8 papers
Structured Differentiable Optimization for Efficient Decision-focused Learning in Power Systems
Wangkun Xu, Fei Teng
Decision-focused learning (DfL) trains forecasting models to align downstream decision consequences, such as power-system operating costs. However, its application to realistic pow…
Qubit-Efficient Quantum Annealing for Stochastic Unit Commitment
Wei Hong, Wangkun Xu, Fei Teng
Stochastic Unit Commitment (SUC) has been proposed to manage the uncertainties driven by renewable integration, but it leads to significant computational complexity. When accelerat…
Flow-based Polynomial Chaos Expansion for Uncertainty Quantification in Power System Dynamic Simulation
Le Fang, Wangkun Xu, Fei Teng
The large-scale integration of renewable energy sources introduces significant operational uncertainty into power systems. Although Polynomial Chaos Expansion (PCE) provides an eff…
Stochastic Virtual Power Plant Dispatch via Temporally Aggregated Distributed Predictive Control with Performance Guarantees
Luca Santosuosso, Fei Teng, Sonja Wogrin
This paper addresses the energy dispatch of a virtual power plant comprising renewable generation, energy storage, and thermal units under uncertainty in renewable output, energy p…
Learning-Augmented Power System Operations: A Unified Optimization View
Wangkun Xu, Zhongda Chu, Fei Teng
With the increasing penetration of renewable energy and inverter-based resources, traditional physics-based power-system operation faces growing challenges in maintaining economic…
Headroom as A Grid Service in Software-Defined Power Grids: A Peak-to-Peak Control Design Approach
Zhongda Chu, Fei Teng
To address system frequency challenges driven by the integration of renewable generation, advanced control strategies are designed at the device level to provide effective frequenc…