Performance Study of Neural Network and ANFIS Based MPPT Methods For Grid Connected PV System

The maximum power point tracking (MPPT) methods are applied in PV solar systems to accomplish the desired maximum power from the PV system. Hence, it is important to design the best technique which can reach the maximum power point (MPP) effectively. In this paper, a grid connected PV system is controlled by artificial neural network (ANN) and adaptive neuro-fuzzy system (ANFIS) based MPPT methods. Both of proposed MPPT methods are analyzed related to their performance efficiency and response under the variation of solar irradiation and cell temperature. The obtained results of both methods are compared to experimental results which show that ANFIS has more response and efficiency than ANN in maximum power point tracking. The investigation has been done by using MATLAB/Simulink Environment.

[1]  Mansour Souissi,et al.  Maximum Power Point Tracking Control Using Neural Networks for Stand-Alone Photovoltaic Systems , 2014 .

[2]  Mohamed A. Awadallah,et al.  Parameters estimation of photovoltaic modules: comparison of ANN and ANFIS , 2014 .

[3]  Soteris A. Kalogirou,et al.  MPPT-based artificial intelligence techniques for photovoltaic systems and its implementation into field programmable gate array chips: Review of current status and future perspectives , 2014 .

[4]  Martin Brown,et al.  Neurofuzzy adaptive modelling and control , 1994 .

[5]  Mohammad Hassan Moradi,et al.  Classification and comparison of maximum power point tracking techniques for photovoltaic system: A review , 2013 .

[6]  Engin Karatepe,et al.  Artificial neural network-polar coordinated fuzzy controller based maximum power point tracking control under partially shaded conditions , 2009 .

[7]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[8]  A. S. Vanmukhil,et al.  Photovoltaic Generation System with MPPT Control Using ANFIS , 2013 .

[9]  Bhavnesh Kumar,et al.  A comparative study of maximum power point tracking methods for a photovoltaic-based water pumping system , 2014 .

[10]  Carlos A. Canesin,et al.  Evaluation of the Main MPPT Techniques for Photovoltaic Applications , 2013, IEEE Transactions on Industrial Electronics.

[11]  Moumi Pandit,et al.  Controlling Output Voltage of Photovoltaic Cells using ANFIS and Interfacing it with Closed Loop Boost Converter , 2013 .

[12]  Kashif Ishaque,et al.  A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition , 2013 .