Estimation of the energy of a PV generator using artificial neural network

Renewable Energy

Volumn 34, Issue 12, 2009, Pages 2743-2750

  Almonacid, F ^a   Rus, C ^a   Perez P J ^a   Hontoria, L ^a  

^a UNIVERSITY OF JAÉN   (Spain)

Author keywords

Artificial neural network; PV generator

Indexed keywords

ACCURATE PREDICTION; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORKS; CELL TEMPERATURE; ELECTRICAL CHARACTERISATION; GRID-CONNECTED; INDUSTRIALIZED COUNTRIES; INTERNATIONAL COLLABORATIONS; PHOTOVOLTAIC GENERATORS; PHOTOVOLTAIC INSTALLATION; PHOTOVOLTAIC SOLAR ENERGY; PV GENERATOR; PV GENERATORS; PV MODULES; RENEWABLE ENERGIES; URBAN BUILDINGS;

BACKPROPAGATION; CELL MEMBRANES; CRYSTALLINE MATERIALS; INTERNATIONAL COOPERATION; PHOTOVOLTAIC EFFECTS; SOLAR ENERGY; SOLAR POWER GENERATION;

NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; BUILDING; INDUSTRIAL DEVELOPMENT; INSTALLATION; INTERNATIONAL COOPERATION; PHOTOVOLTAIC SYSTEM; RENEWABLE RESOURCE; SOLAR POWER; SUSTAINABLE DEVELOPMENT; URBAN AREA;

EID: 68049137320     PISSN: 09601481     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.renene.2009.05.020     Document Type: Article

References (17)

1. International energy agency report IEA-PVPS T1-16; 2007.
2. Bücher K. Do we need site-dependent and climate dependent module rating? InL Proc. 23rd IEEE photovoltaic specialists conf., Louisville, KY; May 10-14, 1993. p. 1056-62.
3. Anderson D, Bishop J, Dunlop E. Energy rating of photovoltaic modules. In: 16th European photovoltaic solar energy conference, Glasgow; 2000. p. 2087-91.
4. Hontoria L, Aguilera J, Nofuentes G, Almonacid F, De la Casa J. Contribution to quality control of PV modules: a new standard test conditions (stc) V-I curve conversion method using neural networks. In: Proceedings of world renewable energy congress on CD-ROM, Aberdeen, United Kingdom; 2005.
5. Almonacid F, Hontoria L, Aguilera J, Nofuentes G. Improvement in the quality control of PV modules using neural network. In: 21st European photovoltaic solar energy conference and exhibition, Dresden, Germany; 2006.
6. Almonacid F., Hontoria L., Rus C., Fuentes M., and Nofuentes G. Characterisation of PV modules using artificial neural network. Renewable Energy 34 (2009) 941-944
7. Almonacid G, et al. In: 14th European photovoltaic solar energy conference, Barcelona, Spain; 1997. p. 2656-58.
8. Drif M., Pérez P.J., Aguilera J., and Aguilar J.D. A new estimation method of irradiance on a partially shaded PV generator in grid-connected photovoltaic systems. Renewable Energy 33 9 (Sep 2008) 2048-2056
9. Drif M., Pérez P.J., Aguilera J., Almonacid G., Gómez P., de la Casa J., and Aguilar J.D. Univer project. A grid connected photovoltaic system of 200kWp at Jaé n University. Overview and performance analysis. Solar Energy Materials & Solar Cells 91 (2007) 670-683
10. IEC Standard 61724, Photovoltaic system performance monitoring-guidelines for measurement, data exchange and analysis; 1993.
11. King DL, Kratochvil JA, Boyson WE, Bower W. Field experience with a new performance characterisation procedure for photovoltaic arrays. In: Proceeding of the 2nd world conference and exhibition on photovoltaic solar energy conversion, Joint research Center report EUR 18656, Vienna, Austria; 1998. p. 1947-52.
12. Levenberg K. A method for the solution of certain problems in least squares. Quarterly of Applied Mathematics 2 (1944) 164-168
13. Marquardt D. An algorithm for least-squares estimation of nonlinear parameters. SIAM Journal on Applied Mathematics 11 (1963) 431-441
14. Fuentes M., Nofuentes G., Aguilera J., Talavera D., and Castro M. Application and validation of algebraic methods to predict the behaviour of crystalline silicon PV modules in Mediterranean climates. Solar Energy 81 (2007) 1396-1408
15. Osterwald C.R. Translation of device performance measurements to reference conditions. Solar Cells 18 (1986) 269-279
16. Luque A., and Hegedus S. Handbook of PV science and engineering (2003), John Wiley & Sons, Chichester p. 915-39
17. Alonso-Abella M, Chenlo F. A model for energy production estimation of PV grid connected systems based on energetic losses and experimental data. In: On site diagnosis, 19th European photovoltaic solar energy conference, Paris; June 2004. p. 2447-50.