Abstract
Since a representative dataset of the climatological features of a location is important for calculations relating to many fields, such as solar energy system, agriculture, meteorology and architecture, there is a need to investigate the methodology for generating a typical meteorological year (TMY). In this paper, a hybrid method with mixed treatment of selected results from the Danish method, the Festa-Ratto method, and the modified typical meteorological year method is proposed to determine typical meteorological years for 35 locations in six different climatic zones of China (Tropical Zone, Subtropical Zone, Warm Temperate Zone, Mid Temperate Zone, Cold Temperate Zone and Tibetan Plateau Zone). Measured weather data (air dry-bulb temperature, air relative humidity, wind speed, pressure, sunshine duration and global solar radiation), which cover the period of 1994–2015, are obtained and applied in the process of forming TMY. The TMY data and typical solar radiation data are investigated and analyzed in this study. It is found that the results of the hybrid method have better performance in terms of the long-term average measured data during the year than the other investigated methods. Moreover, the Gaussian process regression (GPR) model is recommended to forecast the monthly mean solar radiation using the last 22 years (1994–2015) of measured data.
Highlights
It is known that China is the most populous country in the world, with a population of more than1.3 billion and covering an area of over 9.6 million km2
According to this method [37,38], it can be divided into six climatic types based on annual accumulated temperature, which is obtained from the summation of the daily mean temperatures over 10 ◦ C within a year, namely Tropical Zone (TZ) (>8000 ◦ C), Subtropical Zone (SZ) (4500 ◦ C–8000 ◦ C), Warm Temperate
Where i is the number of the month; RMSD1 i is the root mean square difference of index 1 for month i; SYRMSD1 is mean yearly values of RMSE of index 1; RMSD2 i and SYRMSD2 are for index 2; RMSD3 i and SYRMSD3 are for index 3; and RMSD4 i and SYRMSD4 are for index 4
Summary
It is known that China is the most populous country in the world, with a population of more than. The available years, which contain months with extremely high or extremely low dry-bulb temperature, are ruled out until only one year remains, which is chosen to be the representative month of the TRY This selection procedure may lead to an unrepresentative database, so it is not recommended for use in research of long-term performance of solar energy systems performed by the ASHRAE [17]. TMYs are composed of a mixture of the results of the Danish method, the Festa-Ratto method, and the modified typical meteorological year method for 35 representative locations in six climatic zones in China. Those months that have meteorological data closest to long-term weather observations (the value of ERMSD is smallest for each individual month) are selected to generate a TMY for a certain city
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