Diseño e Implementación de un Sistema de Control estable basado en Lógica Borrosa para optimizar el rendimiento de un sistema de Generación Fotovoltaico

  1. Maissa Farhat 1
  2. Oscar Barambones 2
  3. Jose A. Ramos 2
  4. Eladio Duran 3
  5. Jose M. Andujar 3
  1. 1 Engineering School of Gabes
  2. 2 Universidad del País Vasco/Euskal Herriko Unibertsitatea
    info

    Universidad del País Vasco/Euskal Herriko Unibertsitatea

    Lejona, España

    ROR https://ror.org/000xsnr85

  3. 3 Universidad de Huelva
    info

    Universidad de Huelva

    Huelva, España

    ROR https://ror.org/03a1kt624

Erakutsi afiliazioak +
Aldizkaria:
Revista iberoamericana de automática e informática industrial ( RIAI )

ISSN: 1697-7920

Argitalpen urtea: 2015

Alea: 12

Zenbakia: 4

Orrialdeak: 476-487

Mota: Artikulua

DOI: 10.1016/J.RIAI.2015.07.006 DIALNET GOOGLE SCHOLAR lock_openSarbide irekia editor

Beste argitalpen batzuk: Revista iberoamericana de automática e informática industrial ( RIAI )

Garapen Iraunkorreko Helburuak

Laburpena

This paper presents a new control scheme for a standalone photovoltaic (PV) system based on a fuzzy-logic (FLC). The proposed control system provides good tracking for the optimal reference voltage, at which the maximum power generation is obtained. The photovoltaic system is connected to a load through a DC/DC boost converter. The FLC controller provides the appropriate duty cycle (D) to the DC/DC converter in order to get the maximum power from the PV system. A method for the stability analysis of the closed-loop system is also proposed. The stability analysis is based on the Lyapunov methods and is a semi-qualitative analysis because there is no closed loop system model available for the analytical analysis. Both simulation results and experimental tests on a real PV system show that the FLC provides good tracking for the maximum power point (MPP).Finally, the performance of the FLC on a real PV system consisting of a commercial solar panels Atersa model A55 is analyzed. To perform the experimental tests the proposed control strategy has been implemented on the dSPACE digital signal processor model DS1104. The experimental results demonstrate the good performance of the proposed FLC control scheme over a commercial photovoltaic system

Erreferentzia bibliografikoak

  • Abderrahim E.F, Fouad. G, Abdelmoinime E.M. (2013), Reference Voltage Optimizer for Maximum Power Tracking in Single-Phase Grid-Connected Photovoltaic Systems, Journal of Control and Systems Engineering 1 (2), 57-66.
  • Alajmi, B.N., Ahmed, K.H., Finney S.J and. Williams B.W. (2011). FuzzyLogic-Control Approach of a Modified Hill-Climbing Method for Maximum Power Point in Microgrid Standalone Photovoltaic System. IEEE Transactions on Power Electronics 26 (4): 1022-1030.
  • Algazar, M.M., AL-Monier H., EL-Halim H. A., El Kotb Salem M E (2012) Maximum Power Point Tracking Using Fuzzy Logic Control. International Journal of Electrical Power & Energy Systems 39 (1): 21-28.
  • Andújar. J. M, Barragán. A.J, (2014), Hibridación de sistemas borrosos para el modelado y control. Revista Iberoamericana de Automática e Informática industrial, 11 (2), 127-141.
  • Andújar, J. M, Segura, F. (2012), Power Management Based on Sliding Control Applied to Fuel Cell System. A further Step toward the Hybrid Control Concept.Applied Energy.99, 213-225.
  • Andújar. J. M, Barragán.A.J, Gegúndez.M.E, Maestre.M (2007), Control Borroso Multivariable Basado en Heurística. Un Caso Práctico: Grúa Porta Contenedores, Revista Iberoamericana de Automática e Informática industrial, 4 (2) ,81–89.
  • Brunton S.L., Rowley C.W., Kulkarni S.R., Clarkson C. (2010), Maximum Power Point Track- ing for Photovoltaic Optimization Using Ripple-Based Extremum Seeking Control, IEEE Trans. on Power Electronics Vol.25, No.10
  • Chokri. B. S, Mohamed. O (2011), Comparison of Fuzzy Logic And Neural Network In Maximum Power Point Tracker For PV Systems, Electric Power Systems Research,.81, 43–50.
  • Durán, E, Andújar, J. M., Galan, J., Sidrach de Cardona, M, (2009), Methodology and Experimental System for Measuring and Displaying I-V Characteristic Curves of PV Facilities. Progress in Photovoltaics.,17 (8), pp 574-586.
  • Farhat, M., Flah, A., Sbita, L., (2014), Photovoltaic Maximum Power Point Tracking Based on ANN Control, International Review on Modelling and Simulations, 7 (3), 474 – 480.
  • Farhat. M, Sbita.L, (2012), Advanced ANFIS-MPPT Control Algorithm for Sunshine photovoltaic Pumping Systems," International Conference on Renewable Energies and Vehicular Technology,
  • Farhat. M, Sbita.L (2011), Advanced Fuzzy MPPT Control Algorithm for Photovoltaic Systems, Science Academy Transactions on Renewable Energy Systems Engineering and Technology, 1, (1), pp. 29-36.
  • Fazel.T, Zainal. S, Shahrin. M. A, (2012), FPGA Implementation of a SingleInput Fuzzy Logic Controller for Boost Converter With the Absence of an External Analog-to-Digital Converter, IEEE transactions on industrial electronics, 59 (2), 1208- 1217.
  • Hannan. M. A, Ghani. Abd. Z, Mohamed.A, (2010), An Enhanced Inverter Controller for PV Applications Using the dSPACE Platform, Hindawi Publishing Corporation, International Journal of Photoenergy.
  • Hirosato. S, (2013), Nonlinear Identi¿cation Using Single Input Connected Fuzzy Inference Model, 17th International Conference in Knowledge Based and Intelligent Information and Engineering Systems,.
  • Jungyong. P, Shiho. K, (2012), Maximum Power Point Tracking Controller for Thermoelectric Generators with Peak Gain Control of Boost DC–DC Converters, Journal of Electronic Materials, 41(6), 1242-1246.
  • Marcelo. G.V., Jonas. R. G, Ernesto. R. F (2009), Modeling and circuit-based simulation of photovoltaic arrays, 10th Brazilian Power Electronics Conference (COBEP)
  • Nevzat. O, (2010), Recent Developments in Maximum Power Point Tracking Technologies for Photovoltaic Systems, Hindawi Publishing Corporation International Journal of Photoenergy
  • Ollervides.J, Santibáñez..M, Lama.A, Dzul.A, (2010), Aplicación de Control Borroso a un Sistema de Suspensión Magnética: Comparación Experimental, Revista Iberoamericana de Automática e Informática industrial, 7 (3) ,1697–7912.
  • Patcharaprakiti, N., Suttichai P., and Sriuthaisiriwong Y., (2005). Maximum Power Point Tracking Using Adaptive Fuzzy Logic Control for GridConnected Photovoltaic System. Renewable Energy 30 (11): 1771-1788.
  • Shiqiong. Z, Longyun. K, Jing. S, Guifang.G, Bo Cheng, B Cao, Yiping. T (2010), A novel maximum power point tracking algorithms for stand-alone photovoltaic, system, International Journal of Control, Automation and Systems, 8 (6), 1364-1371.
  • Trishan.E, Patrick L. C, (2007), Comparison of Photovoltaic Array Maximum Power Point Tracking, Techniques, IEEE Trans. on Energy conversion, 22(2), 439-449.
  • Villalva, M.G. Gazoli, J.R.; Filho, E.R., May (2009) Comprehensive Approach to Modeling and Simulation of Photovoltaic Arrays, IEEE Transactions on power electronics, 24 (5), pp. 1198 – 1208.
  • Zaidi. Z, F. Boudjema, (2010), Hybrid Control and Optimization of a PlusEnergy-House with DHWS, International Renewable Energy Congress IREC, Sousse, Tunisia.
Datuen iturria: Dialnet