Quantitative Shade Detection for PV Systems Based on Clearsky Data

In modern monitoring applications, losses from shading should be quantitatively separated from other loss mechanisms such as soiling, degradation or total failures. Based on clearsky reference data, we introduce a shading matrix which enables accurate hourly description of shading losses of PV strings over the year. This matrix can be used to improve failure detections and reference yield data in PV systems. Furthermore, a shading matrix with respect to sun position is introduced to improve the spatial understanding of shading caused by surrounding objects.

Publication Details

Journal
EU PVSEC
Published
2024-11-14
DOI
https://doi.org/10.4229/eupvsec2024/4bv.3.29
Citations
1
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.10
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article

Quantitative Shade Detection for PV Systems Based on Clearsky Data

1 citations
EU PVSEC
Photovoltaic System Optimization Techniques
0.10
article

Quantitative Shade Detection for PV Systems Based on Clearsky Data

article en
1 citations

Abstract

In modern monitoring applications, losses from shading should be quantitatively separated from other loss mechanisms such as soiling, degradation or total failures. Based on clearsky reference data, we introduce a shading matrix which enables accurate hourly description of shading losses of PV strings over the year. This matrix can be used to improve failure detections and reference yield data in PV systems. Furthermore, a shading matrix with respect to sun position is introduced to improve the spatial understanding of shading caused by surrounding objects.

EU PVSEC
Life in Land
Openalex Percentile: Top 62%
Photovoltaic System Optimization Techniques
0.10
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Quantitative Shade Detection for PV Systems Based on Clearsky Data · EU PVSEC (2024) | TGRS Research Map | TGRS