Author(s)

Bo Gao ¹, Jiawei Pan ², Xuwen Liu ¹, Changyu Qian ², Linjie Wang ¹

Affiliation(s)

¹ Jiangsu Power Exchange Center Co., Ltd., No. 62, Yunnan Road, Gulou District, Nanjing, China
² School of Electrical Engineering, Southeast University, No. 2, Sipailou, Xuanwu District, Nanjing, China

Corresponding Author

Changyu Qian

ABSTRACT

In order to detect the abnormal behavior of unit quotation in power market, an outlier detection method based on characteristic index is proposed. According to the characteristics of abnormal behavior of unit quotation, the corresponding characteristic indexes are extracted, and the dimension is reduced by principal component analysis method. The local outlier factor algorithm is used to detect outliers, and the evaluation indexes are compared when different number of features are extracted. The experimental results show that the proposed method can detect abnormal quotation units to a certain extent, and the evaluation index is improved with the number of features extracted.

KEYWORDS

Outlier detection, Feature extraction, Principal component analysis, Local outlier factor

CITE THIS PAPER

Bo Gao, Jiawei Pan, Xuwen Liu, Changyu Qian, Linjie Wang, Outlier Detection of Power Supplier Quotation Based on Characteristic Index. Industrial Engineering and Innovation Management (2022) Vol. 5: 34-43. DOI: http://dx.doi.org/10.23977/ieim.2022.051205.

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