Data-and physic-driven user power clustering method

Bin Qian; RenLi Cheng; Mi Zhou; Yuxiang Zhu; Fusheng Li; Jun Shi; Yong Xiao; Ao Liu; Xin Xu

doi:10.1117/12.2634909

25 April 2022 Data-and physic-driven user power clustering method

Bin Qian, RenLi Cheng, Mi Zhou, Yuxiang Zhu, Fusheng Li, Jun Shi, Yong Xiao, Ao Liu, Xin Xu

Proceedings Volume 12244, 2nd International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2022); 122444R (2022) https://doi.org/10.1117/12.2634909
Event: 2nd International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2022), 2022, Guilin, China

Abstract

This paper deeply studies the user load clustering method and user industry correlation indicators, proposes a massive power user clustering algorithm based on data-physical characteristics driven jointly. The case study in this paper proves that this method not only ensures the quality of user load clustering, but also greatly ensures the consistency of user industry categories within the class.

Citation Download Citation

Bin Qian, RenLi Cheng, Mi Zhou, Yuxiang Zhu, Fusheng Li, Jun Shi, Yong Xiao, Ao Liu, and Xin Xu "Data-and physic-driven user power clustering method", Proc. SPIE 12244, 2nd International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2022), 122444R (25 April 2022); https://doi.org/10.1117/12.2634909

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