Data mining method for energy consuming behavior of integrated energy system considering typical factors

Qingsong Hua; Qiang Li; Shengyu Gao; Di Liu; Hong Zhu; Dongxu Zhou; Qilin Shuai

doi:10.1117/12.2635831

6 May 2022 Data mining method for energy consuming behavior of integrated energy system considering typical factors

Qingsong Hua, Qiang Li, Shengyu Gao, Di Liu, Hong Zhu, Dongxu Zhou, Qilin Shuai

Proceedings Volume 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022); 122561S (2022) https://doi.org/10.1117/12.2635831
Event: 2022 International Conference on Electronic Information Engineering, Big Data and Computer Technology, 2022, Sanya, China

Abstract

Traditional mining methods are easily influenced by typical factors such as nature, so the precision of data mining is not ideal. This paper presents a data mining method for energy consumption behavior of integrated energy system considering typical factors. The K-means algorithm is used to correct the damaged data and to mine and marginalize the partially disturbed data in the data. Therefore, the standardized processing method is used to quantify the data. After filtering, the characteristics of user's electricity consumption behavior can be accurately extracted. Experimental results show that the proposed method can effectively extract the accurate electricity consumption data, and the accuracy is higher than the traditional method.

Citation Download Citation

Qingsong Hua, Qiang Li, Shengyu Gao, Di Liu, Hong Zhu, Dongxu Zhou, and Qilin Shuai "Data mining method for energy consuming behavior of integrated energy system considering typical factors", Proc. SPIE 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022), 122561S (6 May 2022); https://doi.org/10.1117/12.2635831

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