EPJ Photovoltaics 17, 24 (2026)
https://doi.org/10.1051/epjpv/2026016

Original Article

Performance assessment of advanced static reconfiguration strategies to address realistic shading of solar arrays

¹ Energetic Engineering and Computer Engineering Laboratory (L2GEGI), Department of Electrical Engineering, University of Tiaret, 14000 Tiaret, Algeria
² Univ Paris Est Créteil, CERTES, F-94010 Créteil, France
³ Power Electronics and Renewable Energy Research Laboratory (PEARL), Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia

^* e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 24 January 2026
Accepted: 1 June 2026
Published online: 3 July 2026

Abstract

Partial shading conditions (PSCs) represent a complex and often unavoidable challenge in photovoltaic (PV) systems, leading to reduced maximum power output and causing mismatch losses. PSCs also result in multiple peaks on the power–voltage (P–V) curve, where the maximum power can become trapped at local maxima. Array reconfiguration techniques are therefore essential for improving the efficiency of the system and ensuring optimal power extraction from PV systems. In this study, the conventional Total-Cross-Tied (TCT) and eight advanced methods for static reconfiguration were analyzed. These include: Shape-Do-Ku (SPDK), Ken-Ken (KK), Skyscraper (SS), Jigsaw (JS), Kendoku (KDT), Novel Grecian Reconfiguration (NGR), Novel Ramanujan Reconfiguration (NRR), and Super Magic-Square Reconfiguration (SMR). The performance of the system was assessed under four realistic partial shading scenarios: corner (S-1), half (S-2), tree (S-3), and chimney (S-4). Key performance indicators, including Global Peak Power (GP), Shading Loss (SL), Execution Ratio (ER), Fill Factor (FF), and Power Gain (PE), were used for assessment. The results demonstrate that the NRR and SMR configurations are capable of reliably tracking the GP across different positions on the P–V curve. These methods attain average ER of 74.76% and 74.46%, respectively, with the NRR configuration demonstrating superior overall performance—enhancing the GP by 1.26%–25.03% and FF by 2.41%–49.37%, while reducing SL by 2.47%–77.77% compared to existing reconfiguration techniques. These results highlight the superior effectiveness of the NRR scheme, confirming its robustness and efficiency in optimizing PV array performance under diverse and challenging PSCs.