Publications

(2020). Programmable Quantum Annealers as Noisy Gibbs Samplers. arXiv.

arXiv

(2020). The Impacts of Convex Piecewise Linear Cost Formulations on AC Optimal Power Flow. arXiv.

arXiv

(2019). The Potential of Quantum Annealing for Rapid Solution Structure Identification. arXiv.

PDF Code arXiv

(2019). The Power Grid Library for Benchmarking AC Optimal Power Flow Algorithms. arXiv.

Code arXiv

(2019). Evaluating Ising Processing Units with Integer Programming. CPAIOR ‘19.

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(2018). Relaxations of AC Maximal Load Delivery for Severe Contingency Analysis. Transactions on Power Systems.

PDF Code arXiv

(2018). PowerModels.jl: An Open-Source Framework for Exploring Power Flow Formulations. PSCC ‘18.

Code arXiv

(2016). Strengthening the SDP Relaxation of AC Power Flows With Convex Envelopes, Bound Tightening, and Valid Inequalities. Transactions on Power Systems.

PDF arXiv

(2015). The QC Relaxation: A Theoretical and Computational Study on Optimal Power Flow. Transactions on Power Systems.

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(2015). Strengthening Convex Relaxations with Bound Tightening for Power Network Optimization. CP ‘15.

Preprint PDF Code

(2014). NESTA, The NICTA Energy System Test Case Archive. arXiv.

arXiv

(2014). A Linear-Programming Approximation of AC Power Flows. IJOC.

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