Impact of Soiling on Si and CdTe PV Modules: Case Study in Different Brazil Climate Zones

Shading is one of the most critical factors that produces a reduction in power in photovoltaic (PV) modules. The main causes of shading are related to cloud cover; local specificity; natural characteristics; building and other civil works; and the presence of the PV system itself. A reduction in overall radiation produces a consequent reduction in electric power. Another more problematic effect is associated with the partial shading of the PV modules. The shaded cell behaves as a load, dissipating energy and increasing its temperature. This effect can involve irreversible changes to the PV module, with a decrease in performance that can even cause the destruction of the shaded cell.The main aim of this work is the development of a testing procedure for the performance evaluation of commercial PV modules in the presence of partial shading on one cell. Tests were carried out using thermographic and electric measurements and by varying the shading levels according to IEC standards. Shading up to total darkening is achieved by means of a number of filters that reduce the direct solar irradiance.As a case study, a complete characterisation of a 180 Wp polycrystalline PV module was performed according to the proposed testing procedure, showing that high temperatures can be measured on the shaded PV module surface even if only 50 % of the surface of one cell of the PV module is darkened.

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Remote sensing of urban thermal environments within local climate zones: A case study of two high-density subtropical Chinese cities

Urban Climate ◽

10.1016/j.uclim.2019.100568 ◽

2020 ◽

Vol 31 ◽

pp. 100568

Author(s):

Xiaoliang Chen ◽

Yong Xu ◽

Jinxin Yang ◽

Zhifeng Wu ◽

Hong Zhu

Keyword(s):

Remote Sensing ◽

High Density ◽

Climate Zones ◽

Chinese Cities ◽

Local Climate ◽

Thermal Environments ◽

Local Climate Zones

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Transitional Climate Zones and Biome Boundaries: A Case Study from China

Ecological Studies - Landscape Boundaries ◽

10.1007/978-1-4612-2804-2_20 ◽

1992 ◽

pp. 394-402 ◽

Cited By ~ 10

Author(s):

Congbin Fu

Keyword(s):

Climate Zones

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Mapping the local climate zones of urban areas by GIS-based and WUDAPT methods: A case study of Hong Kong

Urban Climate ◽

10.1016/j.uclim.2017.10.001 ◽

2018 ◽

Vol 24 ◽

pp. 567-576 ◽

Cited By ~ 36

Author(s):

Ran Wang ◽

Chao Ren ◽

Yong Xu ◽

Kevin Ka-Lun Lau ◽

Yuan Shi

Keyword(s):

Hong Kong ◽

Urban Areas ◽

Climate Zones ◽

Local Climate ◽

Local Climate Zones

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PV modules and their backsheets - A case study of a Multi-MW PV power station

Solar Energy Materials and Solar Cells ◽

10.1016/j.solmat.2021.111295 ◽

2021 ◽

Vol 231 ◽

pp. 111295

Author(s):

Claudia Buerhop-Lutz ◽

Oleksandr Stroyuk ◽

Tobias Pickel ◽

Thilo Winkler ◽

Jens Hauch ◽

...

Keyword(s):

Power Station ◽

Pv Modules

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Issues with using Landsat based Surface Temperature for Investigating Linkage between Local Climate Zones and Surface Urban Heat Island in Different Seasons: A Case Study of Manhattan, N.Y.

10.31219/osf.io/m84ne ◽

2019 ◽

Author(s):

Parth Bansal

Keyword(s):

Surface Temperature ◽

Urban Heat Island ◽

Summer Season ◽

Heat Island ◽

Climate Zones ◽

Local Climate ◽

Local Climate Zones ◽

Different Seasons ◽

Urban Heat

This study was conceptualized to investigate differences in surface temperature profile of Local Climate Zones (LCZ) classes in different seasonal conditions. Manhattan was selected as case study due to its dense, but heterogeneous built-up profile and presence of green area which formed the baseline for temperature comparison. However, this study failed to find significant results, in terms of the distinct Urban Heat Island (UHI) feature often reported in literature. Instead, this study suggests that in the case of Manhattan UHI is predominantly within ± 0.5 C° except during summer season. In summer season, where more difference in built and green LCZ is observed, the noise in data, defined by standard deviation of surface temperature in the class, is also higher. Thus, our study concludes that Landsat based surface temperature should be used with extreme caution to investigate UHI since most imagery is taken during day time.

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