The invention relates to a power
system standby shortage risk scene identification method. The method comprises the following steps of: S1, selecting sample features influencing positive and negative standby, and constructing an
initial sample set; S2, screening sample features with relatively large
mutual information as training sample features, and constructing a training sample set; S3, constructing a
decision tree model, and determining an optimal division feature of the
decision tree model according to the Gini index of the training sample set under each training sample feature division; S4, selecting the minimum
sample number of the optimal leaf nodes by adopting a
cross validation method; S5, generating a
decision tree sequence with an error correction mechanism; S6,
pruning the decision tree sequence to generate an
optimal decision tree sequence with error correction codes; S7, evaluating the
decision tree model with the error correction mechanism; and S8, utilizing the evaluated
decision tree model to identify the standby shortage risk scene of a power
system. According to the method, the possible positive and negative standby shortage risk of the power
system can be pre-judged, so that the safety of the power system is ensured.