120 citations · 483 across the 46 of their papers we have counts for
46 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…
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…
Deriving AC OPF Solutions via Proximal Policy Optimization for Secure and Economic Grid Operation
Yuhao Zhou, Bei Zhang, Chunlei Xu +5
Optimal power flow (OPF) is a very fundamental but vital optimization problem in the power system, which aims at solving a specific objective function (ex.: generator costs) while…
Extended Prony Analysis on Power System Oscillation Under a Near-Resonance Condition
Tianwei Xia, Zhe Yu, Kai Sun +2
Power system oscillations under a large disturbance often exhibit distorted waveforms as captured by increasingly deployed phasor measurement units. One cause is the occurrence of…
Implications of Stahl's Theorems to Holomorphic Embedding Pt. 1: Theoretical Convergence
Songyan Li, Daniel Tylavsky, Di Shi +1
What has become known as Stahl's Theorem in power engineering circles has been used to justify a convergence guarantee of the Holormorphic Embedding Method (HEM) as it applies to t…
Implications of Stahl's Theorems to Holomorphic Embedding Pt. 2: Numerical Convergence
Abhinav Dronamraju, Songyan Li, Qirui Li +4
What has become known as Stahl's Theorem in power-engineering circles has been used to justify a convergence guarantee of the Holomorphic Embedding Method (HEM) as it applies to th…
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…
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…
Global Sensitivity Analysis in Load Modeling via Low-rank Tensor
You Lin, Yishen Wang, Jianhui Wang +2
Growing model complexities in load modeling have created high dimensionality in parameter estimations, and thereby substantially increasing associated computational costs. In this…
AI-Based Autonomous Line Flow Control via Topology Adjustment for Maximizing Time-Series ATCs
Tu Lan, Jiajun Duan, Bei Zhang +4
This paper presents a novel AI-based approach for maximizing time-series available transfer capabilities (ATCs) via autonomous topology control considering various practical constr…
Two-stage WECC Composite Load Modeling: A Double Deep Q-Learning Networks Approach
Xinan Wang, Yishen Wang, Di Shi +2
With the increasing complexity of modern power systems, conventional dynamic load modeling with ZIP and induction motors (ZIP + IM) is no longer adequate to address the current loa…
Community Microgrid Planning Considering Building Thermal Dynamics
Xiaohu Zhang, Desong Bian, Di Shi +2
In this paper, the building thermal dynamic characteristics are introduced in the community microgrid (MG) planning model. The proposed planning model is formulated as a mixed inte…
A Deep Reinforcement Learning Based Approach for Optimal Active Power Dispatch
Jiajun Duan, Haifeng Li, Xiaohu Zhang +6
The stochastic and dynamic nature of renewable energy sources and power electronic devices are creating unique challenges for modern power systems. One such challenge is that the c…
Autonomous Voltage Control for Grid Operation Using Deep Reinforcement Learning
Ruisheng Diao, Zhiwei Wang, Di Shi +3
Modern power grids are experiencing grand challenges caused by the stochastic and dynamic nature of growing renewable energy and demand response. Traditional theoretical assumption…
Adaptive Robust Energy Management Strategy for Campus-Based Commercial Buildings Considering Comprehensive Comfort Levels
Zheming Liang, Desong Bian, Dawei Su +4
Neglecting consumers' comfort always leads to failure or slow-response to demand response request. In this paper, we propose several comprehensive comfort level models for various…
Probabilistic Load Forecasting via Point Forecast Feature Integration
Qicheng Chang, Yishen Wang, Xiao Lu +4
Short-term load forecasting is a critical element of power systems energy management systems. In recent years, probabilistic load forecasting (PLF) has gained increased attention f…
Short-term Load Forecasting at Different Aggregation Levels with Predictability Analysis
Yayu Peng, Yishen Wang, Xiao Lu +4
Short-term load forecasting (STLF) is essential for the reliable and economic operation of power systems. Though many STLF methods were proposed over the past decades, most of them…
Bayesian Estimation Based Parameter Estimation for Composite Load
Chang Fu, Zhe Yu, Di Shi +4
Accurate identification of parameters of load models is essential in power system computations, including simulation, prediction, and stability and reliability analysis. Convention…
Adaptive Online Learning with Momentum for Contingency-based Voltage Stability Assessment
Zhijie Nie, Xiaohu Zhang, Xiaoying Zhao +4
Voltage stability refers to the ability of a power system to maintain acceptable voltages among all buses under normal operating conditions and after a disturbance. In this paper,…
A Stacked Autoencoder Application for Residential Load Curve Forecast and Peak Shaving
Xinan Wang, Yishen Wang, Di Shi +1
For the last ten years, utilities have observed on-going transitions on consumers' load curves. The previously flat load curves have more frequently turned into duck-shape. This is…
Submodular Load Clustering with Robust Principal Component Analysis
Yishen Wang, Xiao Lu, Yiran Xu +4
Traditional load analysis is facing challenges with the new electricity usage patterns due to demand response as well as increasing deployment of distributed generations, including…
Optimal Energy Management for Commercial Buildings Considering Comprehensive Comfort Levels in a Retail Electricity Market
Zheming Liang, Desong Bian, Xiaohu Zhang +3
Demand response has been implemented by distribution system operators to reduce peak demand and mitigate contingency issues on distribution lines and substations. Specifically, the…
A Rprop-Neural-Network-Based PV Maximum Power Point Tracking Algorithm with Short-Circuit Current Limitation
Yao Cui, Zhehan Yi, Jiajun Duan +2
This paper proposes a resilient-backpropagation-neural-network-(Rprop-NN) based algorithm for Photovoltaic (PV) maximum power point tracking (MPPT). A supervision mechanism is prop…
Online Low Frequency Oscillation Detection and Analysis System with an Ensemble Filter
Desong Bian, Zhe Yu, Di Shi +2
The widespread deployment of phasor measurement unit (PMU) overpower systems makes it possible to monitor and analyze grid dynamics in real-time. Low-frequency oscillation is harmf…