Fault Diagnosis and Quantification for Photovoltaic Arrays based on Differentiable Physical Models

TL;DR

This paper introduces a differentiable physical model for PV arrays that enables accurate, efficient fault diagnosis and quantification, improving interpretability and performance over existing methods.

Contribution

It presents a novel differentiable fault simulation model and a gradient-based identification method for PV array faults, enhancing accuracy and efficiency.

Findings

I-V reconstruction error below 3%

High quantification accuracy for various faults

Effective fault diagnosis using differentiable physical models

Abstract

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.