激光打孔技术在光伏背板玻璃上的应用

双玻光伏组件以其抗PID性强、防隐裂、防水汽透过、抗蜗牛纹、可靠性优异、轻量化等诸多优点,在晶硅太阳能组件市占比逐步提高。双玻光伏组件用背板玻璃一般需要预留出线孔,光伏背板玻璃的出线孔主要有两种打孔方式:金钢钻上下同步钻孔的模式和激光打孔。激光打孔以其易维护、可异形孔加工、效率高、生产成本低等优势得到各大玻璃厂的认可。通过分析在实际生产中激光打孔出现的打孔缺陷问题,提出了改善措施,有助于工厂的降本增效。     

光伏阵列倾角及方位角的最优化研究

根据光伏阵列的特点建立了光伏阵列的数学模型,分析光伏倾角和方位角对容量和能量价值最大化的影响,并结合2017年的发电数据进行了对比研究,计算出容量和能量价值最大化的倾角和方位角。实验结果表明:该方法能够获得最佳的光伏安装角度,具有较高的应用价值。     

基于VMD和改进TCN的短期光伏发电功率预测

光伏发电功率存在波动性,且光伏出力易受各种气象特征影响,传统TCN网络容易过度强化空间特性而弱化个体特性。针对上述问题,文中提出一种基于VMD和改进TCN的短期光伏发电功率预测模型。通过VMD将原始光伏发电功率时间序列分解为若干不同频率的模态分量,将各个模态分量以及相对应的气象数据输入至改进TCN网络进行建模学习。利用中心频率法确定VMD的最优分解模态分解个数。在传统TCN预测模型的基础上,使用DropBlock正则化取代Dropout正则化以达到抑制卷积层中信息协同的效果,并引入注意力机制自主挖掘并突出关键气象输入特征的影响,量化各气象因素对光伏发电的影响,从而提高预测精度。以江苏省某光伏电站真实数据为例进行仿真实验,结果表明所提预测方法的RMSE为0.62 MW,MAPE为2.03%。     

Influence of photovoltaic generation model and time resolution on the reliability evaluation of distribution systems

This paper aims to investigate the influence of photovoltaic (PV) generation on reliability evaluation of distribution systems. Two PV generation models are used to predict the output power injected into the grid, taking into account the main relevant environmental variables, the irradiance and ambient temperature. Issues that directly affect the output power, such as the spatial smoothing effect due to the plant size and the influence of the irradiance and temperature measurement interval are taken into consideration. Using measurement time series of irradiance and local temperature, the models are used to generate power series in 4‐minute and hourly resolutions. The generated power series are used in a reliability assessment model, with the objective of evaluating the impact of solar resource variability on the reliability indices of the system. Case studies on the IEEE RBTS‐Bus 2 and on the real distribution system of Fernando de Noronha in Brazil are presented and discussed, for power plants of different capacities, considering the effect of the PV generation models, the temporal resolution of the time series and the spatial smoothing of the power output fluctuations. The results show that the power time series in hourly resolution significantly underestimates the frequency of interruptions. For the real system, this index is underestimated at the system level (up to 43%) and at the load points (up to 72%). On the other hand, for the interruption duration index, the temporal aggregation results in a small underestimation (just 4%). The results also indicates that the smoothing effect is irrelevant for typical PV system sizes of distribution systems with discretization equal to or above 4 minutes.     

In-situ self-reconstruction of Ni–Fe–Al hybrid phosphides nanosheet arrays enables efficient oxygen evolution in alkaline

Developing efficient oxygen evolution reaction (OER) electrocatalysts with earth-abundant elements is very important for sustainable H₂ generation via electrochemical water splitting. Here we design a crystalline-amorphous Ni–Fe–Al hybrid phosphides nanosheet arrays grown on NiFe foam for efficient OER application. Dynamic surface reorganization of phosphides at anodic/cathodic polarizations is probed by in situ Raman spectroscopy. The reconstructed amorphous Ni(Fe)OOH species are determined as the active phases that facilitate the OER process. This unique electrode shows highly catalytic activity toward water oxidation, achieving the current densities of 10 and 100 mA cm^?2 at 181 and 214 mV in 1 M KOH, respectively. Meanwhile, it also exhibits excellent stability at a large current density of 100 mA cm^?2 for over 60 h. This work reveals the dynamic structural transformation of pre-catalyst in realistic conditions and highlights the important role of oxyhydroxides as real reactive species in OER process with high activity.     

Enhanced photo-electrochemical activity of ZnO/Cu2S nanotube arrays photocathodes

ZnO/Cu₂S nanotube arrays are fabricated firstly by a facile and capping-agent-free method, and the photo-electrochemical performance has been studied systematically. The results show that ZnO/Cu₂S nanotube arrays achieve enhanced photo-electrochemical water splitting performance and the photocurrent densities of ZnO/Cu₂S are 7.9 times than that of ZnO at 0 V versus Ag/AgCl. The performance of the ZnO/Cu₂S nanotube arrays can be adjusted by changing the amount of Cu₂S microcrystals. The results confirm that the enhanced photo-electrochemical performance of ZnO/Cu₂S is due to the significantly improved visible light absorption, effective separation of photo-induced carriers due to the well band energy match and the formed p-n junction between ZnO and Cu₂S.     

A review on modeling of solar photovoltaic systems using artificial neural networks,fuzzy logic,genetic algorithm and hybrid models

The uncertainty associated with modeling and performance prediction of solar photovoltaic systems could be easily and efficiently solved by artificial intelligence techniques. During the past decade of 2009 to 2019, artificial neural network (ANN), fuzzy logic (FL), genetic algorithm (GA) and their hybrid models are found potential artificial intelligence tools for performance prediction and modeling of solar photovoltaic systems. In addition, during this decade there is no extensive review on applicability of ANN, FL, GA and their hybrid models for performance prediction and modeling of solar photovoltaic systems. Therefore, this article focuses on extensive review on design, modeling, maximum power point tracking, fault detection and output power/efficiency prediction of solar photovoltaic systems using artificial intelligence techniques of the ANN, FL, GA and their hybrid models. In addition, the selected articles on the solar radiation prediction using ANN, FL, GA and their hybrid models are also summarized. Total of 122 articles are reviewed and summarized in the present review for the period of 2009 to 2019 with 90 articles in the field of {ANN, FL, GA and their hybrid models} + solar photovoltaic systems and 32 articles in the field of {ANN, FL, GA and their hybrid models} + solar radiation. The review shows the suitability and reliability of ANN, FL, GA and hybrid models for accurate prediction of the solar radiation and the performance characteristics of solar photovoltaic systems. In addition, this review presents the guidance for the researchers and engineers in the field of solar photovoltaic systems to select the suitable prediction tool for enhancement of the performance characteristics of the solar photovoltaic systems and the utilization of the available solar radiation.     

光伏用电致发光缺陷检测仪空间分辨率的量化评估

针对光伏用电致发光缺陷检测仪空间分辨率目视判定重复性、准确性差,并且难以量化等问题,提出一套基于卷积神经网络模型的空间分辨率量化评估方法。参照相关标准JJF(闽)1088-2018,采取不同的拍摄条件拍摄并切割出空间分辨率线对图像,对图像进行人工分类。设计卷积神经网络结构,采用卷积层、池化层和全连接层结构,并使用已分类完成的空间分辨率线对图像对模型进行训练。最终使用测试集对模型进行评估,结果表明,模型在测试集上的判别正确率达到99.2%。该方法满足使用要求,可取代目视判别,提高了光伏用电致发光缺陷检测仪空间分辨率判定的准确性与重复性,并为其量化提出了新的解决思路。由于太阳电池片用光致发光缺陷检测仪与光伏用电致发光缺陷检测仪的成像方式类似,该方法可兼容太阳电池片光致发光检测仪的性能评估。