Comparative evaluation of different recycling modes for decommissioned photovoltaic products based on stackelberg game.

China is the photovoltaic (PV) leader worldwide and will be confronted with significant challenges stemming from the scrap tide of PV products. Constructing an effective recycling system is essential for retired PV product management. Using the Stackelberg game theory, this study establishes and compares three recycling modes including manufacturer recycling, third-party recycling, and producer responsibility organization (PRO) recycling for decommissioned PV products. Afterward, the effects of module processing costs, echelon utilization rates, and collection subsidies on the transfer prices, collection quantities, supply chain profits, and carbon emissions of the various recycling modes are simulated and analyzed. The results reveal that: (1) The manufacturer recycling realizes optimal supply chain profits; (2) Compared to the PRO recycling mode, the third-party recycling experiences superior performances when retired module processing costs are lower than a specific threshold; (3) Uplifting echelon utilization rates and collection subsidies while reducing module processing costs could supplement the overall economic and environmental benefits within the PV closed-loop supply chain (CLSC); (4) Environmental performances of the different recycling modes are associated with the carbon emission reduction efficiency. Accordingly, valuable insights are provided for manufacturers, recyclers, and governments to develop a sustainable retired PV product recycling system.

Fault Detection and Classification of CIGS Thin-Film PV Modules Using an Adaptive Neuro-Fuzzy Inference Scheme.

The use of artificial intelligence to automate PV module fault detection, diagnosis, and classification processes has gained interest for PV solar plants maintenance planning and reduction in expensive inspection and shutdown periods. The present article reports on the development of an adaptive neuro-fuzzy inference system (ANFIS) for PV fault classification based on statistical and mathematical features extracted from outdoor infrared thermography (IRT) and I-V measurements of thin-film PV modules. The selection of the membership function is shown to be essential to obtain a high classifier performance. Principal components analysis (PCA) is used to reduce the dimensions to speed up the classification process. For each type of fault, effective features that are highly correlated to the PV module's operating power ratio are identified. Evaluation of the proposed methodology, based on datasets gathered from a typical PV plant, reveals that features extraction methods based on mathematical parameters and I-V measurements provide a 100% classification accuracy. On the other hand, features extraction based on statistical factors provides 83.33% accuracy. A novel technique is proposed for developing a correlation matrix between the PV operating power ratio and the effective features extracted online from infrared thermal images. This eliminates the need for offline I-V measurements to estimate the operating power ratio of PV modules.

Redundant Fault Diagnosis for Photovoltaic Systems Based on an IRT Low-Cost Sensor.

In large solar farms, supervision is an exhaustive task, often carried out manually by field technicians. Over time, automated or semi-automated fault detection and prevention methods in large photovoltaic plants are becoming increasingly common. The same does not apply when talking about small or medium-sized installations, where the cost of supervision at such level would mean total economic infeasibility. Although there are prevention protocols by suppliers, periodic inspections of the facilities by technicians do not ensure that faults such as the appearance of hot-spots are detected in time. That is why, nowadays, the only way of continuous supervision of a small or medium installation is often carried out by unqualified people and in a purely visual way. In this work, the development of a low-cost system prototype is proposed for the supervision of a medium or small photovoltaic installation based on the acquisition and treatment of thermographic images, with the aim of investigating the feasibility of an actual implementation. The work focuses on the system's ability to detect hot-spots in supervised panels and successfully report detected faults. To achieve this goal, a low-cost thermal imaging camera is used for development, applying common image processing techniques, operating with OpenCV and MATLAB R2021b libraries. In this way, it is possible to demonstrate that it is achievable to successfully detect the hottest points of a photovoltaic (PV) installation with a much cheaper camera than the cameras used in today's thermographic inspections, opening up the possibilities of creating a fully developed low-cost thermographic surveillance system.

Predictive Fault Diagnosis for Ship Photovoltaic Modules Systems Applications.

In this paper, an application for the management and supervision by predictive fault diagnosis (PFD) of solar power generation systems is developed through a National Marine Electronics Association (NMEA) 2000 smart sensor network. Here, the NMEA 2000 network sensor devices for measuring and supervising the parameters inherent to solar power generation and renewable energy supply are applied. The importance of renewable power generation systems in ships is discussed, as well as the causes of photovoltaic modules (PVMs) aging due to superimposed causes of degradation, which is a natural and inexorable phenomenon that affects photovoltaic installations in a special way. In ships, PVMs are doubly exposed to inclement weather (solar radiation, cold, rain, dust, humidity, snow, wind, electrical storms, etc.), pollution, and a particularly aggressive environment in terms of corrosion. PFD techniques for the real-world installation and safe navigation of PVMs are discussed. A specific method based on the online analysis of the time-series data of random and seasonal I-V parameters is proposed for the comparative trend analyses of solar power generation. The objective is to apply PFD using as predictor symptom parameter (PS) the generated power decrease in affected PVMs. This PFD method allows early fault detection and isolation, whose appearance precedes by an adequate margin of maneuver, from the point of view of maintenance tasks applications. This early detection can stop the cumulative degradation phenomenon that causes the development of the most frequent and dangerous failure modes of solar modules, such as hot-spots. It is concluded that these failure modes can be conveniently diagnosed by performing comparative trend analyses of the measured power parameters by NMEA sensors.

An adaptive snake optimization algorithm incorporating Subtraction-Average-Based Optimizer for photovoltaic cell parameter identification.

Accurate parameter identification of photovoltaic (PV) models is essential for the optimal operation and control of PV systems. However, PV cell modeling exhibits nonlinearity and involves numerous challenging-to-solve unknown parameters, thereby reducing the utilization efficiency of solar energy in PV systems. Therefore, this paper proposes an enhanced Snake algorithm (ISASO) that integrates Subtraction Average-Based Optimization (SABO) to address the shortcomings of traditional PV model parameter identification methods, such as low accuracy, slow convergence, and susceptibility to local optima. The SABO algorithm, which updates the positions of search agents using a consistent arithmetic mean position throughout the optimization process, demonstrates high convergence. By integrating SABO's global search strategy into the exploration phase of SO, the global search capability of SO is further enhanced, mitigating the risk of early local optima in the original SO. Additionally, the Tent chaotic map initialization method is incorporated into standard SO to improve the quality of the initial population and enhance population diversity. A dynamic learning factor and adaptive inertia weight strategy are also employed to accelerate the convergence speed of the SO algorithm, balancing its exploration and exploitation capabilities. To validate the performance of ISASO, it is applied to the CEC2005 benchmark functions and employed to identify the optimal parameters of various PV models. Statistical and analytical results reveal that ISASO markedly outperforms existing methods in parameter identification accuracy and reliability, achieving the lowest Root Mean Square Error (RMSE) values between standard and simulated data. Additionally, the superior performance of ISASO is further verified by comparative analysis with existing meta-heuristic algorithms and the Friedman mean ranking statistical method. Therefore, ISASO can be considered as a reliable and effective method to accurately estimate solar PV model parameters.

Laser-Induced Backward Transfer of Light Reflecting Zinc Patterns on Glass for High Performance Photovoltaic Modules.

Commercially available photovoltaic (PV) modules typically consist of individual silicon half-cut cells that are electrically interconnected. This interconnection method results in gaps between the cells, which do not contribute to the overall PV output power. One approach to enhance the cell-to-module power ratio is the placement of white, diffuse reflecting plastic material within these gaps. Conventionally, the process of generating reflective patterns involves several discrete steps, including film deposition, resist patterning, etching, and resist stripping. This study presents an innovative single-step procedure for the direct deposition of zinc reflective patterns onto glass substrates using laser-induced backward transfer (LIBT) and a nanosecond pulsed laser system. The process successfully produced lines and squares, demonstrating its versatility in achieving diverse geometric patterns under ambient atmospheric pressure and room temperature conditions. The evaluation of the transferred patterns included an examination of geometric dimensions and surface morphology using a 3D microscope and scanning electron microscopy (SEM) analysis at the air/Zn interface. Additionally, the thickness of the zinc film and its adhesion to the glass substrate were quantified. The angular reflectance at a wavelength of 660 nm for both the glass/Zn and air/Zn interfaces was measured.

Characterization of dust particles in South India and investigation on soiling image analysis for photovoltaic application.

The present work aims at the characterization of the dust particles in South India through an image analysis of glass samples inclined at a tilt of 0° and 13° for four different exposure periods (approximately 30 to 40 days/exposure period). It aims as well at the study of the different factors influencing the accuracy of the image analysis of dust particles. The analysis of the shape factor reveals that the dust particles on tilted surface (13°) have regular shapes, and irregular shapes are more observed in horizontal surfaces. The size analysis of the dust particles with magnification of 20 × has revealed that the size distribution is in the range of 0-4 µm but more concentrated in the range of 0-1 µm. However, with 10 × magnification, larger particles are more detected. Furthermore, average results from three sample images seem to be more precise and representative than results from two images. The fractional coverage area of the dust particles on the sample has been calculated and compared with the transmittance losses. These two variables are found to be proportional with an R2 of 53%. Nevertheless, the comparison showed again that three images give better results with an R2 of 75% against 11% for two images. The results obtained in this study are very useful for the development of high precision soiling sensors that are based on image analysis and outdoor soiling microscopes, which are the main components for an efficient and economic cleaning of solar PV modules.

Durability and Performance of Encapsulant Films for Bifacial Heterojunction Photovoltaic Modules.

Energy recovery from renewable sources is a very attractive, and sometimes, challenging issue. To recover solar energy, the production of photovoltaic (PV) modules becomes a prosperous industrial certainty. An important material in PV modules production and correct functioning is the encapsulant material and it must have a good performance and durability. In this work, accurate characterizations of performance and durability, in terms of photo- and thermo-oxidation resistance, of encapsulants based on PolyEthylene Vinyl Acetate (EVA) and PolyOlefin Elastomer (POE), containing appropriate additives, before (pre-) and after (post-) lamination process have been carried out. To simulate industrial lamination processing conditions, both EVApre-lam and POEpre-lam sheets have been subjected to prolonged thermal treatment upon high pressure. To carry out an accurate characterization, differential scanning calorimetry, rheological and mechanical analysis, FTIR and UV-visible spectroscopy analyses have been performed on pre- and post-laminated EVA and POE. The durability, in terms of photo- and thermo-oxidation resistance, of pre-laminated and post-laminated EVA and POE sheets has been evaluated upon UVB exposure and prolonged thermal treatment, and the progress of degradation has been monitored by spectroscopy analysis. All obtained results agree that the lamination process has a beneficial effect on 3D-structuration of both EVA and POE sheets, and after lamination, the POE shows enhanced rigidity and appropriate ductility. Finally, although both EVA and POE can be considered good candidates as encapsulants for bifacial PV modules, it seems that the POE sheets show a better resistance to oxidation than the EVA sheets.

Seawater cooling of PV modules mounted on ships in Swinoujscie/Poland harbour.

New international marine regulations concerning sea transport indicate that one of the ways to meet them is the use of renewable energy sources (RES) on ships. The PV installation mounted on ships is one of solutions. Cooling of PV modules is a way to improve their capacity. The paper presents results of calculation on capacity of PV modules mounted on ships where seawater is used as cooling agent. The calculations were carried out for conditions prevailing in the harbour Swinoujscie/Poland. The aim of this paper is to compare PV module's power gain in six characteristic months (January to June) of the statistic year. Analysis of the results obtained for Swinoujscie shows that application of seawater in cooling systems of PV modules on ships is justified only for spring and summer seasons.

Study of a dust deposition mechanism dominated by electrostatic force on a solar photovoltaic module.

Solar energy is one of the most promising renewable energy sources to solve the energy crisis. Dust deposition on solar photovoltaic (PV) modules significantly reduces the power generation of PV power plants. In this paper, the motion characteristics of the gas phase and charging mechanism of dust particles and solar PV glass are investigated by means of the computational fluid dynamics-discrete element model (CFD-DEM) method. In addition, the mechanism and characteristics of dust deposition on a solar PV module as dominated by electrostatic force are discussed. The research results show that frequent collisions between dust particles and PV glass or between dust particles lead to charging. The dust deposition mechanism on a solar PV module is a gas-solid-electrical multi-directional coupling process. There is a great electrostatic field near the solar PV glass, causing charged dust particle deposition. The dust deposition density decreases when the air inlet velocity increases and when the tilt angle of the solar PV module or the number of particle collisions decreases. Different particle dynamics have different dust deposition ratios for different predominant deposition forces (such as the electrostatic force, van der Waals force, and gravity force). The research findings provide an important theoretical basis for dust deposition prevention and removal from solar PV modules.

Assessment of soiling effect on PV module glass transmittance in Moroccan capital region.

This work is a first part of the study in development on the mapping of soiling losses in the region of Rabat-Sale-Kenitra in Morocco. To perform the work, two holders of glass samples have been constructed and installed in two different sites of Sale City for three successive periods (from April to June 2019). At the end of each period, the transmittance losses of the glass samples as well as the mass of deposited soils are systematically measured. SEM (scanning electronic microscopy) analyses are also performed for more investigation and deep understanding. The obtained results show that the relationship between soil mass density and glass transmittance loss is not always linear as could be expected. They also show that soiling losses are strongly depending on the environment and nature of the surrounding installation spaces. The SEM analysis results of the 1st period and the inclined surfaces have shown that particles are greater in the range of 2-11 µm and the majority tends to have a regular shape in the two sites. Nevertheless, the frequencies are different. From this study, it can be concluded that it is highly recommended characterizing the site where soiling measurements are conducted not only by its location/city but also by its environment characteristics.

PV cells and modules - State of the art, limits and trends.

The key components of photovoltaic (PV) systems are PV modules representing basic devices, which are able to operate durably in outdoor conditions. PV modules can be manufactured using different materials by different fabrication technologies. The main criteria supporting or limiting a successful placement of particular technologies on the market is the cost of electricity produced by PV systems. The Levelized Cost of Energy (LCOE) method takes into account the investment cost, the operating costs, and the total energy produced during the system service life. The influence of price, efficiency and service life of PV modules on LCOE (together with the availability of materials) sets limits for applicable technologies. Over the past 15 years a categorisation of generations of PV cell and module technology groups has been frequently used. The main features of individual technology groups are discussed from the view of the above criteria. Currently, PV modules are required to have: efficiency higher than 14%, price below 0.4 USD/Wp and service life of more than 15 years. At present, the wafer-based crystalline silicon technologies have best met the criteria due to their high efficiency, low cost and long service time; and due to the abundance of materials, they are set to lead in future PV power generation.

Behavioral data of thin-film single junction amorphous silicon (a-Si) photovoltaic modules under outdoor long term exposure.

Four years׳ behavioral data of thin-film single junction amorphous silicon (a-Si) photovoltaic (PV) modules installed in a relatively dry and sunny inland site with a Continental-Mediterranean climate (in the city of Jaén, Spain) are presented in this article. The shared data contributes to clarify how the Light Induced Degradation (LID) impacts the output power generated by the PV array, especially in the first days of exposure under outdoor conditions. Furthermore, a valuable methodology is provided in this data article permitting the assessment of the degradation rate and the stabilization period of the PV modules. Further discussions and interpretations concerning the data shared in this article can be found in the research paper "Characterization of degradation and evaluation of model parameters of amorphous silicon photovoltaic modules under outdoor long term exposure" (Kichou et al., 2016) [1].