7 papers
Learning-Assisted Day-Ahead Energy Scheduling for Frequency-Secure Inverter-Dominated Grids with Grid-Forming Battery Energy Storage Systems
Fan Jiang, Xingpeng Li
As grid-forming (GFM) battery energy storage systems (BESS) are increasingly deployed to enhance power system inertial response and frequency stability, incorporating their frequen…
Inertia-Constrained Generation Scheduling: Sample Selection, Learning-Embedded Optimization Modeling, and Computational Enhancement
Mingjian Tuo, Fan Jiang, Xingpeng Li +1
Day-ahead generation scheduling is typically conducted by solv-ing security-constrained unit commitment (SCUC) problem. However, with fast-growing of inverter-based resources, grid…
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…
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…
A Black Start Strategy for Hydrogen-integrated Renewable Grids with Energy Storage Systems
Jin Lu, Linhan Fang, Fan Jiang +1
With the increasing integration of renewable energy, the reliability and resilience of modern power systems are of vital significance. However, large-scale blackouts caused by natu…
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…