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Risk identification method of electricity charge recovery for special transformer users based on Stacking model fusion
  • Xixiang Zhang,
  • Qi Meng,
  • Jun Yang
Xixiang Zhang
China Southern Power Grid Guangxi Power Grid Co Ltd
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Qi Meng
广西电网有限责任公司

Corresponding Author:[email protected]

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Jun Yang
China Southern Power Grid Guangxi Power Grid Co Ltd
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Abstract

In view of the current risks faced by electric power companies in the recovery of special transformer users’ electricity bills, a special transformer users’ electricity bill recovery based on Stacking model fusion is proposed Collect risk identification methods. Carry out feature processing, feature construction and feature screening for special transformer user data, and optimize the model from sample distribution and feature attributesThe generalization performance of; The Stacking model is used to fuse multiple base learners to build a risk identification model for electricity fee recovery of special transformer users. The experimental results show that the phaseCompared with other commonly used classification algorithms, the proposed method has better accuracy, recall, P-R harmonic mean, AUC value and model generalization performance,The recognition rate of users with special transformer risk is also higher.