Electric power system voltage stability evaluation misclassification constraint method based on umbrella-type algorithm

Abstract

An electric power system voltage stability evaluation misclassification constraint method based on an umbrella-type algorithm comprises: a step 1, constructing an initial data set, and constructing avoltage stability safety classification label based on an electric power system voltage stability evaluation rule; a step 2, selecting a key operation variable to construct an efficient sample set; astep 3, performing offline training on the voltage stability evaluation model; a step 4, sending a new sample set generated under a new operation working condition into the voltage stability evaluation model to update the model; and a step 5, completing online voltage stability evaluation by using the trained voltage stability evaluation model. The invention aims to solve the limitations of a traditional VSA model constructed based on a data driving tool in the aspects of misclassification constraints and a model updating mechanism. An electric power system voltage stability evaluation misclassification constraint method based on an umbrella-type algorithm is provided, so that the VSA model can provide a VSA result which balances the overall classification precision and the class of classification error constraints.

Description

[0001] The invention belongs to the field of power system voltage stability evaluation, and in particular relates to a misclassification constraint method for power system voltage stability evaluation based on an umbrella algorithm. Background technique [0002] The power system is one of the most complex industrial systems in the world, and its safe operation has always been a concern in system development. In recent years, the wide-area interconnection of modern power systems, the investment of renewable energy, the application of new equipment, the rapid growth of load, and the limitations of transmission capacity have become more and more obvious. The operating burden of the power system is getting heavier and heavier, and the operating state is getting closer and closer to the limit. Static voltage stability is an issue of great concern, and many blackouts are related to it, which may cause huge economic losses and adverse social impacts. Therefore, a reliable voltage st...

AI Technical Summary

Problems solved by technology

[0006] ①The relationship between the overall classification accuracy and the class I classification error rate cannot be well balanced, and the class I classification errors are constrained according to the severity of different VSA misclassifications, so as to reduce the risk of class I classification errors on system operation; ②Only rely on the decision tree Constructed VSA model, when the object attributes in the dataset have missing values, the performance of the tree may be problematic, and the order of attributes in the tree nodes may have a negative impact on performance

The generalization ability of the VSA model constructed only by the decision tree cannot be guaranteed; ③ For the implementation of online VSA, there is a lack of a reliable model update mechanism, and it is difficult to guarantee the effectiveness of online VSA for invisible operating conditions

Images