Keywords

Meteorological database, NASA, NSRDB, Photovoltaics

Presentation Type

Poster

Research Abstract

Solar energy is one of the top runners among the renewable energy. The design and deployment of solar panels are geographic- and climate-specific to optimize the total energy yield. However, the existing meteorological databases are not accessible to users for direct download and visualization. Hence, we have developed a tool that allows users to download and visualize a variety of global meteorological databases, for instance, the National Solar Radiation Database (NSRDB). Enabled by our tool, both historical and Typical Meteorological Year (TMY) data, such as solar irradiance and ambient temperature, across the entire world in specific time intervals (e.g., hourly versus monthly) are available to the users. In this paper, we have also benchmarked meteorological data from different sources, e.g., satellite-derived versus local station, which coincide with each other. In conclusion, our tool can facilitate the design and optimization of large-scale solar farms globally, by making comprehensive meteorological databases more accessible to photovoltaic installers.

Session Track

Energy

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Aug 3rd, 12:00 AM

Bifacial Solar Panel Database InterfacePUMET: A tool for global meteorological data mining for performance and reliability prediction of large scale solar farms

Solar energy is one of the top runners among the renewable energy. The design and deployment of solar panels are geographic- and climate-specific to optimize the total energy yield. However, the existing meteorological databases are not accessible to users for direct download and visualization. Hence, we have developed a tool that allows users to download and visualize a variety of global meteorological databases, for instance, the National Solar Radiation Database (NSRDB). Enabled by our tool, both historical and Typical Meteorological Year (TMY) data, such as solar irradiance and ambient temperature, across the entire world in specific time intervals (e.g., hourly versus monthly) are available to the users. In this paper, we have also benchmarked meteorological data from different sources, e.g., satellite-derived versus local station, which coincide with each other. In conclusion, our tool can facilitate the design and optimization of large-scale solar farms globally, by making comprehensive meteorological databases more accessible to photovoltaic installers.