10 papers
Diagnosis-Driven Co-planning of Network Reinforcement and BESS for Distribution Grid with High Penetration of Electric Vehicles
Linhan Fang, Elias Raffoul, Xingpeng Li
While the rapid proliferation of electric vehicles (EVs) accelerates net-zero goals, uncoordinated charging activities impose severe operational challenges on distribution grids, i…
Violation-Informed Spatio-Temporal Adaptive Targeting Framework for EV-Driven Distribution System Expansion Planning
Linhan Fang, Xingpeng Li
The rapid adoption of electric vehicles (EVs) can cause severe voltage drops and line current overloads in distribution networks, creating an urgent need for scalable expansion pla…
Hosting Capacity Assessment and Enhancement for Edge Data Centers in Active Distribution Networks
Linhan Fang, Xingpeng Li
With the increasing demand for edge computing and AI-driven workloads, integrating small and medium-sized edge data centers into distribution networks has become increasingly impor…
Net Load Forecasting Using Machine Learning with Growing Renewable Power Capacity Features: A Comparative Study of Direct and Indirect Methods
Oluwafolajimi Samuel Bolusteve, Linhan Fang, Xingpeng Li
Renewable energy adoption has increased significantly over the past few years. However, with the increasing adoption of renewable energy, forecasting the net load has become a majo…
Grid Operational Benefit Analysis of Data Center Spatial Flexibility: Congestion Relief, Renewable Energy Curtailment Reduction, and Cost Saving
Haoxiang Wan, Linhan Fang, Xingpeng Li
Data centers are facilities housing computing infrastructure for processing and storing digital information. The rapid expansion of artificial intelligence is driving unprecedented…
Data-Driven EV Charging Load Profile Estimation and Typical EV Daily Load Dataset Generation
Linhan Fang, Jesus Silva-Rodriguez, Xingpeng Li
Widespread electric vehicle (EV) adoption introduces new challenges for distribution grids due to large, localized load increases, stochastic charging behavior, and limited data av…