141 citations · 237 across the 46 of their papers we have counts for
14 papers · 1 filter
Self-Supervised Learning for Large-Scale Preventive Security Constrained DC Optimal Power Flow
Seonho Park, Pascal Van Hentenryck
Security-Constrained Optimal Power Flow (SCOPF) plays a crucial role in power grid stability but becomes increasingly complex as systems grow. This paper introduces PDL-SCOPF, a se…
Learning Optimal Power Flow Value Functions with Input-Convex Neural Networks
Andrew Rosemberg, Mathieu Tanneau, Bruno Fanzeres +2
The Optimal Power Flow (OPF) problem is integral to the functioning of power systems, aiming to optimize generation dispatch while adhering to technical and operational constraints…
Real-Time Risk Analysis with Optimization Proxies
Wenbo Chen, Mathieu Tanneau, Pascal Van Hentenryck
The increasing penetration of renewable generation and distributed energy resources requires new operating practices for power systems, wherein risk is explicitly quantified and ma…
Dual Conic Proxies for AC Optimal Power Flow
Guancheng Qiu, Mathieu Tanneau, Pascal Van Hentenryck
In recent years, there has been significant interest in the development of machine learning-based optimization proxies for AC Optimal Power Flow (AC-OPF). Although significant prog…
Strong Mixed-Integer Formulations for Transmission Expansion Planning with FACTS Devices
Kevin Wu, Mathieu Tanneau, Pascal Van Hentenryck
Transmission Network Expansion Planning (TNEP) problems find the most economical way of expanding a given grid given long-term growth in generation capacity and demand patterns. Th…
Machine Learning-assisted Dynamics-Constrained Day-Ahead Energy Scheduling
Mingjian Tuo, Xingpeng Li, Pascal Van Hentenryck
TThe rapid expansion of inverter-based resources, such as wind and solar power plants, will significantly diminish the presence of conventional synchronous generators in fu-ture po…
Revitalizing Public Transit in Low Ridership Areas: An Exploration of On-Demand Multimodal Transit Systems
Jiawei Lu, Connor Riley, Krishna Murthy Gurumurthy +1
Public transit plays an essential role in mitigating traffic congestion, reducing emissions, and enhancing travel accessibility and equity. One of the critical challenges in design…
On the Viability of Stochastic Economic Dispatch for Real-Time Energy Market Clearing
Haoruo Zhao, Mathieu Tanneau, Pascal Van Hentenryck
Over the past decade, the rapid adoption of intermittent renewable energy sources (RES), especially wind and solar generation, has posed challenges in managing real-time uncertaint…
Inertia-Constrained Generation Scheduling: Sample Selection, Learning-Embedded Optimization Modeling, and Computational Enhancement
Mingjian Tuo, Fan Jiang, Xingpeng Li +1
Day-ahead generation scheduling is typically conducted by solv-ing security-constrained unit commitment (SCUC) problem. However, with fast-growing of inverter-based resources, grid…
Impacts of Differential Privacy on Fostering more Racially and Ethnically Diverse Elementary Schools
Keyu Zhu, Nabeel Gillani, Pascal Van Hentenryck
In the face of increasingly severe privacy threats in the era of data and AI, the US Census Bureau has recently adopted differential privacy, the de facto standard of privacy prote…
End-to-End Feasible Optimization Proxies for Large-Scale Economic Dispatch
Wenbo Chen, Mathieu Tanneau, Pascal Van Hentenryck
The paper proposes a novel End-to-End Learning and Repair (E2ELR) architecture for training optimization proxies for economic dispatch problems. E2ELR combines deep neural networks…
Privacy and Bias Analysis of Disclosure Avoidance Systems
Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck +2
Disclosure avoidance (DA) systems are used to safeguard the confidentiality of data while allowing it to be analyzed and disseminated for analytic purposes. These methods, e.g., ce…
Two-Stage Learning For the Flexible Job Shop Scheduling Problem
Wenbo Chen, Reem Khir, Pascal Van Hentenryck
The Flexible Job-shop Scheduling Problem (FJSP) is an important combinatorial optimization problem that arises in manufacturing and service settings. FJSP is composed of two subpro…
Path-Based Formulations for the Design of On-demand Multimodal Transit Systems with Adoption Awareness
Hongzhao Guan, Beste Basciftci, Pascal Van Hentenryck
This paper reconsiders the ODMTS Design with Adoptions problem (ODMTS-DA) to capture the latent demand in on-demand multimodal transit systems. The ODMTS-DA is a bilevel optimizati…