A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China
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)...
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MDPI AG
2016-12-01
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| Series: | Energies |
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| Online Access: | http://www.mdpi.com/1996-1073/9/12/1094 |
| _version_ | 1798039034374651904 |
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| author | Haixiang Zang Miaomiao Wang Jing Huang Zhinong Wei Guoqiang Sun |
| author_facet | Haixiang Zang Miaomiao Wang Jing Huang Zhinong Wei Guoqiang Sun |
| author_sort | Haixiang Zang |
| collection | DOAJ |
| description | 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. |
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| format | Article |
| id | doaj.art-31bb3d1aa0e84c8a8f6b40d222dc6789 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T21:48:21Z |
| publishDate | 2016-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-31bb3d1aa0e84c8a8f6b40d222dc67892022-12-22T04:01:19ZengMDPI AGEnergies1996-10732016-12-01912109410.3390/en9121094en9121094A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of ChinaHaixiang Zang0Miaomiao Wang1Jing Huang2Zhinong Wei3Guoqiang Sun4College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, ChinaCollege of Energy and Electrical Engineering, Hohai University, Nanjing 211100, ChinaCollege of Energy and Electrical Engineering, Hohai University, Nanjing 211100, ChinaCollege of Energy and Electrical Engineering, Hohai University, Nanjing 211100, ChinaCollege of Energy and Electrical Engineering, Hohai University, Nanjing 211100, ChinaSince 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.http://www.mdpi.com/1996-1073/9/12/1094solar energysolar radiationtypical meteorological year (TMY)climatic zones |
| spellingShingle | Haixiang Zang Miaomiao Wang Jing Huang Zhinong Wei Guoqiang Sun A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China Energies solar energy solar radiation typical meteorological year (TMY) climatic zones |
| title | A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China |
| title_full | A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China |
| title_fullStr | A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China |
| title_full_unstemmed | A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China |
| title_short | A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China |
| title_sort | hybrid method for generation of typical meteorological years for different climates of china |
| topic | solar energy solar radiation typical meteorological year (TMY) climatic zones |
| url | http://www.mdpi.com/1996-1073/9/12/1094 |
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