PRINCIPAL COMPONENT AND CLUSTER ANALYSIS OF PHOTOVOLTAIC CLIMATE IN HEILONGJIANG PROVINCE

Wang Zhiwen; Yang Dazhi; Liu Bai; Qiu Haizhi; Shao Zhuhang

doi:10.19912/j.0254-0096.tynxb.2025-0334

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Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (7) : 564-570. DOI: 10.19912/j.0254-0096.tynxb.2025-0334

PRINCIPAL COMPONENT AND CLUSTER ANALYSIS OF PHOTOVOLTAIC CLIMATE IN HEILONGJIANG PROVINCE

Wang Zhiwen¹, Yang Dazhi¹, Liu Bai¹, Qiu Haizhi², Shao Zhuhang²

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Abstract

This study proposes a PV resource rating method based on principal component analysis （PCA） and clustering algorithms. The methodology involves acquiring solar irradiance and auxiliary meteorological variables for Heilongjiang Province from 2016 to 2020, derived from Himawari-8 satellite data with a spatial resolution of 4 km. Subsequently, nine temporal features are extracted for the five variables using time series analysis, and PCA is applied to reduce the dimensionality of the extracted features. Finally, a spatial distribution map of the PV climate at a power plant scale for Heilongjiang Province is generated through clustering analysis. This map categorizes the total solar resource of Heilongjiang Province into three levels： general, relatively abundant, and very abundant, providing significant scientific support for subsequent refined PV resource assessments.

Key words

photovoltaic / principal component analysis / clustering algorithms / resource assessment / Heilongjiang province / solar energy

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Wang Zhiwen, Yang Dazhi, Liu Bai, Qiu Haizhi, Shao Zhuhang. PRINCIPAL COMPONENT AND CLUSTER ANALYSIS OF PHOTOVOLTAIC CLIMATE IN HEILONGJIANG PROVINCE[J]. Acta Energiae Solaris Sinica. 2026, 47(7): 564-570 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0334

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