Abstract
A silicon based photovoltaic (PV) cells are underlying a surface analysis for understanding its performance degradation. Approach for the split investigation based on the surface images with electrical parameter was used for analyzing the performance factors. Solar devices which are having a power hotspot for proficient electrical vitality are over time span. The defect in the cell due to the surface deformity leads to decreased in the performance parameter and affects the overall maximum power capability. The continuation to diminish wafer thickness in the fabrication process of silicon cells causes increase in the defects patterns as seen in the numerous cases studies. Reviewing the model-based system dependent on image processing algorithm especially designed for the degradation analysis capable to recognize any miniature crack before its large penetration to avoid major damage in the system. Study is based on the board surface and with the measurable symptoms in the initial phase of the degradation process. Analysis of PV cells with ARIMA model with voltage, current and power butt-centric analysis has been investigated to understand the process of its degradation. Recognition of the break and split division technique with edge detection was used in the model for its observation. Channel for split finding and recognizing its pattern is used in the modern application as seen in the recent field of the photovoltaic.
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References
Stromer D, Vetter A, Oezkan HC, Probst C, Maier A (2019) Enhanced crack segmentation (eCS): a reference algorithm for segmenting cracks in multicrystalline silicon solar cells, pp 2156–3381
Energy Statistics Pocket Book (2019) United Nations Publications, New York, USA
Gielena D, Boshella F, Sayginb D, Bazilianc MD, Wagnera N, Gorinia R (2019) The role of renewable energy in the global energy transformation, pp 2211–467X
Feng B, Shen X, Long J, Chen H (2013) A novel crack detection algorithm for solar panel surface images, pp 650–654. 978-0-7695-5125-8/13
Pletzer TM,van Molken JI, RiBland S, Hallam B, Comagliotti E, John J, Breitenstein O, Knoch J (2014) Quantitative local current-voltage analysis with different spatially resolved camera based techniques of silicon solar cells with cracks, pp 3473–3478. 978-1-4799-4398-2/14
Al Ahmar J, Wiese S (2014) A crack analysis model for silicon based solar cells. In: 15th international conference on thermal, mechanical and multi-physics simulation and experiments in microelectronics and microsystems. 978-1-4799-4790-4/14
Jean J-H, Chen C-H, Lin H-L (2011) Application of an image processing software tool to crack inspection of crystalline silicon solar cells. In: Proceedings of the international conference on machine learning and cybernetics. Guilin
Al Ahmar J, Wiesel S (2013) Analysis and simulation of cracks and micro cracks in PV Cells. In: 14th international conference on thermal, mechanical and multi-physics simulation and experiments in microelectronics and microsystems
Aghamohammadi AH, Prabuwono AS, Sahran S, Mogharrebi M (2011) Solar cell panel crack detection using particle swarm optimization algorithm. In: International conference on pattern analysis and intelligent robotics. Putrajaya, Malaysia
Karimi AM, Fada JS, Liu JQ, Braid JL, Koyuturk M, French RH (2018) Feature extraction, supervised and unsupervised machine learning classification of PV cell electroluminescence images. 978-1-5386-8529-7/18
Fu W, Breininger K, Würfl T, Ravikumar N, Schaffert R, Maier A (2017) Frangi-net, a neural network approach to vessel segmentation
Gong D, Medioni G (2012) Probabilistic tensor voting for robust perceptual grouping. Institute for Robotics and Intelligent Systems. https://doi.org/10.1.1.310.2157
Urade HS, Patel R (2011) Study and analysis of particle swarm optimization: a review. In: 2nd national conference on information and communication technology (NCICT)
Chauhan A, Singh A (2017) An ARIMA model for the forecasting of healthcare waste generation in the Garhwal region of Uttarakhand, India. Int J Serv Oper Inf. https://doi.org/10.1504/IJSOI.2017.086587
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Pancholi, K., Pandya, M., Raval, D. (2020). Reviewing Surface Defects for the Performance Degradation in the Solar Devices. In: Mehta, A., Rawat, A., Chauhan, P. (eds) Advances in Electric Power and Energy Infrastructure. Lecture Notes in Electrical Engineering, vol 608. Springer, Singapore. https://doi.org/10.1007/978-981-15-0206-4_18
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DOI: https://doi.org/10.1007/978-981-15-0206-4_18
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