233 citations · 262 across the 7 of their papers we have counts for
7 papers
Roles of Dynamic State Estimation in Power System Modeling, Monitoring and Operation
Junbo Zhao, Marcos Netto, Zhenyu Huang +13
Power system dynamic state estimation (DSE) remains an active research area. This is driven by the absence of accurate models, the increasing availability of fast-sampled, time-syn…
Adaptive Power System Emergency Control using Deep Reinforcement Learning
Qiuhua Huang, Renke Huang, Weituo Hao +3
Power system emergency control is generally regarded as the last safety net for grid security and resiliency. Existing emergency control schemes are usually designed off-line based…
A Comparative Study of Interface Techniques for Transmission and Distribution Dynamic Co-Simulation
Qiuhua Huang, Renke Huang, Rui Fan +5
Transmission and distribution dynamic co-simulation is a practical and effective approach to leverage existing simulation tools for transmission and distribution systems to simulat…
AMPS: An Augmented Matrix Formulation for Principal Submatrix Updates with Application to Power Grids
Yu-Hong Yeung, Alex Pothen, Mahantesh Halappanavar +1
We present AMPS, an augmented matrix approach to update the solution to a linear system of equations when the matrix is modified by a few elements within a principal submatrix. Thi…
Adaptive Adjustment of Noise Covariance in Kalman Filter for Dynamic State Estimation
Shahrokh Akhlaghi, Ning Zhou, Zhenyu Huang
Accurate estimation of the dynamic states of a synchronous machine (e.g., rotor s angle and speed) is essential in monitoring and controlling transient stability of a power system.…
Decentralized Robust Control for Damping Inter-area Oscillations in Power Systems
Jianming Lian, Shaobu Wang, Ruisheng Diao +1
As power systems become more and more interconnected, the inter-area oscillations has become a serious factor limiting large power transfer among different areas. Underdamped (Unda…
Comparative Study of Clustering Techniques for Real-Time Dynamic Model Reduction
Emilie Purvine, Eduardo Cotilla-Sanchez, Mahantesh Halappanavar +4
Dynamic model reduction in power systems is necessary for improving computational efficiency. Traditional model reduction using linearized models or online analysis is not adequate…