Parameter estimation of photovoltaic model via parallel particle swarm optimization algorithm
Corresponding Author
Jieming Ma
School of Electronic and Information Engineering, Suzhou University of Science and Technology, No. 1 Ke Rui Road, Suzhou High-Tech Zone, Suzhou, Jiangsu Province, 215009 China
Department of Computer Science and Software Engineering (CSSE), Xi'an Jiaotong-Liverpool University, Science Building, No. 111 Ren'ai Road, Suzhou Industrial Park, Suzhou, Jiangsu Province, 215123, China
Correspondence
Jieming Ma, School of Electronic and Information Engineering, Suzhou University of Science and Technology, No. 1 Ke Rui Road, Suzhou High-Tech Zone, Suzhou, Jiangsu Province, 215009, China.
E-mail: [email protected]
Search for more papers by this authorKa Lok Man
Department of Computer Science and Software Engineering (CSSE), Xi'an Jiaotong-Liverpool University, Science Building, No. 111 Ren'ai Road, Suzhou Industrial Park, Suzhou, Jiangsu Province, 215123, China
Search for more papers by this authorSheng-Uei Guan
Department of Computer Science and Software Engineering (CSSE), Xi'an Jiaotong-Liverpool University, Science Building, No. 111 Ren'ai Road, Suzhou Industrial Park, Suzhou, Jiangsu Province, 215123, China
Search for more papers by this authorT. O. Ting
Department of Electrical and Electronic Engineering (EEE), Xi'an Jiaotong-Liverpool University, Science Building, No. 111 Ren'ai Road, Suzhou Industrial Park, Suzhou, Jiangsu Province, 215123 China
Search for more papers by this authorPrudence W. H. Wong
Department of Computer Science, University of Liverpool, Ashton Building, Ashton Street, Liverpool, L69 3BX UK
Search for more papers by this authorCorresponding Author
Jieming Ma
School of Electronic and Information Engineering, Suzhou University of Science and Technology, No. 1 Ke Rui Road, Suzhou High-Tech Zone, Suzhou, Jiangsu Province, 215009 China
Department of Computer Science and Software Engineering (CSSE), Xi'an Jiaotong-Liverpool University, Science Building, No. 111 Ren'ai Road, Suzhou Industrial Park, Suzhou, Jiangsu Province, 215123, China
Correspondence
Jieming Ma, School of Electronic and Information Engineering, Suzhou University of Science and Technology, No. 1 Ke Rui Road, Suzhou High-Tech Zone, Suzhou, Jiangsu Province, 215009, China.
E-mail: [email protected]
Search for more papers by this authorKa Lok Man
Department of Computer Science and Software Engineering (CSSE), Xi'an Jiaotong-Liverpool University, Science Building, No. 111 Ren'ai Road, Suzhou Industrial Park, Suzhou, Jiangsu Province, 215123, China
Search for more papers by this authorSheng-Uei Guan
Department of Computer Science and Software Engineering (CSSE), Xi'an Jiaotong-Liverpool University, Science Building, No. 111 Ren'ai Road, Suzhou Industrial Park, Suzhou, Jiangsu Province, 215123, China
Search for more papers by this authorT. O. Ting
Department of Electrical and Electronic Engineering (EEE), Xi'an Jiaotong-Liverpool University, Science Building, No. 111 Ren'ai Road, Suzhou Industrial Park, Suzhou, Jiangsu Province, 215123 China
Search for more papers by this authorPrudence W. H. Wong
Department of Computer Science, University of Liverpool, Ashton Building, Ashton Street, Liverpool, L69 3BX UK
Search for more papers by this authorSummary
Recently, bio-inspired metaheuristic algorithms have been widely used as powerful optimization tools to estimate crucial parameters of photovoltaic (PV) models. However, the computational cost involved in terms of the time increases as data size or the complexity of the applied PV electrical model increases. Hence, to overcome these limitations, this paper presents the parallel particle swarm optimization (PPSO) algorithm implemented in Open Computing Language (OpenCL) to solve the parameter estimation problem for a wide range of PV models. Experimental and simulation results demonstrate that the PPSO algorithm not only has the capability of obtaining all the parameters with extremely high accuracy but also dramatically improves the computational speed. This is possible and is shown in this work via the inherent capabilities of the parallel processing framework. Copyright © 2015 John Wiley & Sons, Ltd.
References
- 1Farivar G, Asaei B. A new approach for solar module temperature estimation using the simple diode model. IEEE Trans. on Energy Convers. 2011; 26(4): 1118–1126.
- 2Messenger RA, Ventre J. Photovoltaic Systems Engineering ( 2nd). CRC Press: Boca Raton, 2004.
- 3Beck JV, Arnold KJ. Parameter Estimation in Engineering and Science Parameter. Wiley series in probability and mathematical statistics: New York, 1977.
- 4Ishaque K, Salam Z, Taheri H, Shamsudin A. A critical evaluation of ea computational methods for photovoltaic cell parameter extraction based on two diode model. Solar Energy 2011; 85(9): 1768–1779.
- 5Chan DSH, Phang JCH. Analytical methods for the extraction of solar-cell single- and double-diode model parameters from I–V characteristics. IEEE Trans. on Electron Devices 1987; 34(2): 286–293.
- 6Phang JCH, Chan DSH, Phillips JR. Accurate analytical method for the extraction of solar cell model parameters. Electronics Letters 1984; 20(10): 406–408.
- 7de Blas MA, Torres JL, Prieto E, Garca A. Selecting a suitable model for characterizing photovoltaic devices. Renewable Energy 2002; 25(3): 371–380.
- 8Chatterjee A, Keyhani A, Kapoor D. Identification of photovoltaic source models. IEEE Trans. on Energy Convers. 2011; 26(3): 883–889.
- 9Gottschalg R, Rommel M, Infield DG, Kearney MJ. The influence of the measurement environment on the accuracy of the extraction of the physical parameters of solar cells. Measurement Science and Technology 1999; 10(9): 796.
- 10Easwarakhanthan T, Bottin J, Bouhouch I, Boutrit C. Nonlinear minimization algorithm for determining the solar cell parameters with microcomputers. International Journal of Solar Energy 1986; 4(1): 1–12.
- 11Mullejans H, Hyvarinen J, Karila J, Dunlop ED. Reliability of the routine 2-diode model fitting of PV modules, in 19th European Photovoltaic Solar Energy Conf., 2004, Conference Proceedings, p. 2459.
- 12Joseph AJ, Hadj B, Ali A-L. Solar cell parameter extraction using genetic algorithms. Measurement Science and Technology 2001; 12(11): 1922.
- 13Soon JJ, Low K-S. Photovoltaic model identification using particle swarm optimization with inverse barrier constraint. IEEE Trans. on Power Electron 2012; 27(9): 3975–3983.
- 14Ye M, Wang X, Xu Y. Parameter extraction of solar cells using particle swarm optimization. Journal of Applied Physics 2009; 105(9): pp. 094 502–8.
- 15Rajasekar N, Krishna Kumar N, Venugopalan R. Bacterial foraging algorithm based solar PV parameter estimation. Solar Energy 2013; 97(0): 255–265.
- 16AlHajri MF, El-Naggar KM, AlRashidi MR, Al-Othman AK. Optimal extraction of solar cell parameters using pattern search. Renewable Energy 2012; 44(0): 238–245.
- 17El-Naggar KM, AlRashidi MR, AlHajri MF, Al-Othman AK. Simulated annealing algorithm for photovoltaic parameters identification. Solar Energy 2012; 86(1): 266–274.
- 18Ishaque K, Salam Z, Mekhilef S, Shamsudin A. Parameter extraction of solar photovoltaic modules using penalty-based differential evolution. Applied Energy 2012; 99(0): 297–308.
- 19da WT Costa, Fardin JF, Simonetti DSL, de Neto L. V. B. M. Identification of photovoltaic model parameters by differential evolution, in IEEE Int. Conf. on Ind. Tech., 2010, Conference Proceedings, pp. 931–936.
- 20Ma J, Ting TO, Man KL, Zhang N, Guan S-U, Wong PWH. Parameter estimation of photovoltaic models via Cuckoo search. Journal of Applied Mathematics 2013; 2013: 8.
- 21Gaster B, Howes L, Kaeli DR, Mistry P, Schaa D. Heterogeneous Computing with OpenCL (2nd). Elsevier Inc.: Waltham, 2012.
- 22Mussi L, Daolio F, Cagnoni S. Evaluation of parallel particle swarm optimization algorithms within the cuda architecture. Information Sciences 2011; 181(20): 4642–4657.
- 23Lasnier F, Ang TG. Photovoltaic Engineering Handbook. Institute of Physics Publishing: London, 1990.
- 24Castaner L, Silvestre S. Modelling Photovoltaic Systems Using PSpice. John Wiley & Sons Ltd.: Chichester, 2002.
10.1002/0470855541 Google Scholar
- 25Mahmoud Y, Xiao W, Zeineldin HH. A simple approach to modeling and simulation of photovoltaic modules. IEEE Trans. on Sustainable Energy 2012; 3(1): 185–186.
- 26Villalva MG, Gazoli JR, Filho ER. Comprehensive approach to modeling and simulation of photovoltaic arrays. IEEE Trans. on Power Electron. 2009; 24(5): 1198–1208.
- 27Khallat MA, Rahman S. A probabilistic approach to photovoltaic generator performance prediction. Trans. Trans. on Energy Convers. 1986; EC-1(3): 34–40.
- 28Ishaque K, Salam Z, Taheri H. Simple, fast and accurate two-diode model for photovoltaic modules. Solar Energy Materials and Solar Cells 2011; 95(2): 586–594.
- 29Kennedy J, Eberhart R. Particle swarm optimization, in IEEE Int. Conf. on Neural Networks, vol. 4, 1995, Conference Proceedings, pp. 1942–1948.
- 30Kennedy J, Eberhart RC, Shi Y. Swarm Intelligence. Morgan Kaufmann Publishers: San Francisco, 2001.
