Victoria Lofstad-Lie

• Lofstad-Lie, Victoria; Marstein, Erik Stensrud; Simonsen, Aleksander & Skauli, Torbjørn (2022). Cost-Effective Flight Strategy for Aerial Thermography Inspection of Photovoltaic Power Plants. IEEE Journal of Photovoltaics. ISSN 2156-3381. 12(6), p. 1543–1549. doi: 10.1109/JPHOTOV.2022.3202072. Full text in Research Archive Show summary

  Thermography from unmanned aerial vehicles (UAV) is widely used for module condition surveys and defect detection in solar (photovoltaic) power plants. This article presents an optimized defect inspection procedure in which a two-stage autonomous flight strategy is adopted to reduce the operation time, and thereby the cost. The first stage is a fast high-altitude flight for rapid coverage of the entire plant. The resolution on the modules is then somewhat degraded, but adequate for detection of possible defect locations. In the second stage, an optimized flight path is calculated to revisit and image only the detected locations from a lower altitude, where the resolution is sufficient for the classification of defects. This concept is studied through simulations of different plant geometries and defect densities. The simulations are supported by actual data, including a plant-scale survey. The proposed strategy is shown to have the potential for significant savings in operation time, on the order of 60% in the experimental case with 2% module defects. Commonly reported defect densities of 0.5% to 1% will give even larger savings. The inspection strategy is shown to be especially beneficial for plant geometries representative of high latitudes.

• Lofstad-Lie, Victoria; Marstein, Erik Stensrud; Simonsen, Aleksander & Skauli, Torbjørn (2021). Cost-effective flight strategy for aerial thermography inspection of photovoltaic power plants. In Angus, Rockett (Eds.), 2021 IEEE 48th Photovoltaic Specialists Conference (PVSC). IEEE conference proceedings. ISSN 978-1-6654-1922-2. p. 0023–0025. doi: 10.1109/PVSC43889.2021.9518710. Show summary

  Thermography from an unmanned aerial vehicle (UAV) offers efficient fault inspection in solar parks. This paper presents an optimized fault detection procedure, including a two-stage autonomous flight strategy. The first stage images the entire park quickly at low resolution, flying fast at high altitude to detect possible faults. In the second stage, the detections are imaged at higher resolution, by flying an optimized path at lower altitude, for fault classification. Based on actual data, including a park-scale survey, this strategy is shown to have potential for significant savings in operation time, on the order of 70% or more, at realistic fault densities.

• Spicher, Andres; Clausen, Lasse Boy Novock; Miloch, Wojciech Jacek; Lofstad, Victoria; Jin, Yaqi & Moen, Jøran Idar (2017). Interhemispheric study of polar cap patch occurrence based on Swarm in situ data. Journal of Geophysical Research (JGR): Space Physics. ISSN 2169-9380. doi: 10.1002/2016JA023750. Full text in Research Archive

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• Lofstad-Lie, Victoria Emilie; Marstein, Erik Stensrud; Simonsen, Aleksander & Skauli, Torbjørn (2021). Cost-Effective Flight Strategy for Aerial Thermography Inspection of Photovoltaic Power Plants.
• Lofstad, Victoria Emilie; Solend, Tor Atle; Øgaard, Mari Benedikte & Aarseth, Bjørn Lupton (2019). Thermal imaging from drones for automatic fault detection in photovoltaic systems.
• Spicher, Andres; Clausen, Lasse Boy Novock; Miloch, Wojciech Jacek; Jin, Yaqi; Lofstad, Victoria Emilie & Moen, Jøran Idar (2018). Polar cap patch climatology based on Swarm density data.

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