Abstract
In order to assess the efficiency of buildings or renewable energy systems, simulation software needs relevant meteorological files. These weather data are generated thanks to statistical methods. Actually, these methods are derived to treat high quality hourly databases or monthly average of the weather parameters. When only inconsistent hourly database is available for a site, the meteorological file used for the energy simulations must be generated from the monthly averages. This paper deals with a new weather data generation tool, Runeole, that is capable of generating a set of Typical Meteorological Year (TMY) data directly from inconsistent hourly databases. This C++ software is based on typical weather sequence analysis. It deals with the analysis and the generation process of stochastic continuous multivariable phenomena with frequency properties applied to a climatic database. The method is able to reproduce the time dependencies and the cross-correlations between different weather parameters. To do so, five weather parameters at least must be taken into account: air temperature, humidity, global solar radiation, wind speed and wind direction. This paper introduces the methodology used and the analysis of the results given by the meteorological databases from different worldwide climates.
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