String outages in photovoltaic plants

Abstract

In this work, the factors leading to string outages are examined, and an enhanced method for detecting faults at the substring

level is presented. Utilizing GPT4-o to analyze O&M reports of 5089 photovoltaic plants, we classified outages

according to the affected components and the underlying origin, identifying the most frequent string fault causes. An

approach employing CUSUM Charts is introduced to identify substring outages within PV systems effectively. The methodology

utilizes fundamental field data that is commonly available in practice. A filtering approach, combined with the use

of CUSUM control charts, minimizes false positives, ensuring that only consistent underperformance is flagged as an outage.

The methodology returns far fewer false positives and more stable error intervals for substring outages than a former

monitoring approach. Overall, the study demonstrates a significant improvement in detecting substring outages. The

advanced methodology enables more effective O&M for PV plants, where substring outages are reliably identified after a

short detection time.

Titel	String outages in photovoltaic plants
Medien	Renewable Energies and Smart Technologies (REST)
Verlag	SAGE
Heft	1
Band	2025 Vol. 3
Verfasser	Maximilian Schönau, Markus Panhuysen, Jonas Sonntag, Holger Banse, Günter Seel, Joseph Jachmann, Achim Schulze, Bernd Hüttl, Prof. Dr. Dieter Landes
Veröffentlichungsdatum	18.06.2025
Projekttitel	Kick-PV
Zitation	Schönau, Maximilian; Panhuysen, Markus; Sonntag, Jonas; Banse, Holger; Seel, Günter; Jachmann, Joseph; Schulze, Achim; Hüttl, Bernd; Landes, Dieter (2025): String outages in photovoltaic plants. Renewable Energies and Smart Technologies (REST) 2025 Vol. 3 (1).