Modelling and experimental analysis of a seasonally tracked V-trough PV/T system in India

Baig, Hasan; Jani, Ruchita; Markam, Bhupendra; Maiti, Subarna

doi:10.1016/j.solener.2018.06.018

Cited by 16 publications

(4 citation statements)

References 31 publications

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“…Solar desalination systems are classified into direct and indirect systems and thermal or nonthermal systems (Ali et al, 2011). Baig et al (2018) integrated PV with heat exchangers connected to an RO plant to enhance the overall system efficiency. Their results indicate raised panel temperature, which resulted in a counter performance, that was addressed by cooling the PV panels.…”

Section: Literature Reviewmentioning

confidence: 99%

Techno-environmental Simulations for Solar Energy-Powered Seawater Reverse Osmosis Desalination for a Hyper Arid Coastal Region

Aldei¹,

Al-Shayji

Aleisa

2022

JER is an international, peer-reviewed journal that publishes f

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This study investigates the efficiency of a solar-powered seawater desalination plant (DP) using reverse osmosis for an arid coastal region. The solar models are investigated using local meteorological data, including direct, diffused and global irradiance. The meteorological data are obtained using local typical meteorological data set collected from a ground weather station. The PVsyst simulation tool is used to model a grid-connected solar PV system utilizing three photovoltaic (PV) technologies: thin-film, monocrystalline, and polycrystalline. Three scenarios were considered: restricted area, daily water production and design capacity. The optimum configuration for the restricted area scenario at the seawater DP location considered is an on-grid thin-film module (170 W) with a tilt angle of 20° and an inverter unit of 2000 kW. The solution module area is 15,248 m2. The annual electricity production will be approximately 4251.1 MWh/y, which represents only 3.1% of the DP demand. Thin-films produce higher annual electricity than monocrystalline and polycrystalline silicon by 8.3% and 5.9%, respectively, but require 15.9% and 5.7% more space than monocrystalline and polycrystalline silicon, respectively. For Shuwaikh DP, a 30 MIGD DP will require a PV system with a capacity of 120 MWp at 30° tilt angles and 60 inverters. The design environmental impact was assessed using life cycle assessment (LCA). The carbon footprint will decrease from 7.3 x10-5 to 1.8 x10-5 (kg CO2 equivalent), for the 30 MIGD production. The fossil fuel depletion will decrease by approximately 80%. However, the large number of solar panels and the significant total ground area required for the 30 MIGD. The solar array of 1,531,054 m2 will adversely affect the urban land occupation impact category by 84% and will increase metal depletion by 37%.The response surface optimization indicates that the optimal performance in the coastal region for power desalination plants is achieved when using a thin-film at a tilt angle of 20 o.

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Section: Literature Reviewmentioning

confidence: 99%

Techno-environmental Simulations for Solar Energy-Powered Seawater Reverse Osmosis Desalination for a Hyper Arid Coastal Region

Aldei¹,

Al-Shayji

Aleisa

2022

JER is an international, peer-reviewed journal that publishes f

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“…Thus, there is a need to adopt an automated technique that can detect, diagnose and localize fault occurrences in PV modules. Fault diagnosis and detection techniques for PV modules can be broadly categorized into two methods: (i) vision-or image-based methods (photoluminescence imaging [20], electroluminescence imaging [21,22], RGB imaging [23], fluorescence imaging [24] and infrared thermography [25][26][27]) and (ii) electrical measurement methods (IV curves [28,29], power spectral analysis, signal processing and reflectometry).…”

Section: Introductionmentioning

confidence: 99%

Weightless Neural Network-Based Detection and Diagnosis of Visual Faults in Photovoltaic Modules

Sridharan,

Joseph,

Vaithiyanathan

et al. 2023

Energies

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The present study introduces a novel approach employing weightless neural networks (WNN) for the detection and diagnosis of visual faults in photovoltaic (PV) modules. WNN leverages random access memory (RAM) devices to simulate the functionality of neurons. The network is trained using a flexible and efficient algorithm designed to produce consistent and precise outputs. The primary advantage of adopting WNN lies in its capacity to obviate the need for network retraining and residual generation, making it highly promising in classification and pattern recognition domains. In this study, visible faults in PV modules were captured using an unmanned aerial vehicle (UAV) equipped with a digital camera capable of capturing RGB images. The collected images underwent preprocessing and resizing before being fed as input into a pre-trained deep learning network, specifically, DenseNet-201, which performed feature extraction. Subsequently, a decision tree algorithm (J48) was employed to select the most significant features for classification. The selected features were divided into training and testing datasets that were further utilized to determine the training, test and validation accuracies of the WNN (WiSARD classifier). Hyperparameter tuning enhances WNN’s performance by achieving optimal values, maximizing classification accuracy while minimizing computational time. The obtained results indicate that the WiSARD classifier achieved a classification accuracy of 100.00% within a testing time of 1.44 s, utilizing the optimal hyperparameter settings. This study underscores the potential of WNN in efficiently and accurately diagnosing visual faults in PV modules, with implications for enhancing the reliability and performance of photovoltaic systems.

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“…They obtained that the power output was enhanced by 34.6 % on March 13 th and by 37 % on September 16 th . Baig et al [9] analyzed and experimented with the seasonally tracked V-Trough PV/T system in India. They observed an average augmentation of 35 % in the electrical power output from the V-Trough PV/T system as compared to the conventional one.…”

Section: Introductionmentioning

confidence: 99%

Solar flat plate collector enhanced by two reflectors: optimum tilts of reflectors

Rachédi

Bechki

Marif

et al. 2022

Electrical Engineering & Electromechanics

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Introduction. In some solar concentrating system applications, in which the incoming sunlight is augmented by using commercial flat plate reflectors placed on different sides of the planar collector, it is very important to choose the optimum tilts of boosters (attached edge-to-edge on the top and bottom sides of the solar collector) for each month, to enhance their received solar irradiation over the year in the southern Algeria. The novelty of the proposed work consists of the development of a novel mathematical model in which the reference of the reflector’s tilt angles is the collector plane, and optimal tilts are optimized on the average day of each month. Purpose. This paper proposes a novel analytical model of two identical planer reflectors, placed on the top and bottom of a latitude tilted flat plate solar collector, for optimizing their optimal inclination angles during the daytime throughout the year in Ouargla city, southeast of Algeria. Methods. Optimal tilt angles of reflectors were obtained by searching for the optimum captured solar irradiation on the collector’s surface from each reflector in the representative day of each month of the year. After that, the obtained tilts were used for calculating incoming solar irradiation on the received area and comparing them to the solar collector without reflectors. Results. The findings of this paper showed that the reflector’s inclination angles were variable from one month to another in which the upper reflector’s tilts reached its maximum in June and minimum in December, contrarily for the lower reflector. Again, an increase of 28.05 % in the daily received solar irradiation on the collector surface with reflectors compared to the conventional one.

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Modelling and experimental analysis of a seasonally tracked V-trough PV/T system in India

Cited by 16 publications

References 31 publications

Techno-environmental Simulations for Solar Energy-Powered Seawater Reverse Osmosis Desalination for a Hyper Arid Coastal Region

Techno-environmental Simulations for Solar Energy-Powered Seawater Reverse Osmosis Desalination for a Hyper Arid Coastal Region

Weightless Neural Network-Based Detection and Diagnosis of Visual Faults in Photovoltaic Modules

Solar flat plate collector enhanced by two reflectors: optimum tilts of reflectors

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