Publications (70)
Collaborative Bayesian Optimization via Wasserstein Barycenters
Donglin Zhan, Haoting Zhang, Rhonda Righter +2
Motivated by the growing need for black-box optimization and data privacy, we introduce a collaborative Bayesian optimization (BO) framework that addresses both of these challenges…
Distributionally Robust Decision Making Leveraging Conditional Distributions
Yuxiao Chen, Jip Kim, James Anderson
Distributionally robust optimization (DRO) is a powerful tool for decision making under uncertainty. It is particularly appealing because of its ability to leverage existing data.…
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…
Approximate Projections onto the Positive Semidefinite Cone Using Randomization
Morgan Jones, James Anderson
This paper presents two novel algorithms for approximately projecting symmetric matrices onto the Positive Semidefinite (PSD) cone using Randomized Numerical Linear Algebra (RNLA).…
Identification of Intraday False Data Injection Attack on DER Dispatch Signals
Jip Kim, Siddharth Bhela, James Anderson +1
The urgent need for the decarbonization of power girds has accelerated the integration of renewable energy. Concurrently the increasing distributed energy resources (DER) and advan…
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…