A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China

Abstract

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 of measured data.

Comparison of Solar Radiation Models to Estimate Direct Normal Irradiance for Korea

“…The data pair that misses either GHI or DNI and was measured when the zenith angle of the sun was larger than 85 • were excluded. The number of the remained pairs of GHI and DNI measurements totals 11,928. Solar radiation models to estimate DNI can be classified into two categories, parametric and decomposition models [5].…”

Research on the Influence of Abrupt Climate Changes on the Analysis of Typical Meteorological Year in China

“…So far, there are 824 meteorology observation stations in China which can constantly take meteorological records, and a database of the TMYs for 270 cities across mainland China. (2) Due to the consensus of the methods to determine a TMY, more research focus on processing and screening the original meteorology databases and improving the accuracy of the data due to the lack of historical and continuous meteorology records [15][16][17][18]. For instance, some research [13,14] worked out the TMY with the meteorological data captured only four times a day, and the predicted solar radiation data with the DFMs (Diffuse fraction models for the hourly solar radiation) [19].…”