Refined analysis method for energy consumption characteristics of massive users

Lingtong Wang; Lintao Huang; Jun Zhang; Jiahao Zhou; Chenghuai Hong

doi:10.1117/12.2660371

16 December 2022 Refined analysis method for energy consumption characteristics of massive users

Lingtong Wang, Lintao Huang, Jun Zhang, Jiahao Zhou, Chenghuai Hong

Proceedings Volume 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022); 1250045 (2022) https://doi.org/10.1117/12.2660371
Event: 5th International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 2022, Chongqing, China

Abstract

The large number of random photovoltaic power generation devices in the park and the increasingly diversified energy demand of the park users have increased the difficulty of energy management in the park. It is urgent for the park to improve the park management level with more accurate energy consumption services. Based on the concept of user profiling in the Internet industry and multidimensional energy consumption analysis, the article proposes a park profiling model applicable to a high proportion of PV access. The user electricity consumption data is analyzed by double clustering algorithm to study the users' electricity consumption behavior; K-means clustering analysis is performed on the user analysis results to obtain the park portrait. The article uses 90,000 data and related electricity consumption business records of Yuhuan City Park in Zhejiang Province for arithmetic analysis to verify the validity of the model. The park portrait obtained by the algorithm proposed in the article can be used to quantitatively analyze the park-related attributes under the high proportion of PV access, and at the same time, it can be combined with the portrait results to propose the energy service about the park.

Citation Download Citation

Lingtong Wang, Lintao Huang, Jun Zhang, Jiahao Zhou, and Chenghuai Hong "Refined analysis method for energy consumption characteristics of massive users", Proc. SPIE 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 1250045 (16 December 2022); https://doi.org/10.1117/12.2660371

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