125 citations
- National Grid (United States)US2 papers
- Oak Ridge National LaboratoryUS2 papers
- Southern Methodist UniversityUS2 papers
- The Ohio State UniversityUS2 papers
- University of Michigan–DearbornUS2 papers
- American Electric Power (United States)US1 paper
- Arizona State UniversityUS1 paper
- Michigan Technological UniversityUS1 paper
- NARI Group (China)CN1 paper
- North Carolina State UniversityUS1 paper
- Pacific Northwest National LaboratoryUS1 paper
- State Grid Nanjing Power Supply Company (China)1 paper
24 papers
Evaluating Load Models and Their Impacts on Power Transfer Limits
Xinan Wang, Yishen Wang, Di Shi +4
Power transfer limits or transfer capability (TC) directly relate to the system operation and control as well as electricity markets. As a consequence, their assessment has to comp…
Parallel Betweenness Computation in Graph Database for Contingency Selection
Yongli Zhu, Renchang Dai, Guangyi Liu
Parallel betweenness computation algorithms are proposed and implemented in a graph database for power system contingency selection. Principles of the graph database and graph comp…
Time Series Classification for Locating Forced Oscillation Sources
Yao Meng, Zhe Yu, Ning Lu +1
Forced oscillations are caused by sustained cyclic disturbances. This paper presents a machine learning (ML) based time-series classification method that uses the synchrophasor mea…
Distributed Frequency Emergency Control with Coordinated Edge Intelligence
Yingmeng Xiang, Zhehan Yi, Xiao Lu +5
Developing effective strategies to rapidly support grid frequency while minimizing loss in case of severe contingencies is an important requirement in power systems. While distribu…
Graph Computing based Distributed State Estimation with PMUs
Yi Lu, Chen Yuan, Xiang Zhang +4
Power system state estimation plays a fundamental and critical role in the energy management system (EMS). To achieve a high performance and accurate system states estimation, a gr…
Wide Area Measurement System-based Low Frequency Oscillation Damping Control through Reinforcement Learning
Yousaf Hashmy, Zhe Yu, Di Shi +1
Ensuring the stability of power systems is gaining more attraction today than ever before, due to the rapid growth of uncertainties in load and renewable energy penetration. Lately…