Sequential correction method for load resources data based on the minimum enclosing ball clustering

Yunlong Bai; Jun Ji; Jun Xie; Guisheng Chen; Xiaoming Wang; Chunping Zhang

doi:10.1117/12.3037796

27 September 2024 Sequential correction method for load resources data based on the minimum enclosing ball clustering

Yunlong Bai, Jun Ji, Jun Xie, Guisheng Chen, Xiaoming Wang, Chunping Zhang

Author Affiliations +

Proceedings Volume 13275, Sixth International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2024); 132751X (2024) https://doi.org/10.1117/12.3037796
Event: 6th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2024), 2024, Wuhan, China

Abstract

Electricity load data is typically analyzed on a temporal scale, which can vary with seasons or different times of the day. When examined on a spatial scale, electricity load data display distinct regional characteristics. Therefore, ensuring accurate data correction under time-series conditions is paramount. In this paper, we present a sequential correction method for load resource data based on minimum enclosing ball clustering. This method is structured into four phases. In the initial phase, data feature extraction is conducted using load similarity based on a dynamic time planning algorithm to identify the data for processing. Subsequently, the Singular Value Decomposition (SVD) dimensionality reduction algorithm is applied in the second phase to decrease the dimensionality of the data for the subsequent steps. The third phase involves utilizing the minimum enclosing ball clustering technique to cluster and analyze the data obtained from the previous step. Finally, in the fourth phase, the uncorrected values are adjusted.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yunlong Bai, Jun Ji, Jun Xie, Guisheng Chen, Xiaoming Wang, and Chunping Zhang "Sequential correction method for load resources data based on the minimum enclosing ball clustering", Proc. SPIE 13275, Sixth International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2024), 132751X (27 September 2024); https://doi.org/10.1117/12.3037796

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KEYWORDS

Feature extraction

Data processing

Singular value decomposition

Matrices

Data corrections

Decision making

Power supplies

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