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Study of solar irradiance and performance analysis of submerged monocrystalline and polycrystalline solar cells
摘要： Underwater photovoltaic (PV) systems supported with modern-day technology can lead to possible solutions for the lack of long-term power sources in marine electronics, navy corps, and many other remotely operated underwater power systems. Currently, most of these systems are powered by conventional batteries, which are bulky, costly, and require periodic maintenance and replacement. Harnessing the underwater Solar energy by using Solar PV cells is simple, reliable, and leads to tremendous advantageous as water itself provides cooling, cleaning, and avoid challenges due to land constraints. The present work encompasses an experimental study on Solar radiation in water and its changes with varying water conditions. Accordingly, the performance of monocrystalline and polycrystalline silicon solar cells with different submerged water conditions and water depths up to 20 cm has been studied. Most importantly, these studies have been carried out with different types of water conditions, consisting of salinity, bacteria, algae, and other water impurities. These investigation results manifest that the percentage decrease of maximum power output in monocrystalline and polycrystalline Solar cells is 65.85% and 62.55%, respectively, in the case of ocean water conditions, whereas in deionized (DI) water conditions, it is 63.06% and 60.72% up to 20 cm. Such results conclude that valuable amount of Solar energy is can be explored underwater. These experimental studies pave the way to explore further to utilize Solar PV cells efficiently in underwater conditions.
关键词： monocrystalline Solar cell,underwater Solar radiation,photovoltaic (PV) technology,PDMS (polydimethylsiloxane),water salinity,polycrystalline Solar cell
更新于2025-09-23 15:21:01
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A multistate investigation of a solar dryer coupled with photovoltaic thermal collector and evacuated tube collector
摘要： In this study, an indirect solar dryer was designed and manufactured using a Photovoltaic Thermal (PV/T) collector and Evacuated Tube (ET) collector. The main objectives of this system were to supply the thermal load of the indirect solar dryer, to ?nd the best model for the drying process, to present a new model to predict the drying process of Tarkhineh (the drying material) and to perform its life-cycle cost analysis (LCCA). The manufactured system was tested under the weather conditions of Sanandaj city, Iran and was compared with open sun drying. When the auxiliary heater was not used, the new model 1 was the best model to describe the drying of Tarkhineh in the open sun mode and the new model 2 was the best model to describe the drying of Tarkhineh in the solar dryer designed and manufactured in this study. The new models 1 and 2 were found to be the best models for describing the drying process of Tarkhineh at set point temperatures 55 °C and 45 °C, supplied by the auxiliary heater, respectively. The payback period of the PV/T solar dryer and ET solar dryer, assuming 300 sunny days/year, were 2.3 and 2.5 years, respectively.
关键词： Evacuated tube collector,Photovoltaic thermal (PV/T) collector,Payback period,Tarkhineh,Models of drying,Solar dryer
更新于2025-09-23 15:21:01
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Application of Generalized Regression Neural Network in Predicting the Performance of Solar Photovoltaic Thermal Water Collector
摘要： Solar photovoltaic thermal water collector (SPV/T-WC) is a hybrid device which converts power from the solar energy in to thermal and electrical simultaneously. The performance of such SPV/T-WC mainly depends on its electrical and thermal power output. Besides the performance of SPV/T-WC, is more sensitive to the transient nature of electrical and thermal power output. Thus a demand for predicting the performance variations in the SPV/T-WC is demand by users. Only limited performance prediction based research works are attempted in the performance prediction of the SPV/T-WC either numerically or by using cognitive models. In this study, two generalized regression neural network (GRNN) models are proposed to predict the transient performance variations in the SPV/T-WC. The two individual objectives of the ?rst and second model include the prediction of overall power output and the overall ef?ciency delivered by an SPV/T-WC system. Both the GRNN models proposed in this study consist of two inputs and single output. In order to train this GRNN model, real time experiments are conducted with stand-alone SPV/T-WC for four continuous days. Then based on such experimental data sets, GRNN models are trained, tested, and validated. The results predicted by the both GRNN models are in good agreement with the real time experimental results. The overall accuracy of the proposed GRNN models in predicting the performance is 95.36% and 96.22% respectively.
关键词： Solar,Water,Collector,Thermal,accuracy,Photovoltaic,GRNN,Prediction
更新于2025-09-23 15:21:01
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Day-ahead photovoltaic power production forecasting methodology based on machine learning and statistical post-processing
摘要： A main challenge towards ensuring large-scale and seamless integration of photovoltaic systems is to improve the accuracy of energy yield forecasts, especially in grid areas of high photovoltaic shares. The scope of this paper is to address this issue by presenting a uni?ed methodology for hourly-averaged day-ahead photovoltaic power forecasts with improved accuracy, based on data-driven machine learning techniques and statistical post-processing. More speci?cally, the proposed forecasting methodology framework comprised of a data quality stage, data-driven power output machine learning model development (arti?cial neural networks), weather clustering assessment (K-means clustering), post-processing output optimisation (linear regressive correction method) and the ?nal performance accuracy evaluation. The results showed that the application of linear regression coe?cients to the forecasted outputs of the developed day-ahead photovoltaic power production neural network improved the performance accuracy by further correcting solar irradiance forecasting biases. The resulting optimised model provided a mean absolute percentage error of 4.7% when applied to historical system datasets. Finally, the model was validated both, at a hot as well as a cold semi-arid climatic location, and the obtained results demonstrated close agreement by yielding forecasting accuracies of mean absolute percentage error of 4.7% and 6.3%, respectively. The validation analysis provides evidence that the proposed model exhibits high performance in both forecasting accuracy and stability.
关键词： Performance,Forecasting,Machine learning,Photovoltaic,Arti?cial neural networks,Clustering
更新于2025-09-23 15:21:01
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Data-driven uncertainty analysis of distribution networks including photovoltaic generation
摘要： This paper investigates residential distribution networks with uncertain loads and photovoltaic distributed generation. An original probabilistic modeling of consumer demand and photovoltaic generation is presented that is based on the analysis of large set of data measurements. It is shown how photovoltaic generation is described by complex non-standard distributions that can be described only numerically. Probabilistic analysis is performed using an enhanced version of the Polynomial Chaos technique that exploits a proper set of polynomial basis functions. It is described how such functions can be generated from the numerically available data. Compared to other approximate methods for probabilistic analysis, the novel technique has the advantages of modeling accurately truly nonlinear problems and of directly providing the detailed Probability Density Function of relevant observable quantities affecting the quality of service. Compared to standard Monte Carlo method, the proposed technique introduces a simulation speedup that depends on the number of random parameters. Numerical applications to radial and weakly meshed networks are presented where the method is employed to explore overvoltage, unbalance factor and power loss, as a function of photovoltaic penetration and/or network configuration.
关键词： Photovoltaic generation,Data-driven models,Polynomial chaos,Unbalanced distribution networks,Probabilistic load flow,Uncertainty Analysis
更新于2025-09-23 15:21:01
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Thiazolo[5,4- <i>d</i> ]thiazole-based organic sensitizers with improved spectral properties for application in greenhouse-integrated dye-sensitized solar cells
摘要： Organic photosensitizers especially designed for producing semitransparent dye-sensitized solar cells (DSSCs) for greenhouse integration were prepared by introduction of different heterocyclic moieties into the thiazolo[5,4-d]thiazole-molecular scaffold. The aim was that of improving their light absorption capability in the green part of the visible spectrum while maintaining a good transparency in the blue and red regions, where the photosynthetic response is maximized. A short and efficient synthetic approach, featuring two consecutive C-H activation reactions in a one-pot procedure as key steps, was used. Based on their spectroscopic and electrochemical characterization, two of dyes prepared appeared especially suitable for greenhouse-integrated photovoltaics. The corresponding semitransparent DSSCs yielded 5.6-6.1% power conversion efficiencies, which were largely superior to those provided by other organic dyes previously proposed for the same application.
关键词： organic photosensitizers,light absorption,photovoltaic efficiency,dye-sensitized solar cells,greenhouse integration,thiazolo[5,4-d]thiazole,transparency
更新于2025-09-23 15:21:01
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Improving the performance and economic analysis of photovoltaic panel using copper tubular-rectangular ducted heat exchanger
摘要： This research empirically and theoretically assessed the performance of a solar photovoltaic (PV) panel in five different cooling configurations under the weather conditions of Sanandaj, Iran in September 2018. The findings indicated that, compared to the simple PV mode, the increased mean electrical efficiencies over the whole experiment were 0.27%, 0.5%, 0.72%, 0.6, and 0.88% for the PV/w-XP, PV/w-XD, PV/w-2XDP, PV/a ,and PV/b-2XDP modes, respectively. Further, the highest electrical power for the PV/w-XP, PV/w-XD, PV/w-2XDP, PV/a, and PV/b-2XDP modes increased by 6.8, 12.17, 16.83, 13.17, and 18.92%, respectively compared to the simple PV mode. The monthly electrical output energy the PV/S, PV/w-XP, PV/w-XD, PV/w-2XDP, PV/a, and PV/b-2XDP modes were 28.24 kWh/A, 29.16 kWh/A, 30.34 kWh/A, 31.81 kWh/A, 31.15 kWh/A, and 32.9 kWh/A, respectively. Then, an economic analysis was carried out for the system with two adjustment coefficients. The results showed that although the payback period with an interest rate and an adjustment coefficient of 10% was 2.72 years longer in the PV/b-2XDP than in the PV/S, the annual worth over 20 years was State USD 3.32 (SANA USD 1.07) higher in the PV/b-2XDP mode than in the PV/S mode by considering merely the electrical section. Hence, considering the outlet hot water and air, PV/b-2XDP is more economical to use.
关键词： Water tubular and channel heat exchanger,Photovoltaic panel,Payback period,Thermoelectric
更新于2025-09-23 15:21:01
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Selection of optimal wavelengths for optical soiling modelling and detection in photovoltaic modules
摘要： Soiling impacts the photovoltaic (PV) module performance by reducing the amount of light reaching the photovoltaic cells and by changing their external spectral response. Currently, the soiling monitoring market is moving toward optical sensors that measure transmittance or reflectance, rather than directly measuring the impact of soiling on the performance of photovoltaic modules. These sensors, which use a single optical measurement, are not able to correct the soiling losses that depend on the solar irradiance spectra and on the spectral response of the monitored PV material. This work investigates methods that can improve the optical detection of soiling by extracting the full soiling spectrum profiles using only two or three monochromatic measurements. Spectral transmittance data, measured with a spectrophotometer and collected during a 46-week experimental soiling study carried out in Ja?en, Spain, was analysed in this work. The use of a spectral profile for the hemispherical transmittance of soiled PV glass is found to significantly improve the soiling detection, returning the lowest errors independently of the PV materials and irradiance conditions. In addition, this work shows that it is also possible to select the measurement wavelengths to minimize the soiling loss detection error depending on the monitored PV semiconductor material (silicon, CdTe, a-Si, CIGS and a representative perovskite). The approaches discussed in this work are also found to be more robust to potential measurement errors compared to single wavelength measurement techniques.
关键词： Soiling,Dust,Optical modelling,Photovoltaic,Spectral losses,Reliability
更新于2025-09-23 15:21:01
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Understanding the effect of solvent additive in polymeric thin film: turning a bilayer in a bulk heterojunction like photovoltaic device
摘要： Here we report the effect of an additive solvent, the 1,8-diiodooctane (DIO) on the performance of a bilayer organic photovoltaic (OPV) device which active layer comprises the poly[2,7-(9,9-bis(2 ethylhexyl)-dibenzosilole)-alt-4,7-bis(thiophen-2-yl)benzo-2,1,3-thiadiazole] (PSiF-DBT) as the electron donor material and C60 as the electron acceptor material. We observed that when the donor layer was treated with 1% of DIO the power conversion efficiency (PCE) of the device increase 138.4% in relation to the device with a non-treated donor layer and 21.3% in relation to the device containing a donor layer submitted to a thermal annealed. The main effects that lead to this increase in PCE are the large interfacial area between donor and acceptor materials and the improved conductivity at low voltages. The increase in polymer surface roughness leads to a more effective PSiF-DBT/C60 interface for exciton dissociation. This effect, as well as the increase in the conductivity, raised the short circuit current density (JSC) to 13.89 mA/cm2 and PCE to 4.84%. Our conclusions are supported by morphological analysis, chemical cross-sectional evaluations with advanced microscopy techniques, charge mobility measurements as well as by theoretical simulations of the devices in which the changes on the donor/acceptor interfacial area were considered. The outcomes suggest that, solvent additives could be an alternative treatment to replace the thermal annealing which imposes further difficulties to perform the lab-to-manufacturing upscaling.
关键词： solvent additive,PSiF-DBT,exciton dissociation,1,8-diiodooctane,C60,organic photovoltaic,power conversion efficiency
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE Sustainable Power and Energy Conference (iSPEC) - Beijing, China (2019.11.21-2019.11.23)] 2019 IEEE Sustainable Power and Energy Conference (iSPEC) - Analysis on photovoltaic penetration in gridding distribution network considering the timing correlation between source and load
摘要： The increased photovoltaic penetration has brought severe problems to the power grid. The penetration capacity of solar power should be calculated accurately so as to arrange the construction of power grid in a reasonable way. An improved clustering method considering the timing correlation between source and load is proposed to distinguish typical photovoltaic output scenes in this paper. A risk rating method based on SA-PSO algorithm is also designed to evaluate the risk level for the photovoltaic penetration of the whole region. Results from an actual gridding distribution network demonstrate the accuracy of the method.
关键词： slope distance,gridding operation,SA-PSO algorithm,photovoltaic penetration,timing correlation
更新于2025-09-23 15:21:01