61 citations · 166 across the 10 of their papers we have counts for
14 papers
Compact Optimization Learning for AC Optimal Power Flow
Seonho Park, Wenbo Chen, Terrence W. K. Mak +1
This paper reconsiders end-to-end learning approaches to the Optimal Power Flow (OPF). Existing methods, which learn the input/output mapping of the OPF, suffer from scalability is…
Bucketized Active Sampling for Learning ACOPF
Michael Klamkin, Mathieu Tanneau, Terrence W. K. Mak +1
This paper considers optimization proxies for Optimal Power Flow (OPF), i.e., machine-learning models that approximate the input/output relationship of OPF. Recent work has focused…
Learning Regionally Decentralized AC Optimal Power Flows with ADMM
Terrence W. K. Mak, Minas Chatzos, Mathieu Tanneau +1
One potential future for the next generation of smart grids is the use of decentralized optimization algorithms and secured communications for coordinating renewable generation (e.…
Spatial Network Decomposition for Fast and Scalable AC-OPF Learning
Minas Chatzos, Terrence W. K. Mak, Pascal Van Hentenryck
This paper proposes a novel machine-learning approach for predicting AC-OPF solutions that features a fast and scalable training. It is motivated by the two critical considerations…
Load Encoding for Learning AC-OPF
Terrence W. K. Mak, Ferdinando Fioretto, Pascal VanHentenryck
The AC Optimal Power Flow (AC-OPF) problem is a core building block in electrical transmission system. It seeks the most economical active and reactive generation dispatch to meet…
High-Fidelity Machine Learning Approximations of Large-Scale Optimal Power Flow
Minas Chatzos, Ferdinando Fioretto, Terrence W. K. Mak +1
The AC Optimal Power Flow (AC-OPF) is a key building block in many power system applications. It determines generator setpoints at minimal cost that meet the power demands while sa…
Bilevel Optimization for Differentially Private Optimization in Energy Systems
Terrence W. K. Mak, Ferdinando Fioretto, Pascal Van Hentenryck
This paper studies how to apply differential privacy to constrained optimization problems whose inputs are sensitive. This task raises significant challenges since random perturbat…
Lagrangian Duality for Constrained Deep Learning
Ferdinando Fioretto, Pascal Van Hentenryck, Terrence WK Mak +3
This paper explores the potential of Lagrangian duality for learning applications that feature complex constraints. Such constraints arise in many science and engineering domains,…
Privacy-Preserving Obfuscation for Distributed Power Systems
Terrence W. K. Mak, Ferdinando Fioretto, Pascal Van Hentenryck
This paper considers the problem of releasing privacy-preserving load data of a decentralized operated power system. The paper focuses on data used to solve Optimal Power Flow (OPF…
Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods
Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck
The Optimal Power Flow (OPF) problem is a fundamental building block for the optimization of electrical power systems. It is nonlinear and nonconvex and computes the generator setp…
Privacy-Preserving Obfuscation of Critical Infrastructure Networks
Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck
The paper studies how to release data about a critical infrastructure network (e.g., the power network or a transportation network) without disclosing sensitive information that ca…
Differential Privacy for Power Grid Obfuscation
Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck
The availability of high-fidelity energy networks brings significant value to academic and commercial research. However, such releases also raise fundamental concerns related to pr…
Phase Transitions for Optimality Gaps in Optimal Power Flows A Study on the French Transmission Network
Terrence W. K. Mak, Lyndon Shi, Pascal Van Hentenryck
This paper investigates phase transitions on the optimality gaps in Optimal Power Flow (OPF) problem on real-world power transmission systems operated in France. The experimental r…
Efficient Dynamic Compressor Optimization in Natural Gas Transmission Systems
Terrence W. K. Mak, Pascal Van Hentenryck, Anatoly Zlotnik +2
The growing reliance of electric power systems on gas-fired generation to balance intermittent sources of renewable energy has increased the variation and volume of flows through n…