太阳能光伏-光热复合发电技术及其商业化应用

由于太阳能自身的间歇性和不稳定性,提高太阳能发电并网的质量成为近年来的研究热点。太阳能光伏-光热（photovoltaic/concentrated solar power,PV-CSP）复合发电技术作为一种新兴技术,相比于单独的太阳能光伏（PV）和太阳能热（CSP）发电技术具有诸多优势,目前已有多种技术形式实现了商业化。介绍了PV、CSP发电技术及PV-CSP复合发电技术,通过一些典型商业化PV-CSP复合电站的建设及运行情况,分析了当今商业化PV-CSP复合电站的应用现状,并综述了近年来对PV-CSP复合发电系统的技术和经济性研究情况。     

基于混沌搜索的改进狮群算法及其在光伏电池参数辨识中的应用

目前已有多种智能算法应用到光伏电池模型的参数辨识中,然而大都存在易陷入局部最优、收敛速度慢等问题,基于改进狮群算法,提出了一种有效的光伏电池参数辨识方法.首先,通过引入混沌初始化、自适应参数和混沌搜索,弥补了狮群算法收敛速度慢、寻优精度不高等不足;将改进狮群算法应用到光伏电池的单二极管模型和双二极管模型的参数辨识中,与...     

光伏太阳能电池厂房空调系统的改革

在当今能源日趋紧张、环境压力日趋增大的情况下,可再生能源受到各国政府的日益重视,太阳能作为一种永续利用的清洁能源,其开发和利用已成为各国可持续发展战略的重要组成部分。太阳能电池产业也成为世界快速、稳步发展的朝阳产业之一,最近10年世界太阳能电池及组件生产的年平均增长率达到40%,最近5年的年平均增长率达到45%,并将维持几十年的快速增长,技术工艺改进日新月异,与其配套的太阳能厂房空调系统也受到越来越多的人重视,如果能够设计一种无论厂房工艺设备动力需求如何变化,只需略加调整就可继续满足新工艺条件下的空调系统,将会为企业赢得时间的优势,提高企业的市场竞争力。     

An optimized metal grid design to improve the solar cell performance under solar concentration using multiobjective computation

In this paper, a new multiobjective genetic algorithm (MOGA)-based approach is proposed to optimize the metal grid design in order to improve the electrical performance and the conversion efficiency behavior of the solar cells under high intensities of illumination. The proposed approach is applied to investigate the effect of two different metal grid patterns (one with 2 busbars outside the active area (linear grid) and another one with a circular busbar surrounding the active area (circular grid)) on the electrical performance of high efficiency c-Si solar cells under concentrated light (up to 150 suns). The dimensional and electrical parameters of the solar cell have been ascertained, and analytical expressions of the power losses and conversion efficiency, including high illumination effects, have been presented. The presented analytical models are used to formulate different objective functions, which are the prerequisite of the multiobjective optimization. The optimized design can also be incorporated into photovoltaic circuit simulator to study the impact of our approach on the photovoltaic circuit design.     

基于IHHO算法的光伏电池工程模型的参数辨识

针对HHO算法存在搜索过程调整不够灵活,不能针对性地进行阶段性搜索,有时会陷入局部最优使算法搜索精度相对较差等问题,提出了一种基于改进哈里斯鹰优化(IHHO)算法的参数辨识方法.对HHO算法进行了两项改进:引人柔性递减策略,在迭代初期扩大全局搜索范围,在迭代后期延长局部搜索时间,从而加强了初期的全局搜索能力和后期的局部...     

新型光伏储电原位集成电池研究进展

随着光伏智能电子产品日益融入到日常生活,人们不仅对高性能光伏发电设备的需求增加,同时对智能化、可持续和快速充电/放电能源集成设备的需求也急剧增加,将能量产生部件和能量存储部件结合成独立设备已经成为一种极具有吸引力和挑战性的前沿技术。原位逐层制备光电转换功能薄膜与储电功能薄膜并组装,获得光伏储电原位集成电池的技术,既减少了太阳光波动对能量输出的影响,又可以实现光伏自供电、弱光缓冲和可穿戴等功能,因此具有良好的发展前景。本文综述了硅基光伏储电原位集成电池、敏化光伏储电原位集成电池、钙钛矿光伏储电原位集成电池的最新研究成果,介绍了此类新型电池性能的评价方法,分析了其工作原理、构造特点和性能参数,并对此新兴研究领域的发展趋势进行了展望。     

A Highly Versatile and Adaptable Artificial Leaf with Floatability and Planar Compact Design Applicable in Various Natural Environments

As a promising means of solar energy conversion, photovoltaic (PV) cell‐based electrolysis has recently drawn considerable attention for its effective solar fuel generation; especially the generation of hydrogen by solar water splitting. Inspired by remarkable accomplishments in enhancing the solar‐to‐hydrogen conversion efficiency, various efforts have aimed at fostering convenient and practical uses of PV electrolysis to make this technology ubiquitous, manageable, and efficient. Here, the design and function of a monolithic photoelectrolysis system—a so‐called artificial leaf—for use in various environments are highlighted. The uniquely designed artificial‐leaf system facilitates an unbiased water‐splitting reaction by combining superstrate PV cells in series with single‐face electrodes in a compact 2D catalytic configuration. Floatability is a new feature of the water‐splitting artificial leaf; this feature maximizes solar light utilization and allows for easy retrieval for recycling. Additionally, its planar design enables operation of the device in water‐scarce conditions. These characteristics endow the artificial leaf with versatility and a high adaptability to natural environments, widening the applicability of the device.     

Squeeze-and-breathe evolutionary Monte Carlo optimization with local search acceleration and its application to parameter fitting

Estimating parameters from data is a key stage of the modelling process, particularly in biological systems where many parameters need to be estimated from sparse and noisy datasets. Over the years, a variety of heuristics have been proposed to solve this complex optimization problem, with good results in some cases yet with limitations in the biological setting. In this work, we develop an algorithm for model parameter fitting that combines ideas from evolutionary algorithms, sequential Monte Carlo and direct search optimization. Our method performs well even when the order of magnitude and/or the range of the parameters is unknown. The method refines iteratively a sequence of parameter distributions through local optimization combined with partial resampling from a historical prior defined over the support of all previous iterations. We exemplify our method with biological models using both simulated and real experimental data and estimate the parameters efficiently even in the absence of a priori knowledge about the parameters.     

钙钛矿太阳能电池的研究进展

钙钛矿太阳能电池由纳米晶致密层、钙钛矿型光活性层CH₃NH₃PbX₃ (X= Cl、Br、I)、空穴传输层及对电极组成。其中光活性层吸光材料的种类及其成膜技术、空穴传输层材料类型及结构设计是影响钙钛矿太阳能电池光电性能的重要因素。本文结合钙钛矿太阳能电池近年来的最新研究进展, 对影响器件光电性能的关键因素: 光吸收层、空穴传输层、工艺参数以及结构设计等进行综述, 同时展望了钙钛矿太阳能电池未来的发展趋势。     

Material challenges for solar cells in the twenty-first century: directions in emerging technologies

Photovoltaic generation has stepped up within the last decade from outsider status to one of the important contributors of the ongoing energy transition, with about 1.7% of world electricity provided by solar cells. Progress in materials and production processes has played an important part in this development. Yet, there are many challenges before photovoltaics could provide clean, abundant, and cheap energy. Here, we review this research direction, with a focus on the results obtained within a Japan–French cooperation program, NextPV, working on promising solar cell technologies. The cooperation was focused on efficient photovoltaic devices, such as multijunction, ultrathin, intermediate band, and hot-carrier solar cells, and on printable solar cell materials such as colloidal quantum dots.     

Silicon nanowires for photovoltaic solar energy conversion

Semiconductor nanowires are attracting intense interest as a promising material for solar energy conversion for the new-generation photovoltaic (PV) technology. In particular, silicon nanowires (SiNWs) are under active investigation for PV applications because they offer novel approaches for solar-to-electric energy conversion leading to high-efficiency devices via simple manufacturing. This article reviews the recent developments in the utilization of SiNWs for PV applications, the relationship between SiNW-based PV device structure and performance, and the challenges to obtaining high-performance cost-effective solar cells.     

Absorption enhancement in silicon nanowire-optical nanoantenna system for photovoltaic applications

The rapidly growing green energy sector has prompted the search for new solutions to increase the performance of solar cells. In this area there is still room for the silicon-based photovoltaic, although the main problem is to find a way to increase the efficiency of the silicon solar cells, at the lowest possible cost. In this work we investigate the influence of a gold bowtie nanoantenna on the absorption profile of silicon nanowire. Because of the energy band gap and low effective absorption cross section, bulk silicon absorbs rather poorly in longer wavelengths of visible light and near-infrared range. Our calculations with frequency domain solver show the absorption boost in nanowire at long-wavelengths due to the coupling of the large local near-field of metallic bowtie nanoantenna to the semiconductor layer. The enhancement was observed at various levels although it was correlated with the shift of localized surface plasmon resonance thus making it dependent on the bowtie geometry. The results suggest that by incorporating metallic nanostructures as well as nanoparticles to the nanowire system, the performance of photovoltaic device can be improved thanks to greater generation of a electron–hole pairs.     

高效率双结钙钛矿叠层太阳能电池研究进展

以钙钛矿电池为顶电池的叠层太阳电池发展迅速,成为太阳能光伏领域的研究热点之一。随着电池结构和制备工艺的优化,叠层电池的光电转换效率快速提升,单片钙钛矿/晶硅叠层电池的效率已达到31.3%。本综述对近年来以宽带隙钙钛矿电池作为顶子电池、晶体硅电池及其他新型中窄带隙电池(钙钛矿电池、有机电池、铜铟镓硒(CIGS)电池)作为底子电池的叠层电池的研究进展进行了系统梳理,总结了叠层电池的顶电池、中间互联层和底电池的材料、结构及光电性能等方面的关键技术及难点,希望能够为进一步提升叠层电池效率提供一些思路。并对未来低成本高效叠层太阳能电池的光学和电学优化需求做出了分析与展望。     

Wind Power Prediction Based on Machine Learning and Deep Learning Models

Wind power is one of the sustainable ways to generate renewable energy. In recent years, some countries have set renewables to meet future energy needs, with the primary goal of reducing emissions and promoting sustainable growth, primarily the use of wind and solar power. To achieve the prediction of wind power generation, several deep and machine learning models are constructed in this article as base models. These regression models are Deep neural network (DNN), k-nearest neighbor (KNN) regressor, long short-term memory (LSTM), averaging model, random forest (RF) regressor, bagging regressor, and gradient boosting (GB) regressor. In addition, data cleaning and data preprocessing were performed to the data. The dataset used in this study includes 4 features and 50530 instances. To accurately predict the wind power values, we propose in this paper a new optimization technique based on stochastic fractal search and particle swarm optimization (SFS-PSO) to optimize the parameters of LSTM network. Five evaluation criteria were utilized to estimate the efficiency of the regression models, namely, mean absolute error (MAE), Nash Sutcliffe Efficiency (NSE), mean square error (MSE), coefficient of determination (R²), root mean squared error (RMSE). The experimental results illustrated that the proposed optimization of LSTM using SFS-PSO model achieved the best results with R² equals 99.99% in predicting the wind power values.     

Optical management for efficiency enhancement in hybrid organic-inorganic lead halide perovskite solar cells

In a few years only, solar cells using hybrid organic–inorganic lead halide perovskites as optical absorber have reached record photovoltaic energy conversion efficiencies above 20%. To reach and overcome such values, it is required to tailor both the electrical and optical properties of the device. For a given efficient device, optical optimization overtakes electrical one. Here, we provide a synthetic review of recent works reporting or proposing so-called optical management approaches for improving the efficiency of perovskite solar cells, including the use of anti-reflection coatings at the front substrate surface, the design of optical cavities integrated within the device, the incorporation of plasmonic or dielectric nanostructures into the different layers of the device and the structuration of its internal interfaces. We finally give as outlooks some insights into the less-explored management of the perovskite fluorescence and its potential for enhancing the cell efficiency.     

基于改进蝗虫优化算法的光伏电池模型参数辨识

针对蝗虫优化算法容易陷入局部最优、收敛精度不足等缺点,提出一种改进蝗虫优化算法。将混沌算法与蝗虫优化算法融合,对蝗虫优化算法进行混沌初始化,改善初始种群质量;再引入差分进化算法的差分策略,通过变异、交叉和选择过程,维持种群的多样性,增大算法跳出局部最优的可能性,从而使算法能搜索到更好的解;在个体更新部分引入了粒子群算法的思想,以当前的最优个体为目标进行个体位置更新,加快算法寻优速度。将改进蝗虫优化算法用于多晶硅太阳能电池模型参数的辨识中,并通过与其它智能优化算法的比较,验证了改进蝗虫算法辨识太阳能电池参数的有效性和优越性。通过实验验证了改进蝗虫优化算法在不同光照下对太阳能电池参数的辨识效果。     

Naphthalenediimide (NDI) polymers for all-polymer photovoltaics

Naphthalenediimide (NDI) polymers are an important class of electron-accepting (acceptor or n-type) semiconductors for organic photovoltaic (OPV) or organic solar cell (OSC) applications. Blending them with compatible electron-donating (donor or p-type) polymers yields an OPV device known as bulk-heterojunction (BHJ) all-polymer solar cells (all-PSCs). Compared to the more extensively studied OPVs using fullerene derivatives as the acceptor material, all-PSCs provide important benefits such as chemical tunability, mechanical flexibility and ambient/stress stability. Through an extensive research on materials design and device optimization in the last five years, all-PSCs employing NDI-based polymers have achieved remarkable improvement in device power conversion efficiency (PCE), now surpassing 10% – a number that approaches the state-of-the-art organic photovoltaic (OPV) cells using fullerenes. In this review, recent development of NDI-based conjugated polymers used in all-PSCs will be highlighted.     

Spectrally selective reflector surfaces for heat reduction in concentrator solar cells: modeling and applications of TiO₂:Nb-based thin films

The energy conversion efficiency of a conventional pn junction solar cell decreases as the temperature increases, and this may eventually lead to failures in the photovoltaic system, especially if it uses concentrated solar radiation. In this work, we show that spectrally selective reflector (SSR) surfaces can be important for reducing the heat buildup on passively cooled solar cells. We outline a computational scheme for optimizing DC magnetron-sputtered TiO?:Nb-based SSRs tailored for silicon solar cells and find good agreement of the reflectance with an experimental realization of the optimal SSR. A figure of merit for SSRs has also been derived and applied to the experimental data.     

Integrated solar capacitors for energy conversion and storage

Solar energy is one of the most popular clean energy sources and is a promising alternative to fulfill the increasing energy demands of modern society.Solar cells have long been under intensive research attention for harvesting energy from sunlight with a high power-conversion efficiency and low cost.However,the power outputs of photovoltaic devices suffer from fluctuations due to the intermittent instinct of the solar radiation.Integrating solar cells and energystorage devices as self-powering systems may solve this problem through the simultaneous storage of the electricity and manipulation of the energy output.This review summarizes the research progress in the integration of new-generation solar cells with supercapacitors,with emphasis on the structures,materials,performance,and new design features.The current challenges and future prospects are discussed with the aim of expanding research and development in this field.     

Photovoltaics in the assessment of wireless sensor network reliability with changing environmental conditions

This paper presents a reliability assessment of a wireless sensor network (WSN) equipped with mini photovoltaic cells (PV‐WSN) under natural environmental conditions while accounting for different types of system failures. In particular, our assessment considers the hardware specifications of the sensors, photovoltaic (PV) specifications, the use of rechargeable batteries, communication protocols, and various elements required for efficient detection of environmental conditions. We accomplished this by developing a simulator that generated data for 2 broad WSN conditions: (1) WSN without PV and (2) WSN with PV. The dynamic source routing protocol was employed for these simulations, and the following variables were assessed for both conditions: WSN reliability, the impact of energy consumption on the network, and the types of failures that lead to sensor unavailability. The following assumptions were made to run the simulation: the distribution of WSN nodes is random, with 1 sink node per rectangular cluster, the sensor nodes are structurally and functionally identical, environmental interference and suboptimal orientation impair PV cell recharge capacity randomly, and no communication loss occurs. Our reliability assessment assumed extreme environmental conditions and further made assessments of component reliability that included the following parameters: sensor and PV cell hardware specifications, the rechargeable nature of PV cell batteries for different sensor activity states, the availability of sunlight for powering PV cells, and the energy efficiency of PV cells. We found that network lifetime was prolonged for the PV‐WSN condition over the WSN without PV condition, introducing a role for PV cells as potential energy sources for WSNs.