Data analysis and tools applied to modeling and simulation of a PV system in Ecuador

  1. Benavides Padilla, Darío Javier 1
  2. Jurado, F 1
  3. González, Luis G 2
  1. 1 University of Jaén, Jaén - Spain
  2. 2 University of Cuenca, Cuenca - Ecuador
Zeitschrift:
Enfoque UTE: Facultad de Ciencias de la Ingeniería e Industrias - Universidad UTE

Datum der Publikation: 2018

Ausgabe: 9

Nummer: 4

Seiten: 1-12

Art: Artikel

DOI: 10.29019/ENFOQUEUTE.V9N4.389 WoS: WOS:000454179900001 DIALNET GOOGLE SCHOLAR lock_openOpen Access editor

Zusammenfassung

This paper presents a research that was carried out for the management of a photovoltaic system in a Microgrid, with applications and the use of tools applied to modeling and computational simulation in the Microgrid laboratory implanted in the facilities of the University of Cuenca (Ecuador). Additionally, through the use of automatic learning techniques, the behavior of the photovoltaic system has been modeled in the study area based on radiation and temperature with very good results. In addition, several applications can be made in real engineering studies such as feasibility, performance analysis, energy estimation, educational models, etc.

Bibliographische Referenzen

  • Ahmad, A., Mehdi, F., Pourya, S. and Cihan, H. (2017), Modeling and Simulation of Microgrid, Procedia Computer Science, 114, 392-400.
  • Almaraashi, M., (2018), Investigating the impact of feature selection on the prediction of solar radiation in different locations in Saudi Arabia, Applied Soft Computing, 66, 250-263.
  • Almorox, J. and Hontoria, C., (2014), Global solar radiation estimation using sunshine duration in Spain, Energy Conversion and Management, 45, 1529-1535.
  • Bays, N., Clifton, J. and Hatipoglu, K., (2014), MATLAB-Graphical User Interface to study partial shading of PV array characteristics, IEEE SOUTHEASTCON, 1-4.
  • Chunming, T., Xi, H., Zhikang, S. and Fei, J., (2017), Big data issues in smart grid – A review, Renewable and Sustainable Energy Reviews, 79, 1099-1107.
  • Ding, K., Bian, X., Liu, H. and Peng, T., (2012), A MATLAB-Simulink-Based PV Module Model and Its Application Under Conditions of Nonuniform Irradiance, IEEE Transactions on Energy Conversion, 27, 864-872.
  • Espinoza, J. L., González, L. G., and Sempértegui, R., (2017), Micro grid laboratory as a tool for research on non-conventional energy sources in Ecuador, IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), 1-7.
  • Meenal, R. and Selvakumar, A., (2018), Assessment of SVM, empirical and ANN based solar radiation prediction models with most influencing input parameters, Renewable Energy, 121, 324-343.
  • Mellit, A., Kalogirou, S.A., Hontoria, L. and Shaari, S., (2009), Artificial intelligence techniques for sizing photovoltaic systems: A review, Renewable and Sustainable Energy Reviews, 13, 406-419.
  • Nayak, B. P. and Shaw, A., (2017), Design of MPPT controllers and PV cells using MATLAB Simulink and their analysis, International Conference on Nascent Technologies in Engineering (ICNTE), 1-6.
  • Prasanth, J., Himanshu, M., Dhanup, S., Sudhakar, T., Masafumi, M. and Rajasekar, N., (2018), Analysis on solar PV emulators: A review, Renewable and Sustainable Energy Reviews, 81, 149-160.
  • Rameen, A., (2017), Modeling and simulation of a micro grid-connected solar PV system, Water Science, 31, 1-10.
  • Razman, A. and Chee, W. T., (2017), A comprehensive review on photovoltaic emulator, Renewable and Sustainable Energy Reviews, 80, 430-452.
  • Sreenivasa, G., Bramhananda, T. and Vijaya, M., (2017), A MATLAB based PV Module Models analysis under Conditions of Nonuniform Irradiance, Energy Procedia, 117, 974-983.