L
Liu Lihuang
Researcher at China Three Gorges University
Publications - 11
Citations - 116
Liu Lihuang is an academic researcher from China Three Gorges University. The author has contributed to research in topics: Electric power system & Feature selection. The author has an hindex of 4, co-authored 11 publications receiving 48 citations.
Papers
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Journal ArticleDOI
An Integrated Scheme for Online Dynamic Security Assessment Based on Partial Mutual Information and Iterated Random Forest
Liu Songkai,Liu Lihuang,Youping Fan,Lei Zhang,Yuehua Huang,Tao Zhang,Cheng Jiangzhou,Lingyun Wang,Menglin Zhang,Shi Ruoyuan,Mao Dan +10 more
TL;DR: An integrated scheme for online dynamic security assessment (DSA) based on feature selection and regression prediction and a spatial-temporal dynamic visualization approach is proposed, which can intuitively provide real-time dynamic security information of power systems.
Journal ArticleDOI
A data-driven approach for online dynamic security assessment with spatial-temporal dynamic visualization using random bits forest
Liu Songkai,Liu Lihuang,Yang Nan,Mao Dan,Lei Zhang,Cheng Jiangzhou,Tianliang Xue,Lian Liu,Yan Guanghui,Qiu Li,Chen Xi,Menglin Zhang,Shi Ruoyuan +12 more
TL;DR: An integrated framework for online DSA with spatial-temporal dynamic visualization with encouraging performance is demonstrated by tests on a 23-bus test system and a practical 1648-bus system.
Journal ArticleDOI
A Data-Driven and Data-Based Framework for Online Voltage Stability Assessment Using Partial Mutual Information and Iterated Random Forest
Liu Songkai,Shi Ruoyuan,Yuehua Huang,Li Xin,Zhenhua Li,Lingyun Wang,Mao Dan,Liu Lihuang,Siyang Liao,Menglin Zhang,Yan Guanghui,Lian Liu +11 more
TL;DR: A novel framework based on data for static voltage stability margin (VSM) assessment of power systems is presented and can select the key operation variables as input features for the assessment based on partial mutual information (PMI).
Journal ArticleDOI
An integrated scheme for static voltage stability assessment based on correlation detection and random bits forest
Liu Songkai,Shi Ruoyuan,Tao Zhang,Fei Tang,Lei Zhang,Liu Lihuang,Mao Dan,Zhenhua Li,Li Xin,Cheng Jiangzhou,Yan Guanghui,Lian Liu,Li Dan,Siyang Liao,Menglin Zhang +14 more
TL;DR: An integrated scheme is proposed to rapidly predict the voltage stability margin (VSM) based on correlation detection and random bits forest based on CD algorithms and the training of the RBF-based prediction model can be achieved.
Journal ArticleDOI
A Data-Driven Approach for Online Inter-Area Oscillatory Stability Assessment of Power Systems Based on Random Bits Forest Considering Feature Redundancy
Liu Songkai,Mao Dan,Tianliang Xue,Fei Tang,Li Xin,Liu Lihuang,Shi Ruoyuan,Siyang Liao,Menglin Zhang +8 more
TL;DR: An integrated scheme for inter-area oscillatory stability assessment (OSA) is proposed in this paper using a compositive feature selection unit and random bits forest (RBF) algorithm, and it can provide fast and accurate estimation of the oscillatory Stability margin (OSM) by using the real-time system operating data.