3 citations · 4 across the 7 of their papers we have counts for
4 papers · 1 filter
Self-Supervised Tuning of Low-Fidelity Optimization Models via High-Fidelity Feedback
Gonzalo E. Constante-Flores, André H. Quisaguano-Paredes, Asha Ramanujam +2
Low-fidelity (LF) optimization models are widely used in large-scale operations because they can be solved efficiently and reliably, but they often exhibit systematic errors relati…
Self-Supervised Learning of Parametric Approximation for Security-Constrained DC-OPF
Anderson Anrrango, André Quisaguano, Gonzalo E. Constante-Flores +1
This paper introduces a self-supervised learning framework for approximating the Security-Constrained DC Optimal Power Flow (SC-DCOPF) problem using a parametric linear model. The…
A Quadratically-Constrained Convex Approximation for the AC Optimal Power Flow
Gonzalo E. Constante-Flores, Can Li
We introduce a quadratically-constrained approximation (QCAC) of the AC optimal power flow (AC-OPF) problem. Unlike existing approximations like the DC-OPF, our model does not rely…
AC-Network-Informed DC Optimal Power Flow for Electricity Markets
Gonzalo E. Constante-Flores, André H. Quisaguano, Antonio J. Conejo +1
This paper presents a parametric quadratic approximation of the AC optimal power flow (AC-OPF) problem for time-sensitive and market-based applications. The parametric approximatio…