Adaptive Dual‐IGBT Architecture With Wireless Control for Rapid I–V Characterization and Fault Detection in Utility‐Scale PV Strings

Effective performance evaluation and fault detection in PV strings rely heavily on current–voltage (I–V) curve analysis. Yet, most commercial tracers are prohibitively expensive, interrupt system operation during testing and lack the capability for real‐time monitoring in high‐voltage, high‐power environments. To overcome these challenges, this study presents a low‐cost, real‐time, and wireless solution—an Online I–V Tracing Tool (OIVTT)—engineered for high‐voltage photovoltaic strings deployed in utility‐scale solar power systems. The OIVTT employs a dual‐branch Insulated Gate Bipolar Transistor (IGBT)–based electronic load driven by an STM32 microcontroller, enabling dynamic I–V curve tracing with precise control across the full operating range. The system is capable of tracing I–V curves for PV strings up to 1500‐V open‐circuit voltage and 20‐A short‐circuit current and performs complete curve acquisition under one second, ensuring compliance with the IEC 60904 standard for solar measurements under stable irradiance and temperature conditions. A wireless communication framework, developed using the Kodular mobile application platform, allows remote initiation and control of measurements, with real‐time data synchronized to the Firebase cloud. For enhanced sampling accuracy, the system employs an adaptive dual‐branch control algorithm that continuously modifies sweep parameters in response to the I–V curve’s gradient, thereby ensuring balanced placement of data points across its steep and flat regions. The algorithm maintains a relative standard deviation (RSD) below 10%, indicating high consistency and precision of data acquisition. The system was experimentally validated using a 15‐module monocrystalline PV string with a total capacity of 3.6 kW, tested under diverse scenarios such as consistent sunlight exposure, induced partial shading, and deliberate modifications to series and shunt resistances. The OIVTT successfully captured performance anomalies and matched theoretical expectations, demonstrating an average deviation of less than 2% when compared with the standard Shockley diode‐based PV model. Under partial shading, the system accurately detected bypass activation events and the presence of stepped I–V profiles, while tests on altered series/shunt resistance confirmed sensitivity to fill factor degradation. In comparison with commercial I–V tracers—which typically require offline testing, exhibit longer sweep durations (2–9 s), and cost ₹12L–₹20L—the proposed OIVTT provides a high‐speed, accurate, and economically viable solution (< ₹35k total cost). Its nonintrusive operation, wireless control, and high‐voltage support make it ideal for continuous monitoring, preventive diagnostics, and maintenance in utility‐scale PV systems.