Dr. Xingpeng Li is an Assistant Professor with the Department of Electrical and Computer Engineering at University of Houston (UH), Houston, TX, USA. He is a Senior Member of IEEE.
He is also the Associate Director of the Power Electronics, Microgrids & Subsea Electrical Systems Center (PEMSEC) at UH.
Education
- Ph.D., Electrical Engineering (Power Systems), Arizona State University, 2017
- M.S., Computer Science (Machine Learning), Georgia Institute of Technology, 2023
- M.S., Industrial Engineering (Operations Research/Optimization), Arizona State University, 2016
- M.S., Electrical Engineering (Power Systems), Zhejiang University, 2013
- B.S., Electrical Engineering (Power Engineering), Shandong University, 2010
Professional Experience
- Assistant Professor, University of Houston, Houston, TX, 2018 - present
- Visiting Faculty, Georgia Institute of Technology, Atlant, GA, 05.2023 - present
- Senior Application Engineer, ABB (now Hitachi Energy), San Jose, CA, 2017-2018
- Intern, PJM Interconnection, Audubon, PA, 2016
- Intern, ISO New England, Holyoke, MA, 2015
Teaching at UH
Awards & Honors
- NSF CAREER Award, National Science Foundation (NSF), USA, 2024
- Early-Career Research Follow, NAS Gulf Research Program, USA, 2023
- Recognition of Excellence, EVA and Human Surface Mobility Program of NASA, USA, 2023
- Emerging Leader, Offshore Technology Conference (OTC), 2023
- Energy Faculty Fellow, Georgia Tech, 2023
- Fellow of the NSF Convergence Research (CORE) Institute, USA, 2023
- Tier-1 Silver Award for the EITPIC prize competition, U.S. Department of Energy, 2019
- Tier-2 Silver Award for the EITPIC prize competition, U.S. Department of Energy, 2019
- IEEE Phoenix Section Student Scholarship, IEEE, 2016
Research Interests
- Application of machine learning and optimization methods in power energy systems
- Power system control, operations and planning
- Grid integration of renewable generation
- Microgrids optimal sizing and energy management
- Distributed energy resources, demand response
- Energy storage, battery degradation quantification
16 Classes taken at ASU (2013.08 - 2016.05)
- APM 525 High-Performance Computing
- EEE 575 Power System Stability
- EEE 576 Power System Dynamics
- EEE 577 Power Systems Operations and Planning
- EEE 598 Power Plant Control and Monitoring
- EEE 598 Electric Energy Markets
- EEE 598 Operations Research Applied to Electric Power Systems
- IEE 470 Stochastic Operations Research
- IEE 506 Web-enabled Decision Support Systems
- IEE 512 Introduction to Financial Engineering
- IEE 521 Urban Operations Research
- IEE 561 Production Systems
- IEE 574 Applied Deterministic Operations Research
- IEE 578 Regression Analysis
- IEE 620 Optimization I
- IEE 622 Optimization II
11 Classes taken at Gatech (2020.08 - 2023.05)
- CS 6515 Introduction to Graduate Algorithms
- CS 6601 Artificial Intelligence
- CS 6603 AI Ethics Society
- CS 7641 Machine Learning
- CS 7642 Reinforcement Learning and Decision Making
- CS 7643 Deep Learning
- CS 7646 Machine Learning for Trading
- CS 7280 Network Science
- ISYE 6420 Bayesian Methods
- ISYE 6501 Introduction to Analytics Modeling
- ISYE 6669 Deterministic Optimization
Papers (with link)
Spatio-Temporal Deep Learning-Assisted Reduced Security-Constrained Unit Commitment
Solar Power Generation Profile Estimation for Lunar Surface Solar PV Systems
N-1 Reduced Optimal Power Flow Using Augmented Hierarchical Graph Neural Network
Analysis of Weather and Time Features in Machine Learning-aided ERCOT Load Forecasting
Optimal Planning of PV and Battery Resources in Remote Microgrids Considering Degradation Costs: An Iterative Post-Optimization Correction-based Approach
Decentralized Micro Water-Energy Co-Optimization for Small Communities
Microgrid Optimal Energy Scheduling Considering Neural Network based Battery Degradation
Feasibility Layer Aided Machine Learning Approach for Day-Ahead Operations
Power and Hydrogen Hybrid Transmission for Renewable Energy Systems: An Integrated Expansion Planning Strategy
Transmission Planning for Climate-impacted Renewable Energy Grid: Data Preparation, Model Improvement, and Evaluation
Linearization of ReLU Activation Function for Neural Network-Embedded Optimization:Optimal Day-Ahead Energy Scheduling
Computational Enhancement for Day-Ahead Energy Scheduling with Sparse Neural Network-based Battery Degradation Model
Evaluation of Battery Energy Storage System to Provide Virtual Transmission Service
Security-Constrained Unit Commitment Considering Locational Frequency Stability in Low-Inertia Power Grids
Convolutional Neural Network-based RoCoF-Constrained Unit Commitment
Active Linearized Sparse Neural Network-based Frequency-Constrained Unit Commitment
Annual Benefit Analysis of Integrating the Seasonal Hydrogen Storage into the Renewable Power Grids
Selectively Linearized Neural Network based RoCoF-Constrained Unit Commitment in Low-Inertia Power Systems
Graph Neural Network-based Power Flow Model
Optimal Sizing of On-site Renewable Resources for Offshore Microgrids
Optimal Dynamic Reconfiguration of Distribution Networks
Cost-Benefit Analysis and Comparisons for Different Offshore Wind Energy Transmission Systems
Machine Learning Assisted Inertia Estimation using Ambient Measurements
Privacy-Preserving Decentralized Energy Management for Networked Microgrids via Objective-Based ADMM
Hierarchical Deep Learning Model for Degradation Prediction per Look-Ahead Scheduled Battery Usage Profile
A Synthetic Texas Backbone Power System with Climate-Dependent Spatio-Temporal Correlated Profiles
Quality Analysis of Battery Degradation Models with Real Battery Aging Experiment Data
Microgrid Optimal Energy Scheduling with Risk Analysis
Resilient Operational Planning for Microgrids Against Extreme Events
Deep Learning based Security-Constrained Unit Commitment Considering Locational Frequency Stability in Low-Inertia Power Systems
A 100% Renewable Energy System: Enabling Zero CO2 Emission Offshore Platforms
Centralized Networked Micro Water-Energy Nexus with Proportional Exchange Among Participants
An Alternative Method for Solving Security-Constrained Unit Commitment with Neural Network Based Battery Degradation Model
The Benefits of Hydrogen Energy Transmission and Conversion Systems to the Renewable Power Grids: Day-ahead Unit Commitment
Reduced Optimal Power Flow Using Graph Neural Network
Quantitative Analysis of Demand Response Using Thermostatically Controlled Loads
Machine Learning Assisted Model Reduction for Security-Constrained Unit Commitment
Wholesale Electricity Price Forecasting using Integrated Long-term Recurrent Convolutional Network Model
Neural Network-based Power Flow Model
An Accelerated-Decomposition Approach for Security-Constrained Unit Commitment with Corrective Network Reconfiguration
Long-term Recurrent Convolutional Networks-based Inertia Estimation using Ambient Measurements
Optimal Allocation of Virtual Inertia Devices for Enhancing Frequency Stability in Low-Inertia Power Systems
Optimal Skeleton Network Reconfiguration considering Topological Characteristics and Transmission Path
Water-Energy Co-Optimization for Community-Scale Microgrids
A Novel Real-Time Energy Management Strategy for Grid-Supporting Microgrid: Enabling Flexible Trading Power
Network Reconfiguration Impact on Renewable Energy System and Energy Storage System in Day-Ahead Scheduling
Dynamic Estimation of Power System Inertia Distribution Using Synchrophasor Measurements
A Novel Real-Time Energy Management Strategy for Grid-Friendly Microgrid: Harnessing Internal Fluctuation Internally
Enhancing System Flexibility through Corrective Demand Response in Security-Constrained Unit Commitment
Benefits and Cyber-Vulnerability of Demand Response System in Real-Time Grid Operations
Stochastic Optimal Power Flow with Network Reconfiguration: Congestion Management and Facilitating Grid Integration of Renewables
Sensitivity Factors based Transmission Network Topology Control for Violation Relief
Reducing Congestion-Induced Renewable Curtailment with Corrective Network Reconfiguration in Day-Ahead Scheduling
Fast Heuristic AC Power Flow Analysis with Data-Driven Enhanced Linearized Model
Enhancing Power System Cyber-Security with Systematic Two-Stage Detection Strategy
Power System Expansion Planning with Seasonal Network Optimization
Enhanced Energy Management System with Corrective Transmission Switching Strategy— Part II: Results and Discussion
Enhanced Energy Management System with Corrective Transmission Switching Strategy— Part I: Methodology
Security Constrained Unit Commitment with Corrective Transmission Switching
Real-Time Contingency Analysis with Correct Transmission Switching
A Data-driven Heuristic for Corrective Transmission Switching
Harnessing Flexible Transmission: Corrective Transmission Switching for ISO-NE
Fast Heuristics for Transmission Outage Coordination
Real-Time Contingency Analysis with Transmission Switching on Real Power System Data
Towards Smart Corrective Switching: Analysis and Advancement of PJM’s Switching Solutions
Effect of Topology Control on System Reliability: TVA Test Case
An Efficient PMU-based Fault Location Technique for Multi-Terminal Transmission Lines
A Hierarchical Energy Management Strategy for Grid-connected Microgrid
Optimal configuration of standalone wind-solar-storage power supply system
A Fuzzy Logical MPPT Control Strategy for PMSG Wind Generation System
Application of double fuzzy control in MPPT of grid-connected photovoltaic generation system
PMU-Based Fault Location Using Voltage Measurements in Large Transmission Networks
Resources (with link)
List of Papers with Data/Codes
Grid Real-Time Operation Simulator (GRTOS) software suite in Java
Power System Academia 101
Security-Constrained Economic Dispatch (SCED) in Python
Logging class/functions in Python
Stochastic Unit Commitment using Lagrangian Relaxation in AMPL
Procedure for Dynamic Simulation under Fault using PSS/E
Remote Access to Unix Servers
Cheat Sheet for General Linux Commands
Generation and Transmission Maintenance Scheduling using Lagrangian Relaxation in AMPL
ECE6327 Smart Grid Systems
Sample AMPL Codes (ECE6327)
Sample AMPL Codes (ECE6379)
Fast Decoupled Power Flow in Matlab
PSS/E Raw File Loader in Java
Logging class/functions in Java
TEP in AMPL
SOPF in AMPL
ECE6379 Power System Operations and Modeling
N-1 SCUC in AMPL
DCOPF in AMPL
Blogs (with link)
Judge - 65th Science & Engineering Fair of Houston (SEFH) - K12
2023 Fall Commencement - Cunzhi Zhao (PhD 2023F)
Group Thanksgiving Party 2023
2023 Spring Commencement - Arun Venkatesh Ramesh (PhD 2022F)
Group Meeting, Dinner and Fun Event
Group Fun Event on Campus (Bowling & Biliards)
Group Lunch on Campus
H-SEF of Harmony Public Schools (K12)
Group pre-Thanksgiving Party
Group Website Launch
