Performance degradation in field-aged crystalline silicon PV modules in different indian climatic conditions

Linear Interpolation methods for predicting the I-V characteristics for c-Si PV modules in outdoor conditions have been used by various groups of researchers. This is essential for minimizing the uncertainty in predicting essential photovoltaic parameters of interpolated I-V characteristics. A near optimum value of empirical co-efficient used in Tsunos model has been investigated under typical Eastern Indian Climatic conditions.

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Investigation of Dominant Failure Mode(s) for Field-Aged Crystalline Silicon PV Modules Under Desert Climatic Conditions

IEEE Journal of Photovoltaics ◽

10.1109/jphotov.2014.2308720 ◽

2014 ◽

Vol 4 (3) ◽

pp. 814-826 ◽

Cited By ~ 33

Author(s):

Joseph M. Kuitche ◽

Rong Pan ◽

GovindaSamy TamizhMani

Keyword(s):

Failure Mode ◽

Crystalline Silicon ◽

Climatic Conditions ◽

Pv Modules

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Experimental investigation of observed defects in crystalline silicon PV modules under outdoor hot dry climatic conditions in Algeria

Solar Energy ◽

10.1016/j.solener.2017.11.018 ◽

2018 ◽

Vol 159 ◽

pp. 475-487 ◽

Cited By ~ 37

Author(s):

Ahmed Bouraiou ◽

Messaoud Hamouda ◽

Abdelkader Chaker ◽

Ammar Neçaibia ◽

Mohammed Mostefaoui ◽

...

Keyword(s):

Experimental Investigation ◽

Crystalline Silicon ◽

Climatic Conditions ◽

Pv Modules

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Proposed Models to Improve Predicting the Operating Temperature of Different Photovoltaic Module Technologies under Various Climatic Conditions

Applied Sciences ◽

10.3390/app11157064 ◽

2021 ◽

Vol 11 (15) ◽

pp. 7064

Author(s):

Dang Phuc Nguyen Nguyen ◽

Kristiaan Neyts ◽

Johan Lauwaert

Keyword(s):

Wind Speed ◽

Crystalline Silicon ◽

Operating Temperature ◽

Thermal Inertia ◽

Climatic Conditions ◽

Solar Irradiation ◽

Photovoltaic Module ◽

Silicon Thin Film ◽

Pv Module ◽

Pv Modules

The operating temperature is an essential parameter determining the performance of a photovoltaic (PV) module. Moreover, the estimation of the temperature in the absence of measurements is very complex, especially for outdoor conditions. Fortunately, several models with and without wind speed have been proposed to predict the outdoor operating temperature of a PV module. However, a problem for these models is that their accuracy decreases when the sampling interval is smaller due to the thermal inertia of the PV modules. In this paper, two models, one with wind speed and the other without wind speed, are proposed to improve the precision of estimating the operating temperature of outdoor PV modules. The innovative aspect of this study is two novel thermal models that consider the variation of solar irradiation over time and the thermal inertia of the PV module. The calculation is applied to different types of PV modules, including crystalline silicon, thin film as well as tandem technology at different locations. The models are compared to models that are described in the literature. The results obtained in different time steps show that our proposed models achieve better performance and can be applied to different PV technologies.

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Financial viability assessment of concentrated solar power technologies under Indian climatic conditions

Sustainable Energy Technologies and Assessments ◽

10.1016/j.seta.2020.100928 ◽

2020 ◽

pp. 100928

Author(s):

Sankalp Kumar ◽

Aviral Agarwal ◽

Anil Kumar

Keyword(s):

Solar Power ◽

Climatic Conditions ◽

Financial Viability ◽

Concentrated Solar Power ◽

Viability Assessment ◽

Indian Climatic

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Efficient Cell Segmentation from Electroluminescent Images of Single-Crystalline Silicon Photovoltaic Modules and Cell-Based Defect Identification Using Deep Learning with Pseudo-Colorization

Sensors ◽

10.3390/s21134292 ◽

2021 ◽

Vol 21 (13) ◽

pp. 4292

Author(s):

Horng-Horng Lin ◽

Harshad Kumar Dandage ◽

Keh-Moh Lin ◽

You-Teh Lin ◽

Yeou-Jiunn Chen

Keyword(s):

Deep Learning ◽

Defect Detection ◽

Crystalline Silicon ◽

Cell Segmentation ◽

Solar Pv ◽

Single Crystalline Silicon ◽

Defect Inspection ◽

Defect Identification ◽

Pv Modules ◽

A Cell

Solar cells may possess defects during the manufacturing process in photovoltaic (PV) industries. To precisely evaluate the effectiveness of solar PV modules, manufacturing defects are required to be identified. Conventional defect inspection in industries mainly depends on manual defect inspection by highly skilled inspectors, which may still give inconsistent, subjective identification results. In order to automatize the visual defect inspection process, an automatic cell segmentation technique and a convolutional neural network (CNN)-based defect detection system with pseudo-colorization of defects is designed in this paper. High-resolution Electroluminescence (EL) images of single-crystalline silicon (sc-Si) solar PV modules are used in our study for the detection of defects and their quality inspection. Firstly, an automatic cell segmentation methodology is developed to extract cells from an EL image. Secondly, defect detection can be actualized by CNN-based defect detector and can be visualized with pseudo-colors. We used contour tracing to accurately localize the panel region and a probabilistic Hough transform to identify gridlines and busbars on the extracted panel region for cell segmentation. A cell-based defect identification system was developed using state-of-the-art deep learning in CNNs. The detected defects are imposed with pseudo-colors for enhancing defect visualization using K-means clustering. Our automatic cell segmentation methodology can segment cells from an EL image in about 2.71 s. The average segmentation errors along the x-direction and y-direction are only 1.6 pixels and 1.4 pixels, respectively. The defect detection approach on segmented cells achieves 99.8% accuracy. Along with defect detection, the defect regions on a cell are furnished with pseudo-colors to enhance the visualization.

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Feasibility Study of the Technical and Economic Performance of Grid-Connected PV System for Selected Rooftops in UTHM

Journal of Electronic Voltage and Application ◽

10.30880/jeva.2021.02.02.005 ◽

2021 ◽

Vol 2 (2) ◽

Author(s):

Mohamad Fakrie Mohamad Ali ◽

◽

Mohd Noor Abdullah ◽

Keyword(s):

Feasibility Study ◽

Crystalline Silicon ◽

Electricity Consumption ◽

Payback Period ◽

Net Energy ◽

Pv System ◽

Pv Module ◽

Electricity Bill ◽

Pv Modules ◽

Energy Metering

This paper presents the feasibility study of the technical and economic performances of grid-connected photovoltaic (PV) system for selected rooftops in Universiti Tun Hussein Onn Malaysia (UTHM). The analysis of the electricity consumption and electricity bill data of UTHM campus show that the monthly electricity usage in UTHM campus is very high and expensive. The main purpose of this project is to reduce the annual electricity consumption and electricity bill of UTHM with Net Energy Metering (NEM) scheme. Therefore, the grid-connected PV system has been proposed at Dewan Sultan Ibrahim (DSI), Tunku Tun Aminah Library (TTAL), Fakulti Kejuruteraan Awam dan Alam Bina (FKAAS) and F2 buildings UTHM by using three types of PV modules which are mono-crystalline silicon (Mono-Si), poly-crystalline silicon (Poly-Si) and Thin-film. These three PV modules were modeled, simulated and calculated using Helioscope software with the capacity of 2,166.40kWp, 2,046.20kWp and 1,845kWp respectively for the total rooftop area of 190,302.9 ft². The economic analysis was conducted on the chosen three installed PV modules using RETScreen software. As a result, the Mono-Si showed the best PV module that can produce 2,332,327.40 kWh of PV energy, 4.4% of CO₂ reduction, 9.3 years of payback period considering 21 years of the contractual period and profit of RM4,932,274.58 for 11.7 years after payback period. Moreover, the proposed installation of 2,166.40kWp (Mono-SI PV module) can reduce the annual electricity bill and CO2 emission of 3.6% (RM421,561.93) and 4.4% (1,851.40 tCO₂) compared to the system without PV system.

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