Temperature Interpolation Method of Distributed Photovoltaic Power Station Group Based on Multisource Data Fusion

In order to improve the coverage and accuracy of the temperature data of distributed photovoltaic (PV) station group, this paper proposes a temperature interpolation method of distributed PV power station group based on multi-source data fusion. Firstly, the applicability and accuracy of four spatial interpolation methods were studied by using high-precision temperature data from meteorological stations. The results showed that the Co-Kriging (CK) method has the highest interpolation accuracy, which was used to construct a base temperature distribution map. Secondly, the base distribution map was utilized to perform weighted average correction on the temperature data of low-precision PV power stations. Finally, the CK method was used to construct a more accurate temperature distribution map based on the temperature data of meteorological stations and the corrected temperature data of PV power stations. Taking Jiangsu province as the research area, the experimental results showed that the interpolation accuracy of the proposed method is significantly higher than that of the base distribution map.