Optimal Polynomial Approximation of Photovoltaic Panel Characteristics Using a Stochastic Approach
AbstractThe essence of this article is finding the optimal degree of the p=f(v) real photovoltaic panel characteristics approximation polynomial. The characteristics are considered as one realization of a stochastic system and it is the result of long-term measuring. The outputs are the coefficients of an approximation polynomial of an optimal degree. For its calculation, we use the well-known Euclidean norm of residues. The advantage of this approach is that it takes all the influences on the panel’s attributes into consideration (solar irradiation, temperature, aging, random effects). It is necessary for the approximation to carry out a rotation of the measured characteristics and a backwards rotation of the approximation polynomial course. This method enables us to create a mathematical or numerical model of a real photovoltaic panel of any type. All the algorithms and experiments were done using MATLAB® system.
LEUCHTER, J., BAUER, P. and FINNEY, S.J. Modeling and experimental verification of EGS to achieve higher efficiency. In 35th Annual Conference of IEEE Industrial Electronics (IECON 2009. Porto (Portugal), 2009, p. 3983-3986.
LEUCHTER, J., RERUCHA, V. and ZOBAA, A.F. Mathematical modeling of photovoltaic systems. In 14th Power Electronics and Motion Control Conference (EPE-PEMC 2010). Ohrid (Macedonia), 2010, p. 422-427.
ZAPLATILEK, K. and LEUCHTER, J. Photovoltaic Panel Modeling in MATLAB® Environment. Radioengineering, 2011, vol. 20, no. 2, p. 445-450.
ZAPLATILEK, K. and LEUCHTER, J. Behavioral Model of Photovoltaic Panel in Simulink®. Advances in Electrical and Computer Engineering, 2011, vol. 11, no. 4, p. 83-88.
KODALI, H. K. and GANAPATHYSUBRAMANIAN, B. Computer simulation of heterogeneous polymer photovoltaic devices. Modelling and Simulation in Materials Science and Engineering, 2012, vol. 20, no. 3.
GONZALEZ, D., RAMOS, P., CARLOS, A., SAAVEDRA, M. and ANDRES, J. Modeling and control of grid connected photovoltaic systems. Revista Facultad de Ingenieria-Universidad de Antioquia (Colombia), 2012, no. 62, p. 145 - 156.
AMROUCHE, B., GUESSOUM, A. and ABDERREZAK, B. M. A simple behavioural model for solar module electric characteristics based on the first order system step response for MPPT study and comparison. Applied Energy, vol. 91, no. 1, p. 395-404.
QI, Ch. and MING, Z. Photovoltaic Module Simulink Model for a Stand-alone PV System. In Proceedings of the International Conference on Applied Physics and Industrial Engineering (ICAPIE). Wuhan (Peoples Republic of China), 2012, p. 94-100.
DIAZ, F., MONTERO, G. and ESCOBAR, J. M. An adaptive solar radiation numerical model. Journal of Computational and Applied Mathematics, 2012, vol. 236, no. 18, p. 4611-4622.
HEIBER, M. C. and DHINOJWALA, A. Dynamic Monte Carlo modeling of exciton dissociation in organic donor-acceptor solar cells. Journal of Chemical Physics, 2012, vol. 137, no. 1.
WANG, F., Mi, Z. and Su, S. Short-Term Solar Irradiance Forecasting Model Based on Artificial Neural Network Using Statistical Feature Parameters. Energies, 2012, vol. 5, no. 5, p. 1355-1370.
RODRIGO, P., RUS, C. and ALMONACID, F. A new method for estimating angular, spectral and low irradiance losses in photovoltaic systems using an artificial neural network model in combination with the Osterwald model. Solar Energy Materials and Solar Cells, vol. 96, no. 1, p. 186-194.
Di FAZIO, A. R. and RUSSO, M. Photovoltaic generator modelling to improve numerical robustness of EMT simulation. Electric Power Systems Research, vol. 83, no. 1, p. 136-143.
WISSEM, Z., GUEORGUI, K. and HEDI, K. Modeling and technical-economic optimization of an autonomous photovoltaic system. Energy, 2012, vol. 37, no. 1, p. 263-272.
LI, Z., He, S. and ZHANG, S. Approximation Methods for Polynomial Optimization, Springer, 2012.
MATHEWS, J.H. and FINK, K.K. Numerical Methods Using MATLAB®. Pearson Prentice-Hall, 2004.
How to Cite
Authors who publish with this journal agree to the following terms:
1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
Users can use, reuse and build upon the material published in the journal for any purpose, even commercially.