A hierarchical self-adaptive data-analytics method for real-time power system short-term voltage stability assessment
As one of the most complex and largest dynamic industrial systems, a modern power grid envisages the wide-area measurement protection and control (WAMPAC) system as the grid sensing backbone to enhance security, reliability, and resiliency. However, based on the massive wide-area measurement data, h...
محفوظ في:
المؤلفون الرئيسيون: | Zhang, Yuchen, Xu, Yan, Dong, Zhao Yang, Zhang, Rui |
---|---|
مؤلفون آخرون: | School of Electrical and Electronic Engineering |
التنسيق: | مقال |
اللغة: | English |
منشور في: |
2021
|
الموضوعات: | |
الوصول للمادة أونلاين: | https://hdl.handle.net/10356/151001 |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Real-time assessment of fault-induced delayed voltage recovery : a probabilistic self-adaptive data-driven method
بواسطة: Zhang, Yuchen, وآخرون
منشور في: (2020) -
A missing-data tolerant method for data-driven short-term voltage stability assessment of power systems
بواسطة: Zhang, Yuchen, وآخرون
منشور في: (2021) -
An ensemble approach for short-term load forecasting by extreme learning machine
بواسطة: Li, Song, وآخرون
منشور في: (2017) -
Robust ensemble data analytics for incomplete PMU measurements-based power system stability assessment
بواسطة: Zhang, Yuchen, وآخرون
منشور في: (2020) -
Ensemble learning of deep learning-based receiver for 5G communication system implementation
بواسطة: Xu, Ziang
منشور في: (2024)