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。     

A comprehensive review of renewable energy resources for electricity generation in Australia

Recently, renewable energy resources and their impacts have sparked a heated debate to resolve the Australian energy crisis. There are many projects launched throughout the country to improve network security and reliability. This paper aims to review the current status of different renewable energy resources along with their impacts on society and the environment. Besides, it provides for the first time the statistics of the documents published in the field of renewable energy in Australia. The statistics include information such as the rate of papers published, possible journals for finding relative paper, types of documents published, top authors, and the most prevalent keywords in the field of renewable energy in Australia. It will focus on solar, wind, biomass, geothermal and hydropower technologies and will investigate the social and environmental impacts of these technologies.     

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.     

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。     

Techno-economic analysis of hydrogen energy for renewable energy power smoothing

With the increasing proportion of renewable energy (mainly wind power and photovoltaic) connected to the grid, the fluctuation of renewable energy power brings great challenges to the safe and reliable operation of power grid. As a clean, low-carbon secondary energy, hydrogen energy is applied in renewable energy (mainly wind power and photovoltaic) grid-connected power smoothing, which opens up a new way of coupling hydrogen storage energy with renewable energy. This paper focuses on the optimization of capacity of electrolyzers and fuel cells and the analysis of system economy in the process of power output smoothing of wind/photovoltaic coupled hydrogen energy grid-connected system. Based on the complementary characteristics of particle swarm optimization (PSO) and chemical reaction optimization algorithm (CROA), a particle swarm optimization-chemical reaction optimization algorithm (PSO-CROA) are proposed. Aiming at maximizing system profit, the capacity of electrolyzers and fuel cells are constrained by wind power fluctuation, and considering environmental benefits, government subsidies and time value of funds, the objective function and its constraints are established. According to the simulation analysis, by comparing the calculated results with PSO and CROA, it shows that PSO-CROA effectively evaluates the economy of the system, and optimizes the optimal capacity of the electrolyzers and fuel cells. The conclusion of this paper is of great significance for the application of hydrogen energy storage in the evaluation of power smoothness and economy of renewable energy grid connection and the calculation of economic allocation of hydrogen energy storage capacity.     

Polytetrafluoroethylene-intercalated MXene membranes with good photothermal performance for enhanced laser ignition

Photothermal effect has been widely used in many areas such as cancer therapy, photothermal energy harvesting, and laser ignition. However, exploring reliable and efficient free-standing energy converter for enhancing the photothermal performance is still a challenge. Herein, free-standing membrane based on two-dimensional MXene (Ti₃C₂) nanosheets and polytetrafluoroethylene (PTFE) was fabricated and characterized by X-ray diffraction, scanning electron microscopy and differential scanning calorimetry, which demonstrated a drastic temperature rise by laser irradiation and was further used as energy converter for enhancing the photothermal performance of laser ignition. Furthermore, the initiating power of the laser initiator can be largely reduced by adding a thin layer of MXene/PTFE membrane above the B/KNO₃ cylinder. This work can give great promise for MXene-based membranes as the laser energy converter for reducing the initiating energy and promote the development of laser initiators with low initiating energy.     

Morphology,structure, and photovoltaic properties of poly(3‐hexylthiophene) and [6,6]‐phenyl‐C61‐butyric acid methyl ester‐based ternary blends doping with polystyrene of different tacticities

The influence of the polystyrene of different tacticities on the morphology, phase structure, and photovoltaic properties of poly(3‐hexylthiophene) (P3HT) and [6,6]‐phenyl‐C61‐butyric acid methyl ester (PCBM) blend has been extensively investigated. The atactic polystyrene (aPS) immiscible with P3HT tended to form the phase‐separated and columnar structure at low aPS weight ratio. Besides, the aPS could migrate to the surface of the films with PCBM phase distributing in the interfaces between P3HT and aPS domains at high aPS weight ratio of 75 wt %. The syndiotactic polystyrene (sPS) immiscible with P3HT could induce the crystallization of P3HT at low weight ratio of 3 wt %. The device based on aPS/P3HT/PCBM ternary blend showed of power conversion efficiency (PCE) of 1.2% even at aPS weight ratio of 50 wt %. However, the device based on sPS/P3HT/PCBM exhibited a sharp decrease in PCE value from 2.3% to 0.6% at sPS weight ratio of 3 wt %, due to the change in film morphology. The performance of the solar cell is believed to be determined by the morphology and phase structure of the ternary blends as revealed by the atomic force microscopy and UV‐vis spectra analysis. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41823.