Research On Weather Data For Building Energy Efficient Based On The Space Distribution

Building is the filter of climate for indoor environment. Climate is one of the most important factors of building energy consumption. Generally, it is the greater difference between outdoor climate and indoor micro-climate the greater energy consumption of building. It is very difficult to meet the requirements of building energy efficiency with the existing weather data in China, because of the wide area coverage, rough terrain and the sparse meteorological stations. So how to get the weather date which has no meteorological station, from existing weather data to analysis building energy consumption? On this issue, the following researches are taken.Firstly, series of analytical model are established,based on the principle of climate elements of space distribution. Including: the use of separate -combination method to synthesis establish a mathematical model of spatial distribution for dry bulb temperature. According to the correlation of radiation and air temperature, the correction model is established for local topography on the temperature. According to, and a nationwide model of spatial distribution of global solar radiation is founded, with the percentage of sunshine around China. Combined with digital elevation grid data, global solar radiation model is set up to consider terrain masking conditions. The model can calculate the amount of solar radiation across the country month by month distribution.Secondly, some spatial distribution grid data are calculated month by month, according to the established models. It includes mean temperature radiation temperature, direct radiation shielding factors of topography, and global solar radiation. And the spatial distribution of temperature and global solar radiation data in the error grid analysis and data testing, using cross-validation method.Thirdly, a systemic method to generate daily and hourly weather data is given. The method includes near station weather data coordinated method and statistics-based random distribution probability method. According to this method, cloud cover, solar radiation, air temperature and air humidity are integrated to generate a "class typical meteorological year.”And the method is validated analysis by selecting the typical station weather date to test.Finally, the building thermal design climate zone map is reploted with the grid data. And it contrasted with the original climate zone map. By analyzing the heat balance formula for thermal collectors components of passive solar buildings,the index table is determined for the climate zone of passive solar building. Two passive solar building climate zone map for the Tibetan Plateau are drew, one map used the method on contour line , another map was drew with the spatial distribution grid data. Analysis showed that the spatial distribution of climate factors described in the data grid can be more truly reflect the climate factors in the distribution under the condition of the terrain features.Spatial distribution of meteorological parameters for China’s building energy efficient was studied in this thesis. The system analytical method on generating spatial distribution grid meteorological parameter data is given. And a series of grid data sets are calculated for building energy efficiency in China. It provides a new way to calculate meteorological parameters of building energy efficient. It can be referent for the calculation of building energy analysis, drawing climate zone of building energy efficient, study on regional building and legislating building energy efficient policies.