Publications

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Methodology to predict annual yield losses and gains caused by solar module design and materials under field exposure

Methodology to predict annual yield losses and gains caused by solar module design and materials under field exposure

• Optimizing module design for a maximum annual performance. • Detailed gain and loss analysis from cell under STC to module in real environment. • Understanding the impact of module material on the annual module yield. • Impact of angular light, temperatures, lower irradiances on module performance. • Impact of weather condition (ambient temperature, wind speed) on module performance.

Methodology for Generating High Time Resolution Typical Meteorological Year Data for Accurate Photovoltaic Energy Yield Modelling

Methodology for Generating High Time Resolution Typical Meteorological Year Data for Accurate Photovoltaic Energy Yield Modelling

Accurate energy yield prediction is of utmost importance for commercial scale photovoltaic systems. One key parameter crucial to the prediction accuracy is the quality of solar radiation data. Most energy yield prediction models rely on Typical Meteorological Year data with maximum temporal resolution of one hour. In this work we develop a methodology to generate Typical Meteorological Year data with much higher time resolution using gap filling methods that aim to maintain high-quality solar radiation data for photovoltaic yield modelling.

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