VMD-AdaBoost-SVM-based adjustable load prediction method and system, and storage medium

The invention discloses an adjustable load prediction method and system based on a VMD-AdaBoost-SVM, and a storage medium. The prediction method comprises the following steps: converting a load curve and a load peak regulation curve; using a VMD model to decompose the load peak regulation curve to obtain each modal component; a plurality of SVM weak predictors are synthesized into one SVM strong predictor weak learning machine by using an AdaBoost algorithm, and a plurality of SVM weak predictors are synthesized into one strong predictor by using the advantages of AdaBoost, so that the transaction scale prediction of the adjustable load participating in the peak regulation market is realized; through comparison verification of different prediction models, it can be known that the prediction method can reduce the prediction error of the adjustable load peak regulation transaction scale, and the precision and stability of the prediction result are improved. 本发明公开了一种基于VMD-AdaBoost-SVM的可调负荷预测方法、系统及存储介质。预测方法包括：对负荷