Adaptive Neuro-Fuzzy Model for Grid-Connected Photovoltaic System

AbstractThis paper proposed an adaptive neuro-fuzzy inference system (ANFIS) model to multilevel inverter for grid-connected photovoltaic (PV) system. The purpose of the proposed controller is to avoid the requirement of any optimal PWM (pulse width-modulated) switching-angle generator and proportional–integral controller. The proposed method strictly prevents the variations present in the output voltage of the cascaded H-bridge multilevel inverter. Here, the ANFIS models have the inputs which are the grid voltage and the difference voltage, and the output target is the control voltage. By means of these parameters, the ANFIS makes the rules and can be tuned perfectly. During the testing time, the ANFIS provides the control voltage according to the different inputs. Then, the ANFIS-based algorithm for multilevel inverter for grid-connected PV system is implemented in the MATLAB/simulink platform, and the effectiveness of the proposed control technique is analyzed by comparing the model’s performances with the neural network, fuzzy logic control, etc.

[1]  M. Liserre,et al.  Future Energy Systems: Integrating Renewable Energy Sources into the Smart Power Grid Through Industrial Electronics , 2010, IEEE Industrial Electronics Magazine.

[2]  J.J. Mora,et al.  Fault Location in Power Distribution Systems using ANFIS Nets and Current Patterns , 2006, 2006 IEEE/PES Transmission & Distribution Conference and Exposition: Latin America.

[3]  S. P. Natarajan,et al.  FPGA based Fuzzy Logic Control for Single Phase Multilevel Inverter , 2010 .

[4]  C. Larbes,et al.  Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system , 2009 .

[5]  Venu Gopala Rao,et al.  Control of a Three-Phase Cascaded H-Bridge Multilevel Inverter for Stand-alone PV System , 2012 .

[6]  Adel M. Sharaf,et al.  A novel maximum power fuzzy logic controller for photovoltaic solar energy systems , 2008 .

[7]  Yuzuru Ueda,et al.  Analysis Results of Output Power Loss Due to the Grid Voltage Rise in Grid-Connected Photovoltaic Power Generation Systems , 2008, IEEE Transactions on Industrial Electronics.

[8]  R. Seyezhai,et al.  Design and Development of Hybrid Multilevel Inverter employing Dual Reference Modulation Technique for Fuel Cell Applications , 2011 .

[9]  Nasrudin Abd Rahim,et al.  Five-level inverter with dual reference modulation technique for grid-connected PV system , 2010 .

[10]  Gorazd Štumberger,et al.  Operational properties of a photovoltaic system with three single phase inverters , 2010 .

[11]  Mamadou Lamine Doumbia,et al.  An improved maximum power point tracking method for photovoltaic systems , 2008 .

[12]  Jiabing Hu,et al.  Direct Active and Reactive Power Regulation of Grid-Connected DC/AC Converters Using Sliding Mode Control Approach , 2011, IEEE Transactions on Power Electronics.

[13]  Kostas Kalaitzakis,et al.  Development of a microcontroller-based, photovoltaic maximum power point tracking control system , 2001 .

[14]  Francisco D. Freijedo,et al.  Multilevel Multiphase Space Vector PWM Algorithm , 2008, IEEE Transactions on Industrial Electronics.

[15]  P. S. Manoharan,et al.  FPGA based multilevel cascaded inverters with SVPWM algorithm for photovoltaic system , 2013 .

[16]  Keith A. Corzine,et al.  Multilevel voltage-source duty-cycle modulation: analysis and implementation , 2002, IEEE Trans. Ind. Electron..

[17]  Moncef Jraidi,et al.  New control strategy for 2-stage grid-connected photovoltaic power system , 2008 .

[18]  Wei-Yen Hsu,et al.  Motor Imagery Electroencephalogram Analysis Using Adaptive Neural-Fuzzy Classification , 2014 .

[19]  Engin Karatepe,et al.  Polar coordinated fuzzy controller based real-time maximum-power point control of photovoltaic system , 2009 .

[20]  Leon M. Tolbert,et al.  Adaptive Selective Harmonic Minimization Based on ANNs for Cascade Multilevel Inverters With Varying DC Sources , 2013, IEEE Transactions on Industrial Electronics.

[21]  Giampaolo Buticchi,et al.  A Nine-Level Grid-Connected Converter Topology for Single-Phase Transformerless PV Systems , 2014, IEEE Transactions on Industrial Electronics.

[22]  Zhong Du,et al.  Control of a multilevel converter using resultant theory , 2003, IEEE Trans. Control. Syst. Technol..

[23]  Pierluigi Siano,et al.  A Multilevel Inverter for Photovoltaic Systems With Fuzzy Logic Control , 2010, IEEE Transactions on Industrial Electronics.

[24]  Daniel Foito,et al.  A Grid Connected Photovoltaic System with a Multilevel Inverter and a Le-Blanc Transformer , 2012 .

[25]  T. R. Sumithira,et al.  Elimination of Harmonics in Multilevel Inverters Connected to Solar Photovoltaic Systems Using ANFIS: An Experimental Case Study , 2013 .

[26]  S. Saetieo,et al.  Fuzzy logic control of a space vector PWM current regulator for three phase power converters , 1997, Proceedings of APEC 97 - Applied Power Electronics Conference.

[27]  Paolo Mattavelli,et al.  General-purpose fuzzy controller for DC/DC converters , 1995, Proceedings of 1995 IEEE Applied Power Electronics Conference and Exposition - APEC'95.

[28]  Leon M. Tolbert,et al.  Elimination of Harmonics in a Modular Multilevel Converter Using Particle Swarm Optimization-Based Staircase Modulation Strategy , 2014, IEEE Transactions on Industrial Electronics.

[29]  Nasrudin Abd Rahim,et al.  Elimination of Harmonics in Photovoltaic Seven-level Inverter with Newton-raphson Optimization , 2013 .

[30]  Fabrice Locment,et al.  Maximum power tracking for photovoltaic power system: Development and experimental comparison of two algorithms , 2010 .

[31]  Rashad M. Kamel,et al.  A novel multi-model neuro-fuzzy-based MPPT for three-phase grid-connected photovoltaic system , 2010 .