Monitoring and Visualization of Solar PV Thermal Flow via Interpolation Techniques
DOI:
https://doi.org/10.11113/jest.v1n2.15Keywords:
Bilinear, cubic spline, nearest, temperature profileAbstract
Temperature is one of the major factors that affect the efficient of solar panels and temperature profiles on solar panel are required to optimise the performance of solar PV. A method to construct and visualise the thermal profiles of solar panel with minimum temperature measurement is proposed in this work. Based on nine measured temperature, three different interpolation techniques are used to predict the temperature at 25 points and 81 points. The predicted temperature is then compared with measured temperature from thermal gun. MATLAB is used to reconstruct the thermal image in two different resolution, 17x17 and 33x33. Bilinear interpolation technique and resolution of 33x33 gives the best results and can be applied in industry to predict temperature profile on solar panel with minimum measurement.
References
Ogbomo, O.O., E. H. Amalu, N.N. Ekere, P.O. Olagbegi. 2017. A review of photovoltaic module technologies for increased performance in tropical climate. Renewable and Sustainable Energy Reviews. 75: 1225-1238.
Belkaid, A., J. Gaubert, A. Gherbi and L. Rahmani. 2014. Maximum Power Point tracking for photovoltaic systems with boost converter sliding mode control. 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE), Istanbul, 556-561.
Peled, A., and J. Appelbaum. 2017. Enhancing the power output of PV modules by considering the view factor to sky effect and rearranging the interconnections of solar cells. Prog. Photovolt: Res. Appl., 25: 810–818.
Villalva, M. G., J. R. Gazoli, and E. R. Filho. 2009. Comprehensive Approach to Modeling and Simulation of Photovoltaic Arrays. Power Electronics, IEEE Transactions on, 24(5): 1198–1208.
ALQahtani, A. H., M. S. Abuhamdeh, and Y. M. Alsmadi. 2012. A simplified and comprehensive approach to characterize photovoltaic system performance. 2012 IEEE Energytech, 43210(1): 1–6.
Khan, M., M. Z. Khan, M. N. Imtiaz Khan, S. S. Saha, D. F. Noor, and M. R. K. Rach 2014. Maximum Power Point Tracking for Photovoltaic Array Using Parabolic Interpolation. International Journal of Information and Electronics Engineering, 4(3):249-255.
Jones A. D. and C. P. Underwoord. 2001. A thermal model for photovoltaic systems. Solar Energy, 70(4): 349–359.
King, D. L., Kratochvil, J. A. and Boyson, W. E. 2004. Photovoltaic array performance model. United States. doi:10.2172/919131.
Marion, B., S. Rummel and A. Anderberg 2004. Current-voltage curve translation by bilinear interpolation. Progress in Photovoltaics: Research and Applications, 12(8): 593–607.
Ishaque, K., Z. Salam, M. Amjad, and S. Mekhilef. 2012. An Improved Particle Swarm Optimization (PSO)-based MPPT for PV with reduced steady-state oscillation. IEEE Transactions on Power Electronics, 27(8): 3627–3638.
Mangeni G., R.H.G. Tan, T.H. Tan, S.K. Cheo, V.H. Mok, J.Y. Pang. 2017. Photovoltaic Module Cell Temperature Measurements using Linear Interpolation Technique, 2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) [7969759].
Hafiz, F.A. 2017. Monitoring and Visualization of Solar PV Thermal Flow via Interpolation Techniques. MSc disseratation. Heriot-Watt University. Putrajaya.
Steinhart J.S. and S.R. Hart. 1968. Calibration curves for thermistors, Deep Sea Research and Oceanographic Abstracts 1968;15(4): 497-503.
Kutz, J.N. 2013. Data-Driven Modeling & Scientific Computation: Methods for Complex Systems & Big Data, OUP Oxford.
