中圖分類號： TP391.4
文獻標識碼： A
DOI： 10.19358/j.issn.2096-5133.2022.03.013
引用格式： 王巖俊，蔡高琰，駱德漢，等. 基于差量特征與AdaBoost的家用負荷識別方法研究[J].信息技術(shù)與網(wǎng)絡安全，2022，41(3)：78-82.

Research on household load identification method based on difference features and AdaBoost

Abstract： Aiming at household load, a non-intrusive online load identification method using smart meters for data collection is proposed. This method uses the smart meter to calculate the difference feature vector of the load to build a feature library in advance, trains the AdaBoost classifier model which takes the decision tree as the weak classifier, and uses the feature vector contained in the alarm information of the smart meter when the load is switched to classify the load，and to achieve load online recognition. This method has good real-time performance and improves the recognition effect of a single decision tree model. The experimental results show that the proposed method is feasible，and realizes the acquisition of load usage information, has good practical application value.

Key words : non-intrusive load identification；smart meter；difference feature；adaptive boosting(AdaBoost)