6 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…
Input Convex Neural Network as a Surrogate in Stability-Constrained Optimization for IBR-dominated Power Systems
Wangkun Xu, Hongyang Jia, Yi Wang +2
Input convex neural networks (ICNNs) are increasingly used as surrogates for stability indices and embedded as constraints in power-system optimization. This letter clarifies two r…
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…
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…
On the Incorporation of Stability Constraints into Sequential Operational Scheduling
Wangkun Xu, Zhongda Chu, Florin Capitanescu +1
With the increasing penetration of Inverter-Based Resources (IBRs), power system stability constraints must be incorporated into the operational framework, transforming it into sta…