233 citations · 373 across the 18 of their papers we have counts for
10 papers · 1 filter
Dynamic State Estimation for Power System Control and Protection
Yu Liu, Abhinav Kumar Singh, Junbo Zhao +12
Dynamic state estimation (DSE) accurately tracks the dynamics of a power system and provides the evolution of the system state in real-time. This paper focuses on the control and p…
Distributed Robust State Estimation for Hybrid AC/DC Distribution Systems using Multi-Source Data
Manyun Huang, Junbo Zhao, Zhinong Wei +2
Hybrid AC/DC distribution systems are becoming a popular means to accommodate the increasing penetration of distributed energy resources and flexible loads. This paper proposes a d…
Data-Driven Assisted Chance-Constrained Energy and Reserve Scheduling with Wind Curtailment
Xingyu Lei, Zhifang Yang, Junbo Zhao +1
Chance-constrained optimization (CCO) has been widely used for uncertainty management in power system operation. With the prevalence of wind energy, it becomes possible to consider…
Analytic Deep Learning-based Surrogate Model for Operational Planning with Dynamic TTC Constraints
Gao Qiu, Youbo Liu, Junyong Liu +4
The increased penetration of wind power introduces more operational changes of critical corridors and the traditional time-consuming transient stability constrained total transfer…
Model-Free Voltage Regulation of Unbalanced Distribution Network Based on Surrogate Model and Deep Reinforcement Learning
Di Cao, Junbo Zhao, Weihao Hu +4
Accurate knowledge of the distribution system topology and parameters is required to achieve good voltage controls, but this is difficult to obtain in practice. This paper develops…
Real-time LCC-HVDC Maximum Emergency Power Capacity Estimation Based on Local PMU Measurements
Long Peng, Junbo Zhao, Yong Tang +3
The adjustable capacity of a line-commutated-converter High Voltage Direct Current (LCC-HVDC) connected to a power system, called the LCC-HVDC maximum emergency power capability or…
Distributed Voltage Regulation of Active Distribution System Based on Enhanced Multi-agent Deep Reinforcement Learning
Di Cao, Junbo Zhao, Weihao Hu +3
This paper proposes a data-driven distributed voltage control approach based on the spectrum clustering and the enhanced multi-agent deep reinforcement learning (MADRL) algorithm.…
Data-driven Optimal Power Flow: A Physics-Informed Machine Learning Approach
Xingyu Lei, Zhifang Yang, Juan Yu +3
This paper proposes a data-driven approach for optimal power flow (OPF) based on the stacked extreme learning machine (SELM) framework. SELM has a fast training speed and does not…
Nonlinear Virtual Inertia Control of WTGs for Enhancing Primary Frequency Response and Suppressing Drive-Train Torsional Oscillations
Bi Liu, Qi Huang, Junbo Zhao +2
Virtual inertia controllers (VICs) for wind turbine generators (WTGs) have been recently developed to compensate for the reduction of inertia in power systems. However, VICs can in…
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…