature models saw a reduction in root mean square error when using transient assumptions over steady state. The performance models demonstrated similar behavior with a first and third interquartile NMBEs within ±4.2% and an overall average NMBE within ±2.3%. Although differences among models were observed at different times of the day/year, this study shows that the availability of system‐specific input data is more important than model selection. For example, using spec sheet or generic PAN file data with a complex PV performance model does not guarantee a better accuracy than a simpler PV performance model that uses system‐specific data.

14 SOLAR ENERGY↗

Inverted metamorphic GaInAs solar cell grown by dynamic hydride vapor phase epitaxy

We present an inverted metamorphic rear heterojunction ~1.0 eV GaInAs solar cell deposited by dynamic hydride vapor phase epitaxy (D-HVPE) with high growth rate. This device uses a Ga 1-x In x P compositionally graded buffer (CGB) to bridge the lattice constant gap between the GaAs substrate and the Ga0.71In0.29As emitter layer. High-resolution x-ray diffraction and transmission electron microscopy confirm that the Ga 0.71 In 0.29 As emitter is grown lattice-matched to the in-plane lattice constant of the CGB with minimal generation of defects at the GaInAs/GaInP interface. The device contains a threading dislocation density of 2.3 × 10 6 cm -2 , a level that enables high-performance minority carrier devices and is comparable to previously demonstrated GaInP CGBs grown by D-HVPE. The device exhibits an open-circuit voltage of 0.589 V under a one-sun AM1.5G illumination condition and a bandgap-voltage offset of 0.407 V, indicating metamorphic epitaxial performance nearly equal to state-of-the-art devices. We analyze the dark current of the device and determine that reducing recombination in the depletion region, which can be achieved by reducing the threading dislocation density and optimizing the device doping density, will improve the device performance. Furthermore, the CGB and device layers, comprising ~8 µm of thickness, are grown in under 10 min, highlighting the ability of D-HVPE to produce high-quality metamorphic devices of all types with the potential for dramatically higher throughput compared to present technology.

14 SOLAR ENERGY↗

Signal Temporal Logic Control for Residential HVAC Systems to Accommodate High Solar PV Penetration

This paper proposes a new signal temporal logic (STL) control for ON/OFF residential buildings' Heating Ventilation and Air Conditioning (HVAC) systems. STL is used to control indoor temperatures while consuming most of the generated solar photovoltaic (PV) power locally to minimize its impact on the grid and reduce the need for large energy storage devices. In contrast to most, if not all, control mechanisms such as the traditional model predictive control (MPC), STL control allows for including temporal constraints in the control formulation to further relax indoor temperatures' constraints and allow them to exceed the comfort band limits for a prespecified (short) period of time. This relaxation allows to consume an additional PV power by the HVAC systems, which prevents such an unwanted intermittent power from affecting the grid. We formulate the MPC-based STL control mechanism to implement the objective. Simulation results show that the PV tracking performance has been improved while employing the proposed STL controller.

Wu, Tumin↗

Clear-Sky Detection Using Time-Averaged, Tilted-Plane Data

A method is presented to detect clear-sky periods for plane-of-array, time-averaged irradiance data that is based on the algorithm originally described by Reno and Hansen. We show this new method improves the state-of-the-art by providing accurate detection at longer data intervals, and by detecting clear periods in plane-of-array data, which is novel. We illustrate how accurate determination of clear-sky conditions helps to eliminate data noise and bias in the assessment of long-term performance of PV plants.

clear-sky conditions↗

Assessment of Accelerated Stress Testing Data for Silicon Photovoltaics Using Tensor Decomposition Methods

In this work, we examine the use of high-order tensor decompositions to analyze degradation pathways emerging from accelerated stress testing of silicon photovoltaic (PV) modules. Matrix-based decompositions are powerful tools for studying two-dimensional data arrays and form the foundation of a host of classical data analysis techniques. Tensors are high-order extrapolations of matrices that are able to account for more parameter dimensions, and a variety of tensor decomposition methods have been developed that similarly seek to extend insights from matrix decompositions to higher dimensions. Applying and interpreting tensor decomposition methods to sequences of PV module image data, we seek to uncover and isolate different degradation modes occurring from accelerated stress testing procedures. Further, we consider the contributions of different modes to PV module performance degradations.

data analysis↗

Performance of Photovoltaic Systems Recorded by Open Solar Performance and Reliability Clearinghouse (oSPARC)

This article analyzes data from 2,200 photovoltaic systems collected through the Open Solar Performance and Reliability Clearinghouse (oSPARC, 2018) to draw conclusions about the measured performance of the systems, how it compares to expectations, and how wide the variation is. The systems range in size from 2 kW to 1,200 kW, with an average size of 229 kW, and were activated in oSPARC between March 13, 2007 and Dec. 16, 2016. Data regarding co-incident insolation and ambient temperature are provided through the oSPARC platform for the population of systems and summarized here. Results indicate that - after correcting for measured insolation, derating for temperature, and correcting for balance-of-system efficiency and degradation as a result of system age - the performance ratio of these 2,200 systems averages 91.7%. Adjusting for known parameters such as age and efficiency, the ratio would ideally be 100%. Thus, the 'underperformance' of this system sample is measured at 9.3% and suggests that as much as 9.3% could be recovered if the systems were caused to perform as expected through optimal operation and maintenance. Efforts to correlate the performance ratio with environmental conditions resulted in very low coefficients of regression, but the method already normalizes for actual site insolation and temperature, which are responsible for much of the site-specific variation. An exemption is air-quality nonattainment areas, where the measured performance of plants averages 86.9% and is consistently lower than the average of 95.9% in areas that are in compliance with air quality standards, likely because of particulate matter such as diesel soot exacerbating the soiling rate.

14 SOLAR ENERGY↗

Optical Detection of Crack Separation in Si PV Modules

Studying the mechanical behavior of silicon cell fractures is critical for understanding changes in PV module performance. Traditional methods of detecting cell cracks, e.g., electroluminescence (EL) imaging, utilize electrical changes and defects associated with cell fracture. Therefore, these methods reveal crack locations, but do not operate at the time or length scales required to accurately measure other physical properties of cracks, such as separation width and behavior under dynamic loads.

14 SOLAR ENERGY↗

Using Current Data to Detect Hardware Faults at Solar Plants

Monitoring amperage data is an effective means of detecting faults in PV plant data. Utilizing amperage data collected at the combiner box gives plant operators an up-to-date list of faulted equipment, allowing them to coordinate maintenance needs at much shorter intervals than previously. Shorter maintenance intervals will increase PV plant production levels, narrowing the gap between expected and actual PV plant performance. The amperage monitoring method performs at a high level, with a string-outage related fault detection True Positive Rate of 46% and False Positive Rate of 8%.

14 SOLAR ENERGY↗

Solar Radiation Research Laboratory (SRRL) Core Project Final Report: Fiscal Years 2022-2024

The Solar Radiation Research Laboratory (SRRL) at the National Laboratory of the Rockies (NLR) is a world-leading solar calibration and measurement facility and maintains and disseminates the World Radiation Reference (essentially the W/m2) for the United States that is essential for traceable and accurate measurements of solar radiation at all solar generation facilities. SRRL operates two calibration facilities that meet International Standards Organization-17025 (ISO-17025) standards and provide unique high-quality calibrations to NREL and other U.S. Department of Energy laboratories. The Baseline Measurement System (BMS) at SRRL provides a high-quality record of solar irradiance and surface meteorological conditions. SRRL capabilities are used to develop (1) improved methods for the calibration of solar radiometers; (2) new standards through the ISO, the International Electrotechnical Commission (IEC), and the American Standards for Testing of Materials (ASTM) International; (c) solar radiation and meteorological models; and (d) advanced instrumentation and methods for operating solar measurement stations. The SRRL datasets are also critical for the validation of new models and datasets, such as the National Solar Radiation Database (NSRDB). The research and development of solar radiation measurement systems and resource modeling techniques are essential for advancing the scientific basis for producing reliable resource data. Specifically, the spatial, temporal, and spectral (wavelength dependency) characteristics of the solar resource are required in several different time frames for various project phases.

14 SOLAR ENERGY↗

Iterative and Self-Consistent Estimation of Degradation and Soiling Loss in PV Systems - A Case Study

In many parts of the world, soiling is a significant loss mechanism for PV energy production. Methods for accurately quantifying historical and current soiling losses are needed. Furthermore, state-of-the-art methods to estimate degradation rates based on production data do not handle soiling in a satisfactory manner. In order to accurately estimate either of these quantities, it is in many cases helpful to consider their combined effect on PV system performance. In this work we make use of the Combined Degradation and Soiling (CODS) algorithm, which iteratively decomposes time series of daily normalized energy yield into four components: a soiling ratio, a degradation trend, seasonal variations, and noise. We demonstrate the use of the model on field performance data from a utility-scale power plant in a high-soiling environment in the Middle East. We apply the algorithm to the temperature-corrected performance index of the DC power on inverter level, quantifying how soiling varies over time and through the plant. The irradiation-weighted average soiling loss in this plant is 2.3 %, with a median soiling rate of -0.086 %/day. Between the inverters in the site in study, estimated degradation rates range between -0.86 %/year and -0.15 %/year, with a mean rate of -0.48 %/year.

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

Industry Facing PV Degradation Prediction Tool and Database to Enable a 50 Year Life Module

The goal of this work is to create an online tool that can be used to search for degradation information and extrapolate PV module performance and durability to field exposure. A graphical user interface will aid in the understanding of the results. The prediction tool will be built modular and published open-source allowing users to expand on the existing framework.

degradation↗