Adaptive photovoltaic array reconfiguration based on real cloud patterns to mitigate effects of non-uniform spatial irradiance profiles

Abstract This paper proposes a simple and dynamic reconfiguration algorithm for photovoltaic (PV) arrays in order to mitigate negative effects of non-uniform spatial irradiance profiles on PV power production. Spatially dispersed irradiance profiles incident on inclined PV module surfaces at each application site are generated based on real sky images. Models of PV modules are constructed in MATLAB/Simulink based on one-diode mathematical model of a PV cell. The proposed dynamic reconfiguration algorithm operates based on irradiance equalization principle aiming for creation of balanced-irradiance series-connected rows of PV modules. The proposed algorithm utilizes an irradiance threshold to obtain near-optimal configurations in terms of irradiance equalization and number of switching actions under any type of non-uniform spatial irradiance profile. The algorithm provides no limits on the number of PV modules within the array. The reconfiguration algorithm is examined with different irradiance profiles and significant improvements, almost equivalent to the ideal case corresponding to equal irradiance for all panels, are achieved for each shading pattern. The advantages of the algorithm are simplicity and providing significant improvements in array’s power generation alongside with reduced number of switching actions.

[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]  N. D. Kaushika,et al.  Energy yield simulations of interconnected solar PV arrays , 2002, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[3]  M. M. A. Salama,et al.  Optimal Photovoltaic Array Reconfiguration to Reduce Partial Shading Losses , 2013, IEEE Transactions on Sustainable Energy.

[4]  P. R. Wilson,et al.  Improved Optimization Strategy for Irradiance Equalization in Dynamic Photovoltaic Arrays , 2013, IEEE Transactions on Power Electronics.

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

[6]  Mahmoud Alahmad,et al.  An adaptive utility interactive photovoltaic system based on a flexible switch matrix to optimize performance in real-time , 2012 .

[7]  J. Kleissl,et al.  Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed , 2011 .

[8]  Syafaruddin,et al.  Modeling and simulation of photovoltaic (PV) system during partial shading based on a two-diode model , 2011, Simul. Model. Pract. Theory.

[9]  R. Ramaprabha,et al.  A Comprehensive Review and Analysis of Solar Photovoltaic Array Configurations under Partial Shaded Conditions , 2012 .

[10]  Marcelo Gradella Villalva,et al.  Comprehensive Approach to Modeling and Simulation of Photovoltaic Arrays , 2009, IEEE Transactions on Power Electronics.

[11]  Syafaruddin,et al.  A comprehensive MATLAB Simulink PV system simulator with partial shading capability based on two-diode model , 2011 .

[12]  Jan Kleissl,et al.  Stereographic methods for cloud base height determination using two sky imagers , 2014 .

[13]  B. Patnaik,et al.  Distributed multi-sensor network for real time monitoring of illumination states for a reconfigurable solar photovoltaic array , 2012, 2012 1st International Symposium on Physics and Technology of Sensors (ISPTS-1).

[14]  R. Dougal,et al.  Dynamic Multi-Physics Model for Solar Array , 2002 .

[15]  Aissa Chouder,et al.  Study of bypass diodes configuration on PV modules , 2009 .

[16]  Giuseppe Carannante,et al.  Experimental Performance of MPPT Algorithm for Photovoltaic Sources Subject to Inhomogeneous Insolation , 2009, IEEE Transactions on Industrial Electronics.