Power System Transient Stability Based on Data Mining Theory

2017 3rd International Conference on Environmental Science and Material Application

生态环境科学;材料科学

Cui, Zhen^1 ; Shi, Jia^2 ; Wu, Runsheng^1 ; Lu, Dan^1 ; Cui, Mingde^1

State Grid Sichuan Tianfu New District Power Supply Company, Chengdu

610000, China^1

College of Electrical Engineering and New Energy, China Three Gorges University, Yichang

44300, China^2

关键词: Association classification;    Classification prediction;    Power system operations;    Power system transient stability;    Stability of power system;    Time-domain simulations;    Transient stability assessment;    Transient stability indices;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/108/5/052009/pdf
DOI  :  10.1088/1755-1315/108/5/052009

来源: IOP

【 摘 要 】

In order to study the stability of power system, a power system transient stability based on data mining theory is designed. By introducing association rules analysis in data mining theory, an association classification method for transient stability assessment is presented. A mathematical model of transient stability assessment based on data mining technology is established. Meanwhile, combining rule reasoning with classification prediction, the method of association classification is proposed to perform transient stability assessment. The transient stability index is used to identify the samples that cannot be correctly classified in association classification. Then, according to the critical stability of each sample, the time domain simulation method is used to determine the state, so as to ensure the accuracy of the final results. The results show that this stability assessment system can improve the speed of operation under the premise that the analysis result is completely correct, and the improved algorithm can find out the inherent relation between the change of power system operation mode and the change of transient stability degree.