Weather index and weighted LS-SVM-based power system short-term load prediction method

The invention discloses a weather index and weighted LS-SVM-based power system short-term load prediction method. The method comprises the following steps of S1, obtaining a sample of original data; S2, according to the original data, calculating a comprehensive weather index; S3, performing data preprocessing on date type data and the comprehensive weather index; S4, according to an obtained dimensionless load characteristic quantity, performing gray correlation analysis between the dimensionless load characteristic quantity and a power system load, and calculating a characteristic quantity weight through a correlation degree obtained by the gray correlation analysis; and S5, building a weather index and weighted LS-SVM-based power system short-term load prediction model, performing parameter optimization by adopting a fruit fry optimization algorithm, and obtaining power system load prediction data of a to-be-predicted day through model output. The method has very good global optimization performance and few adjustment parameters, difficultly falls into local minimum and can effectively improve the power system short-term load prediction precision.