collaborators

6 papers

eess.SY2026

WAKE-NET: A 3D-Wake-Aware Economic Turbine Layout and Cabling Optimization Framework for Multi-Capacity Multi-Hub-Height Wind Farms Serving Grid-Scale and Industrial Power Systems

Ann Mary Toms, Xingpeng Li

The global transition towards renewable energy has accelerated the deployment of utility-scale wind farms, increasing the need for accurate performance and economic assessments. Al…

eess.SY2026

Optimal Microgrid Sizing of Offshore Renewable Energy Sources for Offshore Platforms and Coastal Communities

Ann Mary Toms, Xingpeng Li, Kaushik Rajashekara

The global energy landscape is undergoing a transformative shift towards renewable energy and advanced storage solutions, driven by the urgent need for sustainable and resilient po…

eess.SY2026

Deep Neural Network-Enhanced Frequency-Constrained Optimal Power Flow with Multi-Governor Dynamics

Fan Jiang, Xingpeng Li, Pascal Van Hentenryck

To ensure frequency security in power systems, both the rate of change of frequency (RoCoF) and the frequency nadir (FN) must be explicitly accounted for in real-time frequency-con…

eess.SY2025

Frequency-Dynamics-Aware Economic Dispatch with Optimal Grid-Forming Inverter Allocation and Reserved Power Headroom

Fan Jiang, Xingpeng Li

The high penetration of inverter-based resources (IBRs) reduces system inertia, leading to frequency stability concerns, especially during synchronous generator (SG) outages. To ma…

eess.SY2025

A Deep Neural Network-based Frequency Predictor for Frequency-Constrained Optimal Power Flow

Fan Jiang, Xingpeng Li, Pascal Van Hentenryck

Rate of change of frequency (RoCoF) and frequency nadir should be considered in real-time frequency-constrained optimal power flow (FCOPF) to ensure frequency stability of the mode…

eess.SP2025

Analysis of Learning-based Offshore Wind Power Prediction Models with Various Feature Combinations

Linhan Fang, Fan Jiang, Ann Mary Toms +1

Accurate wind speed prediction is crucial for designing and selecting sites for offshore wind farms. This paper investigates the effectiveness of various machine learning models in…