Abstract
The method of classification in meteorological parameters is adopted to optimize the operation mode of water source heat pump-assisted solar water heating system under different meteorological parameters in winter of northern region. We select solar radiation as the first-level indictor; the daily solar radiation is divided into four periods as four secondary indictors of solar radiation. The 60-day weather data of winter in Shenyang are in clustering analysis by using clustering method. The results are confirmed by Bayesian discriminant analysis. Furthermore, the operation mode is analyzed on the platform of TRNSYS under the selected typical day of each group. The 60 meteorological days are divided into seven groups based on the results of cluster meteorological analysis. The distribution law of the hourly solar radiation is similar among each group. Consistent rate of discriminant and clustering analysis results is higher than 96.6%. In addition, the optimal heat pump operating time of each group is determined by the minimum energy consumption which is treated as the optimization objective.
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