• HUANG Tiangang ^1,2

  HUANG Tiangang

  School of Electrical Engineering, Southeast University, Nanjing 210096, China; NARI Group Corporation(State Grid Electric Power Research Institute), Nanjing 211106, China
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• XUE Yusheng ^2,3

  XUE Yusheng

  NARI Group Corporation(State Grid Electric Power Research Institute), Nanjing 211106, China; State Key Laboratory of Smart Grid Protection and Control, Nanjing 211106, China
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• LIN Zhenzhi ⁴

  LIN Zhenzhi

  College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
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• WEN Fushuan ⁴

  WEN Fushuan

  College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
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• XU Yan ⁵

  XU Yan

  School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore
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• YUE Dong ⁶

  YUE Dong

  Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
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1. School of Electrical Engineering, Southeast University, Nanjing 210096, China;2. NARI Group Corporation(State Grid Electric Power Research Institute), Nanjing 211106, China;3. State Key Laboratory of Smart Grid Protection and Control, Nanjing 211106, China;4. College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China;5. School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore;6. Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China

In the full process of extended equal area criterion(EEAC)algorithm, dynamic EEAC(DEEAC)is the bridge between analytical static EEAC(SEEAC)and accurate integrating EEAC(IEEAC). For better coordinating the accuracy of IEEAC and the speedability of SEEAC, the influence of the subsection number of DEEAC on the performance of full EEAC is studied in detail. Based on theoretical analysis as well as the machine learning method, an adaptive segmental Taylor series expansion and dimensional reduction mapping are adopted to replace the 2-section expansions for post-fault in DEEAC. The difference between the stability margin given by the original DEEAC and that given by SEEAC is defined as the time-varying index. According to the index, the number of subsections in DEEAC can be adjusted automatically. Its robust performance is verified by 36 sets of data from 9 actual Chinese regional and provincial power systems, where both symmetric and asymmetric faults are considered, totally 3 272 cases. Compared with the average computational burden of the original DEEAC, the computational burden of the proposed adaptive DEEAC increases about 4%, however, the analysis precision for strong time-varying cases, as well as the effectiveness of the classifier for stable cases are significantly improved.

extended equal area criterion(EEAC); imaging system; time-varying degree; piecewise Hamilton-approximation; coordination within an algorithm family; power system transient stability