Publication Type : Journal Article
Publisher : Springer Science and Business Media LLC
Source : Smart Grids and Sustainable Energy
Url : https://doi.org/10.1007/s40866-023-00163-4
Campus : Coimbatore
School : School of Artificial Intelligence
Year : 2023
Abstract : The photovoltaic (PV) arrays are inevitably subjected to partial shading (PS) conditions that highly limit the output. To mitigate these effects, various reconfiguration procedures have been executed by the researchers. However, many of these procedures fail to disperse the shade effectively over the entire array and hence there is a dire need for such an efficient reconfiguration technique. This paper explores Knight’s Tour Magic square (KTM) and Doubly Even-order Magic square (DEM) techniques which effectively disperse the shadow by reconfiguring the array without altering the electrical connections. To examine the superiority of the proposed techniques, their performance has been compared with conventional total-cross-tied, existing odd-even and odd-even-prime configurations of a symmetric 8 × 8 and asymmetric 4 × 3 PV arrays. Further, the applicability of the proposed techniques is proved by analysing the system with eight performance parameters such as global maximum power, power mismatch, percentage losses, efficiency, fill factor, capacity factor, array yield, and performance ratio under 20 distinct PS patterns. The power enhancement in GMP using the KTM and DEM approaches are nearly 42.67%, 17.87%, 16.24%, 8.04% for asymmetric arrays, and 26.43%, 25.38%, 25.09%, 15.61%, 10.63%, for the symmetric arrays. Finally, a comprehensive economic analysis is also performed, and it is observed that there is a significant augmentation in the number of units and the revenue generated by employing the proposed techniques.
Cite this Research Publication : Rayappa David Amar Raj, Kanasottu Anil Naik, Novel Shade Dispersion Techniques for Reconfiguration of Partially Shaded Photovoltaic Arrays, Smart Grids and Sustainable Energy, Springer Science and Business Media LLC, 2023, https://doi.org/10.1007/s40866-023-00163-4