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At least 1,171 records · Page 65

Predicting Solar Plant Generation with Machine Learning Techniques

Accurately predicting power generation for PV sites is critical for prioritizing relevant operations & maintenance activities, thereby extending the lifetime of a system and improving profit margins. A number of factors influence power generation at PV sites, including local weather, shading and soiling losses, design of modules, DC mismatches, and degradation over time. Other external factors such as curtailment and grid outages can also have a notable impact on power generation. Machine learning techniques can be used to provide more accurate predictions of PV power production by accounting for important weather and climate information neglected by current industry methods. This article will cover the deficiencies of those methods and will show how machine learning can dramatically improve power generation predictions.

14 SOLAR ENERGY↗

A Nonrelational Data Warehouse for the Analysis of Field and Laboratory Data From Multiple Heterogeneous Photovoltaic Test Sites

A nonrelational, distributed computing, data warehouse, and analytics environment (Energy-CRADLE) was developed for the analysis of field and laboratory data from multiple heterogeneous photovoltaic (PV) test sites. This data informatics and analytics infrastructure was designed to process diverse formats of PV performance data and climatic telemetry time-series data collected from a PV outdoor test network, i.e., the Solar Durability and Lifetime Extension global SunFarm network, as well as point-in-time laboratory spectral and image measurements of PV material samples. Using Hadoop/HBase for the distributed data warehouse, Energy-CRADLE does not have a predefined data table schema, which enables ingestion of data in diverse and changing formats. For easy data ingestion and data retrieval, Energy-CRADLE utilizes Hadoop streaming to enable Python MapReduce and provides a graphical user interface, i.e., py-CRADLE. By developing the Hadoop distributed computing platform and the HBase NoSQL database schema for solar energy, Energy-CRADLE exemplifies an integrated, scalable, secure, and user-friendly data informatics and analytics system for PV researchers. Furthermore, an example of Energy-CRADLE enabled scalable, data-driven, analytics is presented, where machine learning is used for anomaly detection across 2.2 million real-world current-voltage (I–V) curves of PV modules in three distinct Koppen–Geiger climatic zones.

14 SOLAR ENERGY↗

On the Path to SunShot - The Role of Advancements in Solar Photovoltaic Efficiency, Reliability, and Costs

Although tremendous progress has been made in reducing the cost of PV systems, additional LCOE reductions of 40%–50% between 2015 and 2020 will be required to reach the SunShot Initiative’s targets (see Woodhouse et al. 2016). Understanding the tradeoffs between installed prices and other PV system characteristics—such as module efficiency, module degradation rate, and system lifetime—are vital. For example, with 29%-efficient modules and high reliability (a 50-year lifetime and a 0.2%/year module degradation rate), a residential PV system could achieve the SunShot LCOE goal with modules priced at almost $1.20/W. But change the lifetime to 10 years and the degradation rate to 2%/year, and the system would need those very high-efficiency modules at zero cost to achieve the same LCOE. Although these examples are extreme, they serve to illustrate the wide range of technological combinations that could help drive PV toward the LCOE goals. SunShot’s PV roadmaps illustrate specific potential pathways to the target cost reductions.

14 SOLAR ENERGY↗

Exploring Si Heterojunction Solar Cell Degradation: Bulk and Interface Processes Analyzed by Simulations and Experiments in Order to Develop Mitigation Strategies

The Si technology with the highest conversion efficiency is a-Si/c-Si heterojunction (HJ) PV. Its market penetration, however, is slowed by reports that fielded HJ modules degraded at twice the rate of regular c-Si modules. Our very recent work confirmed this degradation and attributed it to enhanced recombination at the a-Si/c-Si interface, caused by the slow, order-of-magnitude increase of the defect density. We propose to comprehensively explore degradation mechanisms in Si HJ cells by combining simulations and experiments. Theoretically, we will: (1) simulate structure of a-Si and a-Si/c-Si interfaces, identify defects; (2) determine statistics of energy barriers that control defect formation; (3) compute growth of defect density from the barrier distribution, and the resulting degradation of Voc. Experimentally, we will: (1) create a series of HJ-cell-representative stacks with varying layer thicknesses and deposition conditions by using PECVD tools; (2) use temperature and injection-dependent lifetime spectroscopy to determine effective lifetimes; (3) deconvolve the data to separate bulk and interface effects, and the effects of charge density and interface defects to analyze long time degradation. The goal is to identify material and device degradation mechanisms, to develop mitigation strategies for improved stability, such as the introduction of capping layers and hydrogen diffusion control.

14 SOLAR ENERGY↗

Nanomechanical and Fluorescence Characterizations of Weathered PV Module Encapsulation

Nanoindentation and fluorescence spectroscopy provide spatially resolved mechanical and chemical characterization for degradation of poly (ethylene-co-vinyl acetate) (EVA) encapsulants aged under accelerated weathering and in field deployed photovoltaic (PV) modules. For the accelerated weathering tests, two different EVA formulations in the glass/EVA/glass-laminated coupons were exposed to ultraviolet (UV) light for 180 days at three different temperatures (40, 60, and 80 °C) and UV intensities (0.4, 2.2, and 2.9 W/m2/nm at 340 nm). The fluorescence spectra and moduli were uniform through the cross section of both EVA formulations at the lowest temperature and UV intensity; however, under the highest temperature and UV intensity, the UV irradiated sides showed lower moduli and higher fluorescence compared to the opposite sides. For EVA obtained from PV modules deployed 27 years in Sacramento, CA, USA, changes in fluorescence intensity across the thickness were relatively greater than changes in modulus. On the other hand, for EVA obtained from the same type of module stored in the shed for 27 years, no fluorescence was observed, and a uniform modulus was seen through the EVA layer, but with substantially higher values than those obtained from the field-deployed modules. The different extent of changes between laboratory and field exposures suggests the importance of considering effects of temperature and UV intensity for designing a reliable accelerated testing. This study uniquely demonstrates the capability of microscale characterization using nanoindentation and fluorescence microscopy to monitor mechanical and chemical degradation of EVA encapsulants in PV modules.

14 SOLAR ENERGY↗

Using Module Leakage Current Modeling to Understand Corrosion Chemistry

When fielded, modules are exposed to high voltages in the presence of moisture and/or elevated temperature this allows significant leakage currents to flow between the cell and ground. When current changes from an electronic to an ionic form, electrochemical reactions are promoted creating the potential for a wide variety of degradation reactions. This work investigates the nature of this current flow to gain a better understanding of the effect. At the cell surface, current preferentially flows to the metallization and under negative bias will split water to form OH - ions. It is found that transient effects occur in the leakage current as a result of some capacitive and electrochemical effects. This work seeks to provide important insight into the nature of the charge transfer species and the factors that most strongly affect leakage rates to provide better correlation to module performance.

14 SOLAR ENERGY↗

Technoeconomic Analysis of Photovoltaics Module Manufacturing with Thin Silicon Wafers

Reducing silicon usage by adopting thinner wafers can significantly reduce capital expenditure (capex) and cost, and thus accelerate the growth of manufacturing capacity and deployment. In this work, we evaluated potential benefits of thin Si wafers for current and future PV modules. We apply a technoeconomic framework that couples bottom-up cost model, and a cash-flow growth model to analyze PV modules with thin wafers. First, we show that, comparing the current PERC with 160 um thick wafers to the high-efficiency concept with 50 um thin wafers, the capex is reduced from 0.39 to 0.2 $/(W/year) while the cost is from 0.32 to 0.2 $/W. Second, the potential of accelerated deployment is analyzed for the highefficiency thin wafer concept. We found the significant advantages of higher growth rate (~20% relative) and higher deployment plateau (~3 times) than the current PERC modules. modules with thin wafers. First, we show that, comparing the current PERC with 160 um thick wafers to the high-efficiency concept with 50 um thin wafers, the capex is reduced from 0.39 to 0.2 $/(W/year) while the cost is from 0.32 to 0.2 $/W. Second, the potential of accelerated deployment is analyzed for the highefficiency thin wafer concept. We found the significant advantages of higher growth rate (~20% relative) and higher deployment plateau (~3 times) than the current PERC modules.

14 SOLAR ENERGY↗

Suggested Modifications for Bifacial Capacity Testing: Preprint

Capacity tests such as those described in ASTM 2848 and IEC 61724-2 are widely used during the contracting and acceptance testing of PV systems. With the increasing deployment of bifacial PV modules, there is a need to develop a standardized approach to capacity test these systems. Although variability and bias error was inherently higher for the measured capacity of bifacial systems, it could be reduced to a level consistent with the monofacial reference system by appropriate incorporation of rear irradiance- either measured or modeled. Three field installations provided bifacial system capacity that was measured with a mean bias error and standard deviation within 1% over the 2-10 month observation period. Capacity test accuracy could be improved further by utilizing measured back-of-module temperature and the IEC 61724-2 test method.

14 SOLAR ENERGY↗

Photovoltaic Recycling Processes

Solar photovoltaic (PV) installations must be properly dismantled and any waste treated and disposed of at the end of project life. However, because most of the world's nearly 400 GW of PV systems have been built in the past decade - each expected to operate for between 20 and 30 years-current PV module waste volumes do not yet justify widespread operation of PV recycling facilities. In anticipation of increasing demand however, several recycling companies are evaluating the PV waste market to assess waste-volume growth. Others are pursuing research- and pilot-stage PV module recycling activities. The latter are mostly commercial laminated glass and metal recyclers that process batches of PV modules on a periodic basis. This report describes a recent survey-based evaluation of existing commercial and pilot-scale recycling processes in Europe, and associated life cycle inventory data.

14 SOLAR ENERGY↗

Computational Discovery of Intermolecular Singlet Fission Materials Using Many-Body Perturbation Theory

Intermolecular singlet fission (SF) is the conversion of a photogenerated singlet exciton into two triplet excitons residing on different molecules. SF has the potential to enhance the conversion efficiency of solar cells by harvesting two charge carriers from one high-energy photon, whose surplus energy would otherwise be lost to heat. The development of commercial SF-augmented modules is hindered by the limited selection of molecular crystals that exhibit intermolecular SF in the solid state. Computational exploration may accelerate the discovery of new SF materials. The GW approximation and Bethe–Salpeter equation (GW+BSE) within the framework of many-body perturbation theory is the current state-of-the-art method for calculating the excited-state properties of molecular crystals with periodic boundary conditions. In this Review, we discuss the usage of GW+BSE to assess candidate SF materials as well as its combination with low-cost physical or machine learned models in materials discovery workflows. We demonstrate three successful strategies for the discovery of new SF materials: (i) functionalization of known materials to tune their properties, (ii) finding potential polymorphs with improved crystal packing, and (iii) exploring new classes of materials. In addition, three new candidate SF materials are proposed here, which have not been published previously.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transient Weighted Moving-Average Model of Photovoltaic Module Back-Surface Temperature

Accurate modeling of photovoltaic (PV) performance requires the precise calculation of module temperature. Currently, most temperature models rely on steady-state assumptions that do not account for the transient climatic conditions and thermal mass of the module. On the other hand, complex physics-based transient models are computationally expensive and difficult to parameterize. In order to address this, a new approach to transient thermal modeling was developed, in which the steady-state predictions from previous timesteps are weighted and averaged to accurately predict the module temperature at finer time scales. This model is informed by 3-D finite-element analyses, which are used to calculate the effect of wind speed and module unit mass on module temperature. The model, in application, serves as an added filter over existing steady-state models that smooths out erroneous values that are a result of intermittency in solar resource. Validation of this moving-average model has shown that it can improve the overall PV energy performance model accuracy by as much as 0.58% over steady-state models based on mean absolute error improvements and can significantly reduce the variability between the model predictions and measured temperature times series data.

14 SOLAR ENERGY↗

Validation of Heliovolt Modules at the RTCs

The purpose of the project is to design, construct, and commission up to 10 kW DC of Heliovolt’s module technologies. These PV demonstration systems are targeted for installation at: (1) Sandia’s RTC site located in Albuquerque, New Mexico, (2) Sandia’s RTC site located at Florida Solar Energy Center (FSEC) in Cocoa, FL, and (3) at NREL’s RTC site located in Aurora, CO. 5kW of PV was installed at each of these sites, but before the other 5 kW could be installed, Heliovolt Corporation ceased operations and liquidated all assets. The assets remaining at each RTC site have been legally abandoned. Sandia is currently assessing how these assets can be reused to benefit future research projects.

14 SOLAR ENERGY↗

Simultaneous band-gap narrowing and carrier-lifetime prolongation of organic–inorganic trihalide perovskites

The organic–inorganic hybrid lead trihalide perovskites have been emerging as the most attractive photovoltaic materials. As regulated by Shockley–Queisser theory, a formidable materials science challenge for improvement to the next level requires further band-gap narrowing for broader absorption in solar spectrum, while retaining or even synergistically prolonging the carrier lifetime, a critical factor responsible for attaining the near-band-gap photovoltage. In this work, by applying controllable hydrostatic pressure, we have achieved unprecedented simultaneous enhancement in both band-gap narrowing and carrier-lifetime prolongation (up to 70% to ~100% increase) under mild pressures at ~0.3 GPa. The pressure-induced modulation on pure hybrid perovskites without introducing any adverse chemical or thermal effect clearly demonstrates the importance of band edges on the photon–electron interaction and maps a pioneering route toward a further increase in their photovoltaic performance.

36 MATERIALS SCIENCE↗

Characterization of 3D Cirrus Cloud and Radiation Fields Using ARS/AIRS/MODIS data and its Application to Climate Model

During the report period, we have made the following research accomplishments. First, we performed analysis for a number of MODIS scenes comprising of heavy dust events and ice clouds, covering regions of frequent dust outbreaks in East Asia, Middle East, and West Africa, as well as areas associated with long-range dust transports over the Equatorial Tropical Atlantic Ocean. These scenes contain both dust/aerosols and clouds. We collected suitable aerosol/ice-cloud data, correlated ice cloud and aerosol parameters by means of statistical analysis, and interpreted resulting correlation trends based on the physical principles governing cloud microphysics. Aerosol and cloud optical depths and cloud effective particle size inferred from MODIS for selected domains were analyzed from which the parameters including dust aerosol number concentration, ice cloud water path, and ice particle number concentration were subsequently derived. We illustrated that the Twomey (solar albedo) effect can be statistically quantified based on the slope of best-fit straight lines in the correlation study. Analysis of aerosol and cloud retrieval products revealed that for all cases, the region with a larger dust aerosol optical depth is always characterized by a smaller cloud particle size, consistent with the Twomey hypothesis for aerosol-cloud interactions. Second, we developed mean correlation curves with uncertainties associated with small ice-crystal concentration observations for the mean effective ice crystal size (De) and ice water content (IWC) by dividing the atmosphere into three characteristic regions: Tropics cirrus, Midlatitude cirrus, including a temperature classification to improve correlation, and Arctic ice clouds. We illustrated that De has a high correlation with IWC based on theoretical consideration and analysis of thousands of observed ice crystal data obtained from a number of ARM-DOE field campaigns and other experiments. The correlation has the form: ln(De) = a + b ln(IWC) + c ((ln(IWC))2, where a, b, and c are fitting coefficients and are functions of three regions. We demonstrated that this correlation can be effectively incorporated in GCMs and climate models that predict IWC - a significant advance in ice microphysics parameterization for interactive cloud-radiation analysis and feedback. Substantial July mean differences are shown in the OLR (W/m2) and precipitation (mm/day) patterns between UCLA GCM simulations based on Des determined from the De-IWC correlations and the control run using a fixed ice crystal size. Third, in order to improve the computation of spectral radiative transfer processes in the WRF model, we developed a consistent and efficient radiation scheme that can better resolve the spectral bands, determine the cloud optical properties, and provide more reliable and accurate radiative heating fields. In the newly developed radiation module, we have implemented in WRF a modified and improved version referred to as the Fu-Liou-Gu scheme, which includes a combination of delta-four-stream and delta-two-stream approximations for solar and IR flux calculations, respectively. This combination has been proven to be computationally efficient and at the same time to produce a high degree of accuracy. The incorporation of nongray gaseous absorption in multiple scattering atmospheres was based on the correlated k-distribution method. The solar and IR spectra are divided into 6 and 12 bands, respectively, according to the location of absorption bands of H2O, CO2, O3, CH4, N2O, and CFCs. We further included absorption by the water vapor continuum and a number of minor absorbers in the solar spectrum leading to an additional absorption of solar flux in a clear atmosphere on the order of 1-3 W/m2. Additionally, we incorporated the ice microphysics parameterization that includes an interactive mean effective ice crystal size in association with radiation parameterizations. The Fu-Liou-Gu scheme is an ideal tool for the simulation of radiative transfer and ice microphysics within the domain of WRF. It is particularly useful for studying direct and indirect aerosol radiative effects associated with ice cloud formation. The newly implemented radiation module has been demonstrated to work well in WRF and can be effectively used for studies related to cirrus cloud formation and evolution as well as aerosol-cloud-radiation interactions. With the newly implemented radiation scheme, the simulations of cloud cover and ice water path have been improved for cirrus clouds, with a more consistent comparison with the corresponding MODIS observations, especially for optically thin cirrus with an improvement of about 20% in the simulated mean ice water path.

97 MATHEMATICS AND COMPUTING↗

Stabilization of light-induced effects in Si modules for IEC 61215 design qualification

Standardized testing of commercial photovoltaic modules is widely used around the world and decreases risks of module failures. Such testing also reduces financial risks for module manufacturers and customers. This work examines the expected impact of certain defects in silicon (Si) modules during standardized accelerated testing. Specifically, the behavior of boron-oxygen (BO) light-induced degradation (LID) and light- and elevated temperature-induced degradation (LeTID) are simulated during some of the stress tests in IEC 61215. LID and LeTID reaction rates at qualification temperatures are estimated from earlier published data. It is demonstrated the BO-related LID may cause some false positives and false negatives when IEC 61215 tests are performed as prescribed in the 2016 published version. Possible stabilization steps to avoid these false results are suggested. State changes for the defects causing LeTID occur much more slowly than those causing BO LID, and therefore LeTID is predicted to have a lesser impact on the IEC 61215 stress tests results.

14 SOLAR ENERGY↗

Manufacturing Supply Chain Development for Modular Solar-Thermochemical Conversion Platform - CRADA 387 (Final Report)

Modular chemical process intensification (MCPI) is an emerging field where chemical processing is performed using small-scale modular equipment instead of conventional large centralized chemical plants. Conventional chemical plants benefit from economies of scale that encourage scale-up to ever larger plants. A goal of MCPI is to develop technology that intensifies processing so that equipment can be dramatically smaller and integrated into modular systems. Scale-up occurs by adding more modules in parallel rather than making the equipment larger. A key concept is that equipment and modules can ultimately be cheaper by leveraging economies of mass production, analogous to the automotive industry, in manufacturing the equipment. This project made significant progress toward this outcome by meeting the RAPID institute metric to reduce equipment cost by 20% for each doubling in manufacturing volume. The MCPI application was thermochemical technology that is being commercialized by STARS Technology Corporation, one of the CRADA partners. The technology converts solar and renewable power to chemical energy to produce renewable hydrogen, fuels, and chemicals. The benefit to the public is reduction in greenhouse gases that are contributing to climate change. The project transitioned the steam methane reforming (SMR) reactor from conventional fabrication methods to additive manufacturing (AM) direct metal laser sintering (DMLS) process. This is projected to reduce the cost of making a reactor by 58% when producing 100 reactors per year. Innovations in the DMLS process produced a patented design that reduces reactor weight by 60%. Reductions in material costs and processing time extend the DMLS advantage to higher production volumes. The new design promises to be 38% cheaper than the conventional processes at 1000 units per year. The resulting 87% reduction in the steam methane reforming (SMR) module cost in scaling from current costs meets the RAPID metric. The project was successful in producing and testing the first ever additively manufactured SMR reactors. A reactor achieved over 82% efficiency in converting electric power to chemical energy, which is a world record for an inductively heated SMR. The project has contributed to the design and assembly of a first demonstration plant that is headed to a hydrogen bus filling station in Thousand Palms, CA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

US DOE Regional Test Centers Program - 2016 Annual Report.

The US Department of Energy’s Regional Test Center (RTC) program provides outdoor validation and bankability data for innovative solar technologies at five sites across the US representing a range of climate conditions. Data helps get new technologies to market faster and improves US industry competitiveness. Managed by Sandia National Laboratories and the National Renewable Energy Laboratory (NREL), the RTC program partners with US manufacturers of photovoltaic (PV) technologies, including modules, inverters, and balance-of-system equipment. The study is collaborative, with manufacturers (also known as RTC industry partners) and the national labs working together on a system design and validation strategy that meets a clearly defined set of performance and reliability objectives.

14 SOLAR ENERGY↗

Numbering-Up of Microscale Devices for Megawatt-Scale Supercritical Carbon Dioxide Concentrating Solar Power Receivers

Concentrated solar power (CSP) plants have the potential to reduce the consumption of nonrenewable resources and greenhouse gas emissions in electricity production. In CSP systems, a field of heliostats focuses solar radiation on a central receiver, and energy is then transferred to a thermal power plant at high temperature. However, maximum receiver surface fluxes are low (30–100 W cm -2 ) with high thermal losses, which has contributed to the limited market penetration of CSP systems. Recently, small (~4 cm 2 ), laminated micro pin-fin devices have shown potential to achieve concentrated surface fluxes over 100 W cm -2 using supercritical CO 2 as the working fluid. The present study explores the feasibility of using these microscale unit cells as building blocks for a megawatt-scale (250 MW thermal) open solar receiver through a numbering-up approach, where multiple microscale unit cell devices are connected in parallel. A multiscale model of the full-scale central receiver is developed. The model consists of interconnected unit cell and module level (i.e., multiple unit cells in parallel) submodels which predict local performance of the central receiver. Each full-scale receiver consists of 3000 micro pin-fin unit cells divided into 250 modules. The performance of three different full-scale receivers is simulated under representative operating conditions. The results show that the microscale unit cells have the potential to be numbered up to megawatt applications while providing high heat flux and thermal efficiency. At the design incident flux and surface emissivity, a global receiver efficiency of approximately 90% when heating sCO 2 from 550 °C to 650 °C at an average incident flux of 110 W cm -2 can be achieved.

14 SOLAR ENERGY↗