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2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC)最新文献

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NIEL DOSE and DLTS Analyses on Triple and Single Junction solar cells irradiated with electrons and protons 电子和质子辐照下三结和单结太阳能电池的NIEL DOSE和DLTS分析
R. Campesato, C. Baur, M. Casale, M. Gervasi, E. Gombia, E. Greco, Aldo Kingma, P. Rancoita, D. Rozza, M. Tacconi
Space solar cell radiation hardness is of fundamental importance in view of the future missions towards harsh radiation environment (like the Jupiter missions) and for the new spacecraft using Electrical Propulsion. In this paper we report the radiation data for triple junction (TJ) solar cells and related component cells. Triple junction solar cells, InGaP top cells and GaAs middle cells degrade after electron radiation as expected. With proton irradiation, a high spread in the remaining factors was observed, especially for the TJ and Ge bottom cells. Radiation results have been analyzed by means of the Displacement Damage Dose method and DLTS spectroscopy. In particular with DLTS spectroscopy it was possible to analyze the nature of a few defects introduced by irradiation inside the GaAs sub cell observing a strong correlation with the Displacement Damage Dose.
空间太阳能电池的辐射硬度对于未来的恶劣辐射环境任务(如木星任务)和使用电力推进的新航天器具有根本的重要性。本文报道了三结(TJ)太阳能电池及其组件电池的辐射数据。三结太阳能电池,InGaP顶部电池和GaAs中间电池在电子辐射后降解。在质子照射下,其余因子的分布较高,尤其是TJ和Ge底细胞。利用位移损伤剂量法和DLTS光谱对辐射结果进行了分析。特别是DLTS光谱,可以分析砷化镓亚电池内部辐照引入的一些缺陷的性质,观察到与位移损伤剂量的强相关性。
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引用次数: 6
Solar Forecast Reconciliation and Effects of Improved Base Forecasts 太阳预报调整及改进基础预报的效果
Gokhan Mert Yagli, Dazhi Yang, D. Srinivasan, Monika
Forecasting of solar PV generation plays an important role in power system operations. Forecasts are required on various geographical and temporal scales, which can be modeled as hierarchies. In a geographical hierarchy, the overall forecast for the region can either be obtained by directly forecasting the regional time series or by aggregating the individual forecasts generated for the sub-regions. This leads to a problem known as aggregate inconsistency as the two sets of forecasts are most likely different due to modeling uncertainties. Hence, practice is not optimal. Statistically optimal aggregation known as reconciliation, has been proven to provide aggregate consistent forecasts. Reconciliation helps system operators to have a superior foresight in a region-wise level, which eventually results in efficient system planning. The focus of this paper is on improving reconciliation accuracy. In addition, the effects of more accurate disaggregated and aggregated forecasts on the final reconciled predictions have been analyzed. A total of 318 simulated PV plants in California have been used to build a geographical hierarchy. More accurate NWP based and aggregated level forecasts are obtained with model output statistics and artificial neural network models. Significant improvements are observed in reconciled forecasts without using any exogenous information.
太阳能光伏发电预测在电力系统运行中具有重要作用。需要在各种地理和时间尺度上进行预测,这可以建模为层次结构。在地理层次结构中,区域的总体预测可以通过直接预测区域时间序列来获得,也可以通过汇总为子区域生成的单个预测来获得。由于建模的不确定性,两组预测很可能不同,这就导致了一个被称为聚合不一致的问题。因此,实践不是最佳选择。统计上最优的聚合称为调和,已被证明可以提供聚合一致的预测。协调有助于系统操作员在区域层面上具有卓越的远见,从而最终实现有效的系统规划。本文的研究重点是如何提高对账的准确性。此外,还分析了更准确的分类和汇总预测对最终调和预测的影响。加州共有318个模拟光伏电站被用来建立地理等级。通过模型输出统计和人工神经网络模型,可以获得更准确的基于NWP的综合水位预测。在不使用任何外生信息的情况下,在调和预测中观察到显著的改进。
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引用次数: 7
Evaluation of Irradiance Transposition Models When Utilized with Single Axis Tracking PV Systems in the Southwestern United States 美国西南部单轴跟踪光伏系统辐照度转换模型的评估
S. MacAlpine, Chris W. Wolfrom, O. Westbrook
This work examines the accuracy of commonlyused irradiance decomposition and transposition models when modeling single-axis tracking photovoltaic (PV) arrays in the southwestern United States. Inputs to the models include measured one-minute global horizontal, diffuse horizontal, and direct normal irradiance. The bias and variability associated with decomposition models’ predictions are analyzed and compared according to sky clearness and solar zenith angle, with results varying widely depending on the model employed. Separately, transposition model predictions are compared to measured plane-of-array (POA) irradiance at an operating PV plant with single-axis tracking. Goodagreement is found between the transposition models’ predictions and measured irradiance on clear sky days, with an absolute mean bias difference of $< 2$% for all anisotropic models. The decomposition and transposition models are then combined, with their predictions compared to measured POA irradiance at a second tracking PV plant on an annual and seasonal basis. Morevariability and bias are seen when both decomposition and transposition are performed, though good agreement with measured data is still possible with some model combinations.
本研究考察了美国西南部单轴跟踪光伏(PV)阵列建模时常用的辐照度分解和转位模型的准确性。模型的输入包括测量的一分钟全球水平、漫射水平和直接正常辐照度。根据天空晴朗度和太阳天顶角对分解模式预测的偏差和变率进行了分析和比较,结果因所采用的模式而有很大差异。另外,将转置模型预测与单轴跟踪的运行光伏电站的测量平面阵列(POA)辐照度进行比较。在晴空天,转位模型的预测结果与实测辐照度吻合良好,所有各向异性模型的绝对平均偏差均< 2%。然后将分解和转置模型结合起来,并将其预测与第二个跟踪光伏电站每年和季节性测量的POA辐照度进行比较。当进行分解和转置时,可以看到更多的变异性和偏差,尽管一些模型组合仍然可能与测量数据保持良好的一致性。
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引用次数: 0
Investigation of transparent electrodes and transparent/opaque a-Si:H solar cells for indoor photovoltaics 室内光伏透明电极和透明/不透明a-Si:H太阳能电池的研究
Gayoung Kim, M. Shin, J. Lim
Transparent and opaque hydrogenated amorphous silicon solar cells (a-Si:H) with various transparent electrodes are fabricated for indoor photovoltaics to supply power to Internet of Things devices. The performances of fabricated cells are investigated to evaluate the transparent electrode structures. The highest efficiency (6.05%) and highest average transmittance (24%) in the visible range are obtained with a transparent a-Si:H solar cell having single front and rear GZO electrodes, while the best efficiency is 9.29% with an opaque a-Si:H solar cell. Under LED indoor light, the best efficiencies are 5.12% with the opaque solar cell and 5.75% with the transparent solar cells.
采用各种透明电极制备透明和不透明氢化非晶硅太阳能电池(a-Si:H),用于室内光伏发电,为物联网设备供电。研究了制备电池的性能,以评价其透明电极结构。透明a- si:H电池在可见光范围内的效率最高(6.05%),平均透过率最高(24%),而不透明a- si:H电池的效率最高,为9.29%。在LED室内光下,不透明太阳能电池的效率为5.12%,透明太阳能电池的效率为5.75%。
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引用次数: 0
Life Cycle Assessment on Hydrogenation Processes on Silicon Solar Modules 硅太阳能组件加氢过程的生命周期评价
M. M. Lunardi, J. Alvarez-Gaitan, N. Chang, R. Corkish
Hydrogenation processes can offer improvements to the electrical performance of silicon (Si) solar cells from different feedstocks, including low-cost feedstocks, such as upgraded metallurgical silicon (UMG-Si). The development of PV technologies should be complemented by environmental analyses of the production processes. Here we undertake an environmental analysis of Si solar modules including the addition of hydrogenation processes through the life cycle assessment (LCA) method. LCA has not been applied to Si technologies such as hydrogenation, to the best of authors' knowledge. We show that the hydrogenation methods result in better environmental outcomes, considering the assumptions made in this LCA.
氢化工艺可以改善不同原料的硅(Si)太阳能电池的电性能,包括低成本原料,如升级的冶金硅(UMG-Si)。光伏技术的发展应辅之以生产过程的环境分析。在这里,我们对硅太阳能组件进行了环境分析,包括通过生命周期评估(LCA)方法添加氢化过程。据作者所知,LCA尚未应用于硅技术,如氢化。考虑到本LCA中所做的假设,我们表明加氢方法会产生更好的环境结果。
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引用次数: 0
Doping CdTe Absorber Cells using Group V Elements 使用V族元素掺杂CdTe吸收电池
A. Danielson, A. Munshi, Anna Kindvall, S. Swain, K. Barth, K. Lynn, W. Sampath
Arsenic dopant was incorporated in CdTe absorber layers in high-efficiency CdTe cells using feedstock doped with 1018cc-1for sublimation of films. The goal of the work was to develop a feasible method for creating a hole density equal to, or greater than that currently achievable using copper doping using a CuCl treatment. Doping with arsenic resulted in a modest increase in open-circuit voltage (VOC) and a large improvement in fill-factor and conversion efficiency when compared with copper-doped devices with similar structure. All experiments were performed in the presence of cadmium overpressure to encourage dopant activation in tellurium vacancy sites. Arsenic incorporation was measured using Secondary Ion Mass Spectrometry (SIMS) at 4E +16 atoms/cc-1,about four times greater incorporation than previously seen by the authors. Using a CdSeTe/CdTe graded absorber and arsenic doping, a conversion efficiency of 16.79% was achieved.
采用掺杂1018cc-1的原料,将砷掺杂剂掺入高效CdTe电池吸收层中,实现薄膜升华。这项工作的目标是开发一种可行的方法来创造一个等于或大于目前使用铜掺杂使用CuCl处理可以实现的空穴密度。与类似结构的掺杂铜器件相比,砷的掺杂导致了开路电压(VOC)的适度增加和填充因子和转换效率的大幅提高。所有实验都是在镉超压存在的情况下进行的,以促进碲空位位置的掺杂激活。砷的掺入使用次级离子质谱法(SIMS)以4E +16个原子/cc-1的速度测量,大约是作者先前观察到的掺入量的四倍。采用CdSeTe/CdTe梯度吸收剂并掺杂砷,可获得16.79%的转化效率。
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引用次数: 2
Insight into Metal Induced Recombination Losses and Contact Resistance in Industrial Silicon Solar Cells 工业硅太阳能电池中金属诱导复合损耗和接触电阻的研究
V. Mihailetchi, H. Chu, R. Kopecek
Despite of recent improvements in silver paste technology, the open-circuit voltages $( V_{oc})$ of silicon solar cells with screen printed and firing-through silver contacts continue to be limited by the high recombination currents at the metal contacts $( J_{{0} {,met}})$. To maximize solar cell efficiencies, the contact resistance $( rho_{c})$ and $J_{{0} {,met}}$ must be simultaneously minimised. In this study we investigated the origin of $J_{{0} {,met}}$ for screen printed silver pastes on $p^{+}$ and $n^{+}$ doped regions and correlate this with contact formation phases during the firing process. We show that, during the contact firing process, the $J_{{0} {,met}}$ significantly increases and even saturates to its final value at temperatures well below 700°C, which is a temperature range below that is needed for contact formation. The same is observed on both $p^{+}$ and $n^{+}$ diffused junctions with planar or random pyramids textured Si surfaces passivated by a SiO2/SiNx layer stack. This show that most of the metal induced recombination loses originates from the etching of the dielectric layers by the glass frit and less during the contact formation process where $rho_{c}$ is minimised. Furthermore, we demonstrate that increasing the SiNx passivating layer thickness leads to a significant reduction in $J_{{0} {,met}}$, possibly due to an incomplete etching of dielectric layers under the contact, whereas the $rho_{c}$ remain low and constant under optimum firing conditions. These findings could help design metallization pastes optimised to reduce dielectric etching, and hence $J_{{0} {,met}}$, without affecting $rho_{c}$.
尽管银浆技术最近有所改进,但具有丝网印刷和烧透银触点的硅太阳能电池的开路电压仍然受到金属触点处高复合电流的限制。为了使太阳能电池效率最大化,接触电阻$(rho_{c})$和$J_{{0} {,met}}$必须同时最小化。在本研究中,我们研究了$p^{+}$和$n^{+}$掺杂区域上丝网印刷银浆$J_{{0} {,met}}$的来源,并将其与烧制过程中的接触形成相联系起来。我们发现,在接触烧制过程中,$J_{{0} {,met}}$显著增加,甚至在远低于700°C的温度范围内饱和至其最终值,该温度范围低于接触形成所需的温度范围。在$p^{+}$和$n^{+}$扩散结上也观察到同样的现象,这些扩散结具有平面或随机金字塔纹理Si表面,并被SiO2/SiNx层堆叠钝化。这表明,大部分金属诱导复合损失来自于玻璃熔块对介电层的蚀刻,而在接触形成过程中损失较少,其中$rho_{c}$最小。此外,我们证明了增加SiNx钝化层厚度导致$J_{{0} {,met}}$显著降低,这可能是由于接触下介电层的不完全蚀刻,而$rho_{c}$在最佳烧制条件下保持低和恒定。这些发现可以帮助设计优化的金属化浆料,以减少介电腐蚀,因此$J_{{0} {,met}}$,而不影响$rho_{c}$。
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引用次数: 4
High Performance Metamorphic Tunnel Junctions for GaAsP/Si Tandem Solar Cells Grown via MOCVD MOCVD制备GaAsP/Si串联太阳能电池的高性能变形隧道结
D. Chmielewski, Daniel L. Lepkowski, J. Boyer, J. Carlin, T. Grassman, S. Ringel
A high-performance metamorphic $mathbf {Al}_{mathbf {0.2}} mathbf {Ga}_{mathbf {0.8}} mathbf {As}_{mathbf {0.75}} mathbf {P}_{mathbf {0.25}}$/GaAs$_{mathbf {0.75}}{mathbf {P}}_{mathbf {0.25}}$ tunnel junction structure, grown by metal-organic chemical vapor deposition, was designed for use within GaAs$_{mathbf {0.75}} {mathbf {P}}_{mathbf {0.25}}$textbf/Si tandem solar cells. Optimized growth conditions were determined for high C (p-type) and Te (n-type) doping, and a method to mitigate the well-known Te memory effect was develop. The optimized as-grown standalone test device yielded a peak tunneling current of 279.1 Acm $^{mathbf {-2}}$ and zero-bias resistance-area product of $3.0 times 10^{mathbf {-4}} Omega mathbf {cm}^{mathbf {2}}$. Upon exposure to various post-growth thermal treatments these values were found to degrade by up to an order of magnitude, but overall performance still far exceeded the demands for the tandem solar cell operating under AM1.5G, with further extension to operation under medium to high concentration possible.
设计了一种高性能变质$mathbf {Al} {mathbf {0.2}} mathbf {Ga} {mathbf {0.8}} mathbf {As} {mathbf {0.75}} mathbf {P}} {mathbf {0.25}} /GaAs$_{mathbf {0.75}}{mathbf {P}} {mathbf{0.25}}$隧道结结构,用于GaAs$_{mathbf {0.75}}{mathbf {P}} {mathbf {0.25}}$textbf/Si串级太阳能电池。确定了高C (p型)和高Te (n型)掺杂的最佳生长条件,并开发了一种减轻众所周知的Te记忆效应的方法。优化后的独立测试装置产生的峰值隧道电流为279.1 Acm $^{mathbf{-2}}$,零偏电阻面积积为$3.0 乘以10^{mathbf {-4}} Omega mathbf {cm}^{mathbf{2}}$。在暴露于各种生长后热处理后,这些值被发现降低了高达一个数量级,但总体性能仍然远远超过在AM1.5G下工作的串联太阳能电池的要求,进一步扩展到在中高浓度下工作的可能性。
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引用次数: 7
Feature Extraction, Supervised and Unsupervised Machine Learning Classification of PV Cell Electroluminescence Images 光伏电池电致发光图像的特征提取、监督与无监督机器学习分类
A. M. Karimi, Justin S. Fada, Jiqi Liu, J. Braid, Mehmet Koyutürk, R. French
Lifetime performance and degradation analysis of laboratory and field deployed PV modules is paramount to the continued success of solar energy. Image characterization techniques capture spatially resolved macroscopic manifestations of microscopic mechanistic behavior. Automated data processing and analytics allow for a large-scale systematic study of PV module health. In this study, degradation features seen in periodic EL images taken during test-to-failure damp-heat, thermal cycling, ultra-violet irradiance, and dynamic mechanical loading accelerated exposures are extracted and classified using supervised and unsupervised methods. Image corrections, including planar indexing to align module images, are applied. On extracted cell images, degradation states such as busbar corrosion, cracking, wafer edge darkening, and between-busbar dark spots can be studied in comparison to new cells using supervised and unsupervised machine learning. The systematic feature groupings provide a scalable method without bias to quantitatively monitor the degradation of laboratory and commercial systems alike. The evolution of these degradation features through varied exposure conditions provides insight into mechanisms causing degradation in field deployed modules. The supervised algorithms used in this application are Convolutional Neural Networks (CNN) and Support Vector Machines (SVM). With the increase in data and diversity of features, unsupervised learning can be employed to find relations between inherent image properties. Feature extraction techniques help identify intrinsic geometric patterns formed inthe images due to degradation. Principal component analysis is then applied to the extracted set of features to filter the most relevant components from the set, which are then passed to an agglomerative hierarchical clustering algorithm. Google’s Tensorflow library was utilized to enhance the computational efficiency of the CNN model by providing GPUbased parallel matrix operations. Using supervised methods on 5 features an accuracy greater than 98% was achieved. For unsupervised clustering, the classification was done into two clusters of degraded and non-degraded cells with 66% coherence.
实验室和现场部署的光伏组件的寿命性能和退化分析对太阳能的持续成功至关重要。图像表征技术捕捉微观机械行为的空间分辨宏观表现。自动化数据处理和分析允许对光伏组件健康进行大规模系统研究。在这项研究中,在测试到失效的湿热、热循环、紫外线照射和动态机械加载加速曝光期间,周期性EL图像中的退化特征被提取出来,并使用监督和非监督方法进行分类。图像校正,包括平面索引对齐模块图像,应用。在提取的细胞图像上,可以使用有监督和无监督的机器学习来研究退化状态,如母线腐蚀、开裂、晶圆边缘变暗和母线之间的黑点。系统的特征分组提供了一种可扩展的方法,没有偏见,可以定量地监测实验室和商业系统的退化。这些降解特征在不同暴露条件下的演变,有助于深入了解导致现场部署模块降解的机制。本应用中使用的监督算法是卷积神经网络(CNN)和支持向量机(SVM)。随着数据量的增加和特征的多样性,可以使用无监督学习来寻找图像固有属性之间的关系。特征提取技术有助于识别图像中由于退化而形成的固有几何图案。然后将主成分分析应用于提取的特征集,从中过滤出最相关的成分,然后将其传递给聚合层次聚类算法。利用Google的Tensorflow库,通过提供基于gpu的并行矩阵运算来提高CNN模型的计算效率。在5个特征上使用监督方法,准确率超过98%。对于无监督聚类,分类分为降解和非降解细胞两组,一致性为66%。
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引用次数: 14
Comparative study of sand erosion of backsheet of PV modules 光伏组件背板沙蚀比较研究
Umang Desai, Sudha Rathore, A. Agarwal, Aparna Singh
Efficient and uninhibited production of power from PV module depends on all parts of the module performing without getting degraded. Continuous flow of sand particles in deserts can erode backsheet during day and night alike. Erosion of this kind is insidious in nature and can curtail the longevity of PV modules. In the current study, erosion rates have been compared for two backsheets from different manufacturers when eroded by Indian sand. Erosion mechanisms for each backsheet for different sets of experimental conditions are presented in this work. It has been found that the tensile properties of the backsheet play a critical role in influencing the erosion.
光伏组件的高效和不受限制的发电取决于组件的所有部分的性能不退化。沙漠中不断流动的沙粒可以日夜侵蚀背板。这种侵蚀本质上是阴险的,可以缩短光伏组件的寿命。在目前的研究中,比较了来自不同制造商的两种背板在被印度沙侵蚀时的侵蚀速率。在这项工作中提出了不同实验条件下每个背板的侵蚀机制。研究发现,背板的拉伸性能对冲蚀有重要影响。
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引用次数: 0
期刊
2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC)
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