11 citations · 21 across the 12 of their papers we have counts for
12 papers
A Unified Approach for Learning the Dynamics of Power System Generators and Inverter-based Resources
Shaohui Liu, Weiqian Cai, Hao Zhu +1
The growing prevalence of inverter-based resources (IBRs) for renewable energy integration and electrification greatly challenges power system dynamic analysis. To account for both…
Data-driven Forced Oscillation Localization using Inferred Impulse Responses
Shaohui Liu, Hao Zhu, Vassilis Kekatos
Poorly damped oscillations pose threats to the stability and reliability of interconnected power systems. In this work, we propose a comprehensive data-driven framework for inferri…
Wind Power Scenario Generation Using Graph Convolutional Generative Adversarial Network
Young-ho Cho, Shaohui Liu, Duehee Lee +1
Generating wind power scenarios is very important for studying the impacts of multiple wind farms that are interconnected to the grid. We develop a graph convolutional generative a…
Dynamic Response Recovery Using Ambient Synchrophasor Data: A Synthetic Texas Interconnection Case Study
Shaohui Liu, Hao Zhu, Vassilis Kekatos
Wide-area dynamic studies are of paramount importance to ensure the stability and reliability of power grids. This paper puts forth a comprehensive framework for inferring the dyna…
Topology-aware Graph Neural Networks for Learning Feasible and Adaptive ac-OPF Solutions
Shaohui Liu, Chengyang Wu, Hao Zhu
Solving the optimal power flow (OPF) problem is a fundamental task to ensure the system efficiency and reliability in real-time electricity grid operations. We develop a new topolo…
A Confidence-based Iterative Solver of Depths and Surface Normals for Deep Multi-view Stereo
Wang Zhao, Shaohui Liu, Yi Wei +2
In this paper, we introduce a deep multi-view stereo (MVS) system that jointly predicts depths, surface normals and per-view confidence maps. The key to our approach is a novel sol…
NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo
Yi Wei, Shaohui Liu, Yongming Rao +3
In this work, we present a new multi-view depth estimation method that utilizes both conventional reconstruction and learning-based priors over the recently proposed neural radianc…
Risk-Aware Learning for Scalable Voltage Optimization in Distribution Grids
Shanny Lin, Shaohui Liu, Hao Zhu
Real-time coordination of distributed energy resources (DERs) is crucial for regulating the voltage profile in distribution grids. By capitalizing on a scalable neural network (NN)…
Graph Neural Networks for Learning Real-Time Prices in Electricity Market
Shaohui Liu, Chengyang Wu, Hao Zhu
Solving the optimal power flow (OPF) problem in real-time electricity market improves the efficiency and reliability in the integration of low-carbon energy resources into the powe…
A Dynamic Response Recovery Framework Using Ambient Synchrophasor Data
Shaohui Liu, Hao Zhu, Vassilis Kekatos
Wide-area dynamic studies are of paramount importance to ensure the stability and reliability of power grids. The rising deployment synchrophasor and other sensing technologies has…
Probabilistic analysis of masked loads with aggregated photovoltaic production
Shaohui Liu, Daniel Adrian Maldonado, Emil M. Constantinescu
In this paper we present a probabilistic analysis framework to estimate behind-the-meter photovoltaic generation in real time. We develop a forward model consisting of a spatiotemp…
A Functional Package for Automatic Solution of Ordinary Differential Equations with Spectral Methods
Shaohui Liu, Tianshi Wang, Youran Zhang
We present a Python module named PyCheb, to solve the ordinary differential equations by using spectral collocation method. PyCheb incorporates discretization using Chebyshev point…