Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Impact of different weather data sets on photovoltaic system performance evaluation
Building energy simulation plays an important role in decision makings involving energy conservation measures and choices of renewable energy systems in building designs. Traditional simulation tools rely on weather data sets called Typical Meteorological Year (TMY), representing a typical year of weather at ground weather stations throughout the United States. These data sets are constructed using an algorithm to select the “most typical” month of the many years in the database for each month. Some recent publications suggest that one-year TMY data is no longer sufficient to evaluate long-term performance of PV systems, because a typical year does not taken into account extreme weather, and thus does not address the meteorological uncertainty that might occur. Actual electricity outputs from photovoltaic systems vary from year to year. Having more accurate information about production performance should help facilitate system selections that match building designs and how to operate them. In this study, four sets of weather data, Detroit TMY2, Ann Arbor TMY3, Ann Arbor 15-year NSRDB, and Ann Arbor 13-year SolarAnywhere®, are used as inputs in PV system performance simulation. Their impacts on the PV system electricity output availability, variability and uncertainty are analyzed and compared. The magnitude and consequences of the analyses of different weather data sets are presented.
Impact of different weather data sets on photovoltaic system performance evaluation
Building energy simulation plays an important role in decision makings involving energy conservation measures and choices of renewable energy systems in building designs. Traditional simulation tools rely on weather data sets called Typical Meteorological Year (TMY), representing a typical year of weather at ground weather stations throughout the United States. These data sets are constructed using an algorithm to select the “most typical” month of the many years in the database for each month. Some recent publications suggest that one-year TMY data is no longer sufficient to evaluate long-term performance of PV systems, because a typical year does not taken into account extreme weather, and thus does not address the meteorological uncertainty that might occur. Actual electricity outputs from photovoltaic systems vary from year to year. Having more accurate information about production performance should help facilitate system selections that match building designs and how to operate them. In this study, four sets of weather data, Detroit TMY2, Ann Arbor TMY3, Ann Arbor 15-year NSRDB, and Ann Arbor 13-year SolarAnywhere®, are used as inputs in PV system performance simulation. Their impacts on the PV system electricity output availability, variability and uncertainty are analyzed and compared. The magnitude and consequences of the analyses of different weather data sets are presented.
Impact of different weather data sets on photovoltaic system performance evaluation
Yimprayoon, Chanikarn (Autor:in) / Navvab, Mojtaba (Autor:in)
01.08.2014
ARCC Conference Repository; 2011: Reflecting upon Current Themes in Architectural Research | Lawrence Tech
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC:
690
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