A new TMY generation method based on the entropy-based TOPSIS theory for different climatic zones in China

Abstract Typical meteorological years (TMY) serve as basic parameters for building energy consumption simulation and play a key role in building energy-saving design. At present, the most widely used method for generating TMY is the Finkelstein–Schafer statistical method of Sandia Laboratory in the United States. However, when this method is used to generate TMY, all meteorological parameters use a uniform weighting factor which fails to reflect the different regional climate impact differences. It is unreasonable to adopt a unified weighting factor, because the meteorological resources of different climate zones are very different, and the leading role of building energy consumption is different. This paper proposes a new method, applying the entropy-based Technique for Order Preference by Similarity to Ideal Solution(TOPSIS) method for TMY generation. The entropy-based TOPSIS method is an objective method, in which the determination of weight and decision result does not involve any subjective preference but totally relies on the objective data set. This method can reflect the climate differences in different climate zones. The rationality of this method is verified by selecting five typical representative cities in China. The single meteorological parameter deviation analysis and building energy consumption simulation were used to evaluate the generated TMY. The results show that the TMY generated by the entropy-based TOPSIS method is closer to the long-term average. This method only considers monthly data, so the development of entropy-based TOPSIS is simpler and less time-consuming.