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Le Xie

Gordon McKay Professor of Electrical Engineering

Harvard University

United States

Research Interests

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Professors in United States Professors in Energy Engineering Energy Engineering professors in United States

About

Le Xie is a Professor at Texas A&M Engineering in the United States. His research interests encompass privacy-preserving energy management, congestion status identification, and the impacts of COVID-19 on the electricity sector. He has contributed to various publications, focusing on advanced methodologies for power systems, including the analysis of reusing retired batteries and optimizing survivable nano-grids.

Articles (27)

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Collaborators (5)

Tong Wu

Assistant Professor

University of Central Florida

UNITED STATES

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Chao Tian

Texas A&M University

UNITED STATES

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Chanan Singh

Regents Professor

Texas A&M University

UNITED STATES

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Minlan Yu

Harvard University

UNITED STATES

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Anna Scaglione

Professor

Cornell Tech

UNITED STATES

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Le Xie

Research Interests

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About

Articles (27)

Crucial Role of Foundation Models in Enhancing the Interaction of AI and Power Systems: Achieving Integrated Frameworks

Fréchet Power-Scenario Distance: A Measure for Evaluating Synthetic Data Across Multiple Time-Scales in Smart Grids

GridLDM: Unified Latent Diffusion for Cross-Domain, Language-Conditioned Power-System Time-Series Synthesis

Modeling Coincident Peak Pricing in Electricity Markets: Challenges and Peak Shaving Effectiveness

From Crypto Mining to Artificial Intelligence Training: Economic Drivers and Grid Impacts of the Data Center Transition

Flexibility-aware framework for efficient planner-initiated siting of data center

PowerMamba: A Deep State Space Model and Comprehensive Benchmark for Time Series Prediction in Electric Power Systems

A Review of Safe Reinforcement Learning Methods for Modern Power Systems

LLM-Based Adaptive Distribution Voltage Regulation Under Frequent Topology Changes: An In-Context MPC Framework

PowerAgent: A Road Map Toward Agentic Intelligence in Power Systems: Foundation Model, Model Context Protocol, and Workflow

Boosting Grid Throughput for a Sustainable Energy Future: The Role of AI and Advanced Materials

Accelerating Chance-Constrained SCED via Scenario Compression

Actionable Measures of Demand Side Resources as a Part of Virtual Power Plants: Case studies in Texas

Energy efficiency and carbon savings via a body grid

A Physics-Informed Graph Neural Network Framework for N-2 Contingency Screening: A Real-World Texas Grid Study

An Average Power-Based Planning Framework of Transmission Expansion: A New Role for Energy Storage

Open Power System Datasets and Open Simulation Engines: A Survey Toward Machine Learning Applications

Privacy-Preserving Energy Management of a Shared Energy Storage System for Smart Buildings: A Federated Deep Reinforcement Learning Approach

Unsupervised Congestion Status Identification Using LMP Data

A Comprehensive Power Flow Approach for Multi-terminal VSC-HVDC System Considering Cross-regional Primary Frequency Responses

A Cross-Domain Approach to Analyzing the Short-Run Impact of COVID-19 on the US Electricity Sector

A Synchrophasor Data-Driven Method for Forced Oscillation Localization under Resonance Conditions

Implications of COVID-19 for the electricity industry: A comprehensive review

Operational reliability and economy evaluation of reusing retired batteries in composite power systems

Overvoltage analysis and protection of lightning arresters in distribution systems with distributed generation

Planning of survivable nano-grids through jointly optimized water and electricity: The case of Colonias at the Texas-Mexico border

Prediction and assessment of demand response potential with coupon incentives in highly renewable power systems

Collaborators (5)

Tong Wu

Chao Tian

Chanan Singh

Minlan Yu

Anna Scaglione

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