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20192021
most citedDifferential Privacy of Aggregated DC Optimal Power Flow Data

4 citations · 5 across the 3 of their papers we have counts for

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5 papers · 1 filter

math.OC20211 cited

Robust Distributed and Localized Model Predictive Control

Carmen Amo Alonso, Jing Shuang Li, Nikolai Matni +1

We present a robust Distributed and Localized Model Predictive Control (rDLMPC) framework for large-scale structured linear systems. The proposed algorithm uses the System Level Sy…

math.OC2020

Synthesis to Deployment: Cyber-Physical Control Architectures

Shih-Hao Tseng, James Anderson

We consider the problem of how to deploy a controller to a (networked) cyber-physical system (CPS). Controlling a CPS is an involved task, and synthesizing a controller to respect…

math.OC2020

Explicit Distributed and Localized Model Predictive Control via System Level Synthesis

Carmen Amo Alonso, Nikolai Matni, James Anderson

An explicit Model Predictive Control algorithm for large-scale structured linear systems is presented. We base our results on Distributed and Localized Model Predictive Control (DL…

math.OC2020

Worst-Case Sensitivity of DC Optimal Power Flow Problems

James Anderson, Fengyu Zhou, Steven H. Low

In this paper we consider the problem of analyzing the effect a change in the load vector can have on the optimal power generation in a DC power flow model. The methodology is base…

math.OC2019

The Optimal Power Flow Operator: Theory and Computation

Fengyu Zhou, James Anderson, Steven H. Low

Optimal power flow problems (OPFs) are mathematical programs used to determine how to distribute power over networks subject to network operation constraints and the physics of pow…