易姝慧,刘俊杰,方田,黄颖祺,温和.基于互信息和Catboost的空调负荷辨识特征选择及辨识方法[J].电测与仪表,2026,63(6):159-169. Yi Shuhui,Liu Junjie,Fang Tian,Huang Yingqi,WEN He.Feature selection and load identification method for air conditioning load recognition based on mutual information and Catboost[J].Electrical Measurement & Instrumentation,2026,63(6):159-169.
基于互信息和Catboost的空调负荷辨识特征选择及辨识方法
Feature selection and load identification method for air conditioning load recognition based on mutual information and Catboost
Air conditioning load identification is an important basis for the participation of massive air conditioning loads on the user side in demand response regulation. Due to the variety of air-conditioning load types and the complexity and variability of operation modes, it is difficult for the existing means to effectively screen out the features that are relatively typical for air-conditioning load identification, which in turn affects the accuracy of identification. On this basis, this paper presents an interpretable model for air conditioning load identification, leveraging mutual information and CatBoost. It explores a method for selecting electrical characteristic indices of air conditioning loads, investigates the correlation between these indices and equipment labels, and uses Shapley additive explanations (SHAP) to assess the impact of electrical characteristics on the accuracy of the air conditioning load identification model. Experimental results demonstrate that five key features significantly influence the load identification outcomes. This approach provides valuable insights for advancing the lightweight design, generalization, and interpretability of air conditioning load identification models.
