This paper proposes an artificial- intelligence-based solution to interface photovoltaic (PV) array with the three phase ac load and to deliver maximum power to the load. The maximum power delivery to the load is achieved by MPPT controller which employs adaptive neuro-fuzzy inference system (ANFIS). The proposed ANFIS-based MPPT offers an extremely fast dynamic response with great accuracy. The system consists of photovoltaic module, boost converter, voltage source inverter (VSI) and ANFIS controller to control the duty cycle of boost converter switch as well as the modulation index of VSI. The entire proposed system has been modeled and simulated using MATLAB/simulink software. The simulation results show that the proposed ANFIS MPPT controller is very efficient, very simple and low cost.

1. T. Esram and P. L. Chapman, "Comparison of photovoltaic array maximum power point tracking techniques," IEEE Trans. Energy Convers. , vol. 22, no. 2, pp. 439–449, Jun. 2007.
2. W. Xiao, W. G. Dunford, and A. Capel, "A novel modeling method for photovoltaic cells", in Proc. IEEE 35th Annu. Power Electron. Spec. Conf. (PESC), 2004, vol. 3, pp. 1950–1956.
3. S. Arul Daniel and N. AmmasaiGounden"A Novel Hybrid Isolated Generating System Based on PV Fed Inverter-Assisted Wind-Driven Induction Generators," IEEE Transactions On Energy Conversion, Vol. 19, no. 2, June 2004
4. G. Chen and T. T. Pham, Introduction to Fuzzy Sets, Fuzzy Logic, and Fuzzy Control Systems. Boca Raton, FL: CRC Press, 2000.
5. G. R. Walker and P. C. Senia, "Cascaded DC-DC converter connection of photovoltaic modules," IEEE Trans. Power Electron. , vol. 19, no. 4,pp. 1130–1139, Jul. 2004
6. L. Quan and P. Wolfs, "A review of the single phase photovoltaic module integrated converter topologies with three dc link configurations,"IEEE Trans. Power Electron. , vol. 23, no. 3, pp. 1320–1333,May 2008.
7. B. Yang, L. Wuhua, Y. Zhao, and H. Xianging, "Design and analysis of a grid-connected photovoltaic power system," IEEE Trans. Power Electron. , vol. 25, no. 4, pp. 992–1000, Apr. 2010
8. B. M. T. Ho and S. -H. Cheng, "An integrated inverter with maximum power tracking for grid-connected PV systems," IEEE Trans. PowerElectron. , vol. 20, no. 4, pp. 953–962, Jul. 2005.
9. Haitham Abu-Rub, Senior Member, IEEE, AtifIqbal, Senior Member, IEEE, Sk. MoinAhmed, Member, IEEE,Fang Z. Peng, Fellow, IEEE, Yuan Li, Member, IEEE, and GeBaoming Member, IEEE "Quasi-Z-Source Inverter-based photovoltaic generation system with Maximum Power Point tracking control using ANFIS," IEEE Transactions on sustainable energy.
10. A. de Medeiros Torres, F. L. M. Antunes, and F. S. dos Reis, "An artificialneural network-based real time maximum power tracking controller for connecting a PV system to the grid," in Proc. IEEE 24th Ann. Conf. Industrial Electronics Society, 1998, vol. 1, pp. 554–558. 06.
11. Ansari, S. Chaterjee, and A. Iqbal, "Fuzzy logic control scheme for solar photo voltaic system for maximum power point tracker," Int. J Sustain. Energy, vol. 29, no. 4, pp. 245–255, Apr. 2010.
12. A. M. S. Aldobhani and R. John, "Maximum power point tracking of PV system using ANFIS prediction and fuzzy logic tracking," in ProInt. Multiconf. Engineers and Computer Scientists (IMECS), HonKong, Mar. 19–21, 2008, vol. II, CD-ROM.
13. K. H. Hussein, I. Muta, T. Hoshino, M. Osakada, "Maximum photovoltaic power tracking: an algorithm for rapidly changing atmospheric conditions", IEE Proc. -Gener. Trans. Distrib. , Vol. 142, No. 1, January 1995.
14. T. L. Kottas, Y. S. Boutalis, and A. D. Karlis, "New maximum power tracker for PV arrays using fuzzy controller in close cooperation with fuzzy cognitive networks," IEEE Trans. Energy Convers. , vol. 21,
15. T. Hiyama and K. Kitabayashi, "Neural network based estimation of maximum power generation from PV module using environmental information,"IEEE Trans. Energy Convers. , vol. 12, no. 3, pp. 241–247,Sep. 1997

Mppt Anfis Boost Converter Vsi Photovoltaic System