Fault Diagnosis and Quantification for Photovoltaic Arrays based on Differentiable Physical Models
This work addresses the need for efficient and interpretable fault quantification in photovoltaic systems, offering a novel approach that could enhance reliability and maintenance, though it is incremental in applying differentiable physical models to this specific domain.
The paper tackled the problem of fault diagnosis and quantification in photovoltaic arrays by proposing a differentiable fast fault simulation model and a gradient-based fault parameters identification method, achieving high quantification accuracy with I-V reconstruction errors below 3% across various faults.
Accurate fault diagnosis and quantification are essential for the reliable operation and intelligent maintenance of photovoltaic (PV) arrays. However, existing fault quantification methods often suffer from limited efficiency and interpretability. To address these challenges, this paper proposes a novel fault quantification approach for PV strings based on a differentiable fast fault simulation model (DFFSM). The proposed DFFSM accurately models I-V characteristics under multiple faults and provides analytical gradients with respect to fault parameters. Leveraging this property, a gradient-based fault parameters identification (GFPI) method using the Adahessian optimizer is developed to efficiently quantify partial shading, short-circuit, and series-resistance degradation. Experimental results on both simulated and measured I-V curves demonstrate that the proposed GFPI achieves high quantification accuracy across different faults, with the I-V reconstruction error below 3%, confirming the feasibility and effectiveness of the application of differentiable physical simulators for PV system fault diagnosis.