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arXiv · 2511.15624

Fast and Certified Bounding of Security-Constrained DCOPF via Interval Bound Propagation

Eren Tekeler·Xiangru Zhong·Huan Zhang·Samuel Chevalier
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Abstract

Security-Constrained DC Optimal Power Flow (SC DCOPF) is an important tool for transmission system operators, enabling economically efficient and physically secure dispatch decisions. Although CPU-based commercial solvers (e.g., Gurobi) can efficiently solve SC-DCOPF problems with a reasonable number of security constraints, their performance degrades rapidly as both system size and the number of contingencies grow into thousands. In this paper, we design a computational graph representation of the SC-DCOPF-based market-clearing problem, inspired by the third ARPA-E Grid Optimization Competition. Using a tool from the neural network verification community known as Interval Bound Propagation (IBP), we quickly compute bounds on the optimal objective across the full set of N-1 contingencies. Our results demonstrate that IBP can compute certified bounds with mean optimal solution gaps below 3.98% on small cases, and it can efficiently scale up to 8,316 bus systems with thousands of contingencies.

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Eren Tekeler, Xiangru Zhong, Huan Zhang, Samuel Chevalier. 2025-11-19. Fast and Certified Bounding of Security-Constrained DCOPF via Interval Bound Propagation. https://arxiv.org/abs/2511.15624

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