Intelligent Diagnostics of Performance Degradation in Solar Power Plants
Description
A new software module for intelligent performance analytics and fault diagnosis for photovoltaic power plants will be developed and integrated in the existing Nispera platform. The service includes diagnosing prominent under-performance factors, allowing for a cost-effective maintenance planning.
Key Data
Projectlead
Deputy Projectlead
Dr. Gianmarco Pizza
Project team
Oliver Carmignani, Mila Francesca Lüscher, Jannik Zgraggen
Project partners
Nispera AG
Project status
completed, 09/2021 - 03/2024
Funding partner
Innovationsprojekt / Projekt Nr. 55018.1 IP-ICT
Publications
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Data scarcity in fault detection for solar tracking systems : the power of physics-informed artificial intelligence
2024 Lüscher, Mila Francesca; Zgraggen, Jannik; Guo, Yuyan; Notaristefano, Antonio; Goren Huber, Lilach
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Fully unsupervised fault detection in solar power plants using physics-informed deep learning
2023 Zgraggen, Jannik; Guo, Yuyan; Notaristefano, Antonio; Goren Huber, Lilach
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Hybride Instandhaltung : wie fliesst das Fachwissen in die KI?
2023 Goren Huber, Lilach; Palmé, Jan Thomas; Arias Chao, Manuel
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Physics informed deep learning for tracker fault detection in photovoltaic power plants
2022 Zgraggen, Jannik; Guo, Yuyan; Notaristefano, Antonio; Goren Huber, Lilach
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Predictive Maintenance mit Physics-Informed-Deep-Learning : Anwendungsfall Photovoltaikanlagen
2022 Goren Huber, Lilach; Notaristefano, Antonio
Technikumstrasse 81
8400 Winterthur