A Critical Review of Data-Driven Transient Stability Assessment of Power Systems: Principles, Prospects and Challenges

Shitu Zhang, Zhixun Zhu and Yang Li
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Shitu Zhang: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Zhixun Zhu: GHN Energy Jilin Jiangnan Thermal Power Co., Ltd., Jilin 132013, China
Yang Li: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China

Energies, 2021, vol. 14, issue 21, 1-13

Abstract: Transient stability assessment (TSA) has always been a fundamental means for ensuring the secure and stable operation of power systems. Due to the integration of new elements such as power electronics, electric vehicles and renewable power generations, dynamic characteristics of power systems are becoming more and more complex, which makes TSA an increasingly urgent task. Since traditional time-domain simulations and direct method cannot meet the actual operation requirements of power systems, data-driven TSA has attracted growing attention from both academia and industry. This paper makes a comprehensive review from the following four aspects: feature extraction and selection, model construction, online learning and rule extraction; and then, summarizes the challenges and prospects for future research; finally, draws the conclusions of this review. This review will be beneficial for relevant researchers to better understand the research status, key technologies, and existing challenges in the field.

Keywords: transient stability assessment; power systems; data-driven approach; feature extraction and selection; model construction; review (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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