Research on Thermal Fault Detection and Location of Photovoltaic Connectors Based on Multiple Model Estimator

Abstract

Offshore photovoltaic (PV) systems encounter challenges due to high humidity and salt spray environments. The PV connectors on the DC input side of inverters are particularly susceptible to increased contact resistance and local overheating caused by environmental corrosion. This paper introduces a novel thermal fault location method utilizing a multiple model estimator (MME). The approach develops a lumped thermal model and an abnormal overheating disturbance model for the PV connectors. By combining a Kalman filter with a probability fusion algorithm, the method effectively detects thermal faults. Simulation and experimental results demonstrate that this approach can accurately locate faults while requiring only a minimal number of thermal sensors, thereby enhancing the reliability of offshore PV systems.

Keywords

Photovoltaic (PV) connectors / Thermal fault location / Multiple model estimator (MME) / Kalman filter / Probability fusion algorithm

Acknowledgments

We extend our sincere gratitude to all members of Tianjin Key Laboratory of New Energy Power Conversion, Transmission and Intelligent Control for their support of this research.

Author Contributions

Conceptualization, C.W. and L.Z.; Methodology, L.Z.; Software, L.Z.; Validation, C.W., L.Z. and P.C.; Formal Analysis, L.Z.; Investigation, L.Z.; Resources, C.W. and P.C.; Data Curation, L.Z.; Writing—Original Draft Preparation, C.W. and L.Z.; Writing—Review & Editing, C.W., L.Z. and Q.X.; Visualization, C.W. and L.Z.; Supervision, C.W. and P.C.; Project Administration, C.W., L.Z., P.C. and Q.X.; Funding Acquisition, C.W. and P.C.

Ethics Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The statement is required for all original articles which informs readers about the accessibility of research data linked to a paper and outlines the terms under which the data can be obtained.

Funding

This paper was partially supported by the National Key R&D Program of China (No. 2022YFB4200703).

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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