Next Article in Journal
The Effect of Distributed Parameters on Conducted EMI from DC-Fed Motor Drive Systems in Electric Vehicles
Next Article in Special Issue
Predictive Models for Photovoltaic Electricity Production in Hot Weather Conditions
Previous Article in Journal
A Comparison of Modulation Techniques for Modular Multilevel Converters
Article Menu
Issue 12 (December) cover image

Export Article

Open AccessArticle

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

College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Author to whom correspondence should be addressed.
Academic Editor: John Boland
Energies 2016, 9(12), 1094;
Received: 22 October 2016 / Revised: 7 December 2016 / Accepted: 17 December 2016 / Published: 21 December 2016
(This article belongs to the Special Issue Solar Forecasting)
PDF [1555 KB, uploaded 21 December 2016]


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. View Full-Text
Keywords: solar energy; solar radiation; typical meteorological year (TMY); climatic zones solar energy; solar radiation; typical meteorological year (TMY); climatic zones

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Zang, H.; Wang, M.; Huang, J.; Wei, Z.; Sun, G. A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China. Energies 2016, 9, 1094.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top