An intelligent reconfiguration approach based on fuzzy partitioning in PV arrays

The reconfiguration process in photovoltaic (PV) arrays is very important to obtain maximum power under partial shading conditions. Connection architecture of array for this process is changed according to status of non-uniform shadows. However, finding of best connection in big PV arrays is hard in real-time. In this paper, a new efficient and intelligent reconfiguration approach based on partitioning of array is proposed. The proposed approach is aimed to search best connection from possible connections in several small-sized array partitions obtained with decomposing according to location of shadows to carry out control task. Thus, search space of possible connections is considerably reduced for using in real time implementation of reconfiguration process in big size PV arrays. Efficiency, accuracy, and performance proposed reconfiguration approach has been verified for different size and shading conditions with comparative simulation results.

[1]  Guillermo Velasco-Quesada,et al.  Electrical PV Array Reconfiguration Strategy for Energy Extraction Improvement in Grid-Connected PV Systems , 2009, IEEE Transactions on Industrial Electronics.

[2]  S. K. Kollimalla,et al.  Adaptive perturb & observe MPPT algorithm for photovoltaic system , 2013, 2013 IEEE Power and Energy Conference at Illinois (PECI).

[3]  Massimo Vitelli,et al.  Distributed maximum power point tracking of photovoltaic arrays: Novel approach and system analysis , 2008, IEEE Transactions on Industrial Electronics.

[4]  A. Bidram,et al.  Control and Circuit Techniques to Mitigate Partial Shading Effects in Photovoltaic Arrays , 2012, IEEE Journal of Photovoltaics.

[5]  Koray Sener Parlak.  A New reconfiguration method for PV array system , 2013, IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society.

[6]  Paula dos Santos,et al.  Reconfiguration methodology of shaded photovoltaic panels to maximize the produced energy , 2011, XI Brazilian Power Electronics Conference.

[7]  M. M. A. Salama,et al.  Optimal photovoltaic array reconfiguration to maximize power production under partial shading , 2012, 2012 11th International Conference on Environment and Electrical Engineering.

[8]  Radhia Garraoui,et al.  MPPT controller for a photovoltaic power system based on fuzzy logic , 2013, 10th International Multi-Conferences on Systems, Signals & Devices 2013 (SSD13).

[9]  Yanli Liu,et al.  An adaptive solar photovoltaic array reconfiguration method based on fuzzy control , 2010, 2010 8th World Congress on Intelligent Control and Automation.

[10]  Rubiyah Yusof,et al.  Analytical modeling of partially shaded photovoltaic systems , 2013 .

[11]  Kay Soon Low,et al.  A Global Maximum Power Point Tracking Scheme Employing DIRECT Search Algorithm for Photovoltaic Systems , 2010, IEEE Transactions on Industrial Electronics.

[12]  M Karakose,et al.  The intelligent fault diagnosis frameworks based on fuzzy integral , 2010, SPEEDAM 2010.

[13]  Yanli Liu,et al.  Research on an adaptive solar photovoltaic array using shading degree model-based reconfiguration algorithm , 2010, 2010 Chinese Control and Decision Conference.

[14]  H. A. Ashour,et al.  Maximum power point tracking for irregular irradiance of a photovoltaic array , 2013, 2013 12th International Conference on Environment and Electrical Engineering.

[15]  Brad Lehman,et al.  An Adaptive Solar Photovoltaic Array Using Model-Based Reconfiguration Algorithm , 2008, IEEE Transactions on Industrial Electronics.

[16]  M. Balato,et al.  A hybrid MPPT technique based on the fast estimate of the Maximum Power voltages in PV applications , 2013, 2013 Eighth International Conference and Exhibition on Ecological Vehicles and Renewable Energies (EVER).

[17]  V. Agarwal,et al.  MATLAB-Based Modeling to Study the Effects of Partial Shading on PV Array Characteristics , 2008, IEEE Transactions on Energy Conversion.