Details

Autor(en) / Beteiligte

• Cai, Weiwei
• Shi, Yuxin
• Han, Weiheng
• Ren, Lijia
• Lei, Ting
• Liu, Hourui
• Xie, Jingchi
• Huang, Sheng

Titel

Reliability Evaluation Method of Power Grid Security and Stability Control System Based on Survival Theory and Deep Learning

Ist Teil von

• 2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia), 2021, p.1065-1070

Ort / Verlag

IEEE

Erscheinungsjahr

2021

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• The research on the reliability evaluation of the Power Grid Security and Stability Control System (PGSSCS) is the basis for the design of the system, which is also an important guarantee for the normal operation of the power system. Traditional complex mathematical modeling methods do not match the real-time requirements in analysis. Firstly, the research results of reliability evaluation indicators and reliability evaluation modeling methods of PGSSCS have been analyzed. Secondly, the reliability evaluation methods of the PGSSCS based on survival theory and convolutional neural network, which can accurately and quickly realize reliability evaluation, are respectively analyzed. Then, the above two reliability modeling methods were used to analyze PGSSCS with two-layer dual-redundant, and the reliability indexes were calculated respectively. Finally, the training set error and the test set error in the training process are calculated by the two modeling methods respectively. The size of the error between the two different methods and the pros and cons of the training time were compared and analyzed.