Identification of Multiple Input-Single Output (MISO) model for MPPT of Photovoltaic System

This paper presents a modelling of Multiple Input-Single Output (MISO) model for tracking maximum point of Photovoltaic (PV) Systems. A system identification approach is used to obtain the model characteristics of existing structural systems through dynamic observations which incorporate with traditional direct control Maximum Power Point Tracking (MPPT) algorithm. The generate model characteristics was used in designing the MPPT of the Photovoltaic Systems. The need of an efficient mathematical model to characterize the dynamics system for PV is essential for implementing the system for control applications. In this paper, the transfer function relating the input parameters (Solar irradiance and cell temperature) and output parameter (DC current) of the PV module MF120EC3 was identify with the aid of MISO for Auto-Regressive with eXogenous input (ARX) model. The approach has concern on the estimation of the (Direct Current (DC) for photovoltaic system based on the real systems data from Pusat Tenaga Malaysia (Malaysia Energy Centre, MEC). A Fourth-order autoregressive (ARX) model using the ARX algorithm, (ARXQS) was chosen since the model output provide 93.42% best fit model criteria. The modelling is implemented using system identification toolbox of Matlab software.

[1]  Bimal K. Bose,et al.  Neural Network Applications in Power Electronics and Motor Drives—An Introduction and Perspective , 2007, IEEE Transactions on Industrial Electronics.

[2]  Saad Mekhilef,et al.  Simulation and Hardware Implementation of Incremental Conductance MPPT With Direct Control Method Using Cuk Converter , 2011, IEEE Transactions on Industrial Electronics.

[3]  H. Erdo.  Identification of dynamic systems using Multiple Input-Single Output (MISO) models , 2009 .

[4]  Zakaria Hussain,et al.  Identification of Hammerstein-Weiner System for Normal and Shading Operation of Photovoltaic System , 2012 .

[5]  Venkataramanan Balakrishnan,et al.  System identification: theory for the user (second edition): Lennart Ljung; Prentice-Hall, Englewood Cliffs, NJ, 1999, ISBN 0-13-656695-2 , 2002, Autom..

[6]  Ze Cheng,et al.  Research on MPPT control of PV system based on PSO algorithm , 2010, 2010 Chinese Control and Decision Conference.

[7]  N. Dasgupta,et al.  High-Performance Algorithms for Drift Avoidance and Fast Tracking in Solar MPPT System , 2008, IEEE Transactions on Energy Conversion.

[8]  Venkataramanan Balakrishnan,et al.  System identification: theory for the user (second edition): Lennart Ljung; Prentice-Hall, Englewood Cliffs, NJ, 1999, ISBN 0-13-656695-2 , 2002, Autom..

[9]  J. H. Schuppen.  System theory for system identification , 2004 .

[10]  Ma Youjie,et al.  The simulation and design for MPPT of PV system Based on Incremental Conductance Method , 2010, 2010 WASE International Conference on Information Engineering.

[11]  Massimo Vitelli,et al.  A Technique for Improving P&O MPPT Performances of Double-Stage Grid-Connected Photovoltaic Systems , 2009, IEEE Transactions on Industrial Electronics.