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Control of Z-Source Inverter Based PV System with MPPT Using ANFIS

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This paper presents an artificial intelligence based MPPT technique to deliver maximum power from a photo-voltaic (PV) system for three phase resistive load. Z-source inverter (ZSI) is employed in the system to boost PV module output voltage as well as inversion of voltage simultaneously in a single-stage. Here PV cell and PV module model are developed from mathematical equations. The ZSI eliminates the limitations of conventional boost converter interfaced with voltage source inverter (VSI). Simple boost control technique with sinusoidal pulse width modulation is used here for ZSI. Inductor and capacitor values are calculated for Z-source network. In the proposed system duty ratio control of ZSI is developed to control the output power of PV panel. Maximum power point tracking (MPPT) technique using Adaptive Neuro-Fuzzy Inference System (ANFIS) is developed and trained with hybrid learning algorithm to identify parameters of Sugeno-type fuzzy inference systems using Matlab/Simulink tool box for PV module.ANFIS based MPPT is trained with various membership functions like trapezoidal, gauss and bell membership function .Comparative study is done for the complete system using both the artificial neural network (ANN) based MPPT technique and ANFIS based MPPT technique, based on their performance parameters and simulated results in MATLAB/Simulink.
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ANFIS; ANN; Boost Converter; Duty Ratio; Non Shoot-Through Mode; Sinusoidal Pulse Width Modulation; PV Module; Shoot-Through Mode; Simple Boost Control; Voltage Source Inverter; Z-Source Inverter

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Haitham Abu-Rub, Atif Iqbal,Sk.MoinAhmed,FangZ.Peng and YuanLi ,Quasi-Z Source Inverter-Based Photovoltaic Generation System With Maximum Power Tracking Control Using ANFIS,IEEE Trans. on sustainable Energyvol.4,n.1,Jan. 2013.

T. Santhi and A.S Vanmukhil ,ANFIS Controller Based MPPT Control of Photovoltaic Generation System,Research Journal of Applied Sciences 8 (7),2013,pp. 357-382.

Witold Maranda and Maciej Piotrowicz, Calculation of Dynamic MPP-Tracking Efficiency of PV-Inverter Using Recorded Irradiance”20th International Conference,Mixed Design of Integrated Circuits and Systems, June 20-22, 2013

Mahsa KangaraniFarahani and Soheil Mehralian, Comparison Between Artificial Neural Network and Neuro-Fuzzy for Gold Price Prediction,13th Iranian Conference on Fuzzy Systems (IFSC),2013.

A.Durgadevi,S.Arulselvi,ANFIS Modeling and Experimental Study of Standalone Photovoltaic Battery Charging System, IJMER vol. 2, issue.4, Aug. 2012,pp. 2516-2520 ISSN: 2249-6645.

Adel Mellit and Soteris A.Kalogirou, ANFIS-based modelling for photovoltaic power supply system :A case study,Renewable Energy 36 .2011,pp. 250-258.

G. A. Rampinelli,M. A. A. Teyra, A. Krenzinger and C. W. M. Prieb,Artificial Intelligence Techniques Applied to Energetic Analysis of Photovoltaic Systems, IEEE Latin America trans., vol. 8, n. 5, Sep. 2010.

Rym Marouani and Abdel kader Mami,Voltage Oriented Control Applied to a Grid Connected Photovoltaic System with Maximum Power Point Tracking Technique, American Journal of Applied Sciences 7(8,)2010, pp. 1168-1173, ISSN 1546-9239.

Abdulaziz M. S. Aldobhani and Robert John ,Maximum Power Point Tracking of PV System Using ANFIS Prediction and Fuzzy Logic Tracking, IMECS, vol II ,19-21 March, 2008.

Adel Mellit and Soteris A. Kalogirou, Artificial intelligence techniques for photovoltaicn applications: A review,Science Direct, Progress in Energy and Combustion Science 34,2008, pp. 574–632.

Baoming Ge, HaithamAbu-Rub, FangZheng Peng, Qin Lei, Student, AníbalT. de Almeida,Fernando J.T. E. Ferreira, Dongsen Sun, and YushanLiu, An Energy-Stored Quasi-Z-Source Inverter for Application to Photovoltaic Power System, IEEE Transactions On Industrial Electronics,vol.60,n.10,Oct 2013.

Po Xu, Xing Zhang,Chong-Wei Zhang Ren-Xian,Cao and Liuchen Chang, Study of Z-Source Inverter for Grid-Connected PV Systems, IEEE Power Electronics Specialist Conference, Jun 2006.

YuanLi,ShuaiJiang, JorgeG. Cintron-Rivera,and Fang Zheng Peng, Modeling and Control of Quasi-Z-SourceInverter for Distributed Generation Applications, IEEE Transactions On Industrial Electronics, vol. 60,n. 4, April, 2013.

R. Seyezhai, Abinaya K, Akshaya V and Induja U” Simulation, Analysis And Development of Pv Fed Quasi Impedance Source Inverter” International Journal of Electrical and Electronics ,vol. 3, Aug 2013, pp. 201-212.

Dongsen Sun, Baoming Ge , Daqiang Bi and Fang Z. Peng, Analysis and control of quasi-Z source inverter with battery for grid-connected PV system,Electrical Power and Energy Systems 46,2013,pp. 234–240

Poh Chiang Loh, D. MahindaVilathgamuwa, Yue Sen Lai, Geok Tin Chua and Yunwei Li, Pulse Width Modulation of Z-Source Inverters, IEEE Transactions on power electronics, vol. 20, n. 6, Nov 2005.

Fang Peng,Miaosen Shen and ZhaomingQian,Maximum boost control of the Z-source inverter, 35rh Annual IEEE Power Electronics SpecialisrsConference,Germany2004.

Fang Zheng Peng, Z-Source Inverter, IEEE Trans. on Industrial Application,vol. 39, n. 2, April 2003.

Chitra, K., Jeevanandham, A., Ashok, N., Design and realization of maximum boost switched inductor Z-source inverter for three phase on-line UPS, (2014) International Review on Modelling and Simulations (IREMOS), 7 (1), pp. 16-21.

Blorfan, A., Sturtzer, G., Flieller, D., Wira, P., Merckle J., An adaptive control algorithm for maximum power point tracking for photovoltaic energy conversion systems - A comparative study, (2014) International Review of Electrical Engineering (IREE), 9 (3), pp. 559-565.

Hossain, M.K., Ali, M.H., Overview on maximum power point tracking (MPPT) techniques for photovoltaic power systems, (2013) International Review of Electrical Engineering (IREE), 8 (4), pp. 1363-1378.

Melhaoui, M., Baghaz, E., Hirech, K., Yaden, F., Kassmi, K., Contribution to the improvement of the MPPT control functioning of photovoltaic systems, (2014) International Review of Electrical Engineering (IREE), 9 (2), pp. 393-400.

Farhat, M., Flah, A., Sbita, L., Photovoltaic maximum power point tracking based on ANN control, (2014) International Review on Modelling and Simulations (IREMOS), 7 (3), pp. 474-480.


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