17 papers
The Proxy Benders Decomposition
Changkun Guan, El Mehdi Er Raqabi, Mathieu Tanneau +1
Benders decomposition is a fundamental framework for solving large-scale mixed-integer optimization problems with complicating variables that, when fixed, yield significantly easie…
Enhanced Renewable Energy Forecasting using Context-Aware Conformal Prediction
Alireza Moradi, Mathieu Tanneau, Reza Zandehshahvar +1
Artificial intelligence (AI) is increasingly used to support renewable energy forecasting and grid operations. As renewable penetration grows, reliable probabilistic forecasting is…
Self-Certifying Primal-Dual Optimization Proxies for Large-Scale Batch Economic Dispatch
Michael Klamkin, Mathieu Tanneau, Pascal Van Hentenryck
Recent research has shown that optimization proxies can be trained to high fidelity, achieving average optimality gaps under 1% for large-scale problems. However, worst-case analys…
A Hybrid Decomposition Approach for Stochastic Unit Commitment with Combined-Cycle Generators
Rosemary Barrass, Harsha Nagarajan, Mathieu Tanneau +2
The U.S. power grid is undergoing a major paradigm shift with the increased development of renewable generators, electric vehicles, and data centers. In response to this growing ne…
Copula-Based Aggregation and Context-Aware Conformal Prediction for Reliable Renewable Energy Forecasting
Alireza Moradi, Mathieu Tanneau, Reza Zandehshahvar +1
The rapid growth of renewable energy penetration has intensified the need for reliable probabilistic forecasts to support grid operations at aggregated (fleet or system) levels. In…
Volt/VAR Optimization in Transmission Networks with Discrete-Control Devices
Shuaicheng Tong, Michael A. Boateng, Mathieu Tanneau +1
Voltage (Volt) and reactive-power (VAR) control in transmission networks is critical for reliability and increasingly needs fast, implementable decisions. This paper presents a tra…