14 citations · 31 across the 14 of their papers we have counts for
8 papers · 1 filter
A mixed complementarity problem approach for steady-state voltage and frequency stability analysis
Youngdae Kim, Kibaek Kim
We present a mixed complementarity problem (MCP) approach for a steady-state stability analysis of voltage and frequency of electrical grids. We perform a theoretical analysis prov…
Accelerated Computation and Tracking of AC Optimal Power Flow Solutions using GPUs
Youngdae Kim, Kibaek Kim
We present a scalable solution method based on an alternating direction method of multipliers and graphics processing units (GPUs) for rapidly computing and tracking a solution of…
A Reinforcement Learning Approach to Parameter Selection for Distributed Optimal Power Flow
Sihan Zeng, Alyssa Kody, Youngdae Kim +2
With the increasing penetration of distributed energy resources, distributed optimization algorithms have attracted significant attention for power systems applications due to thei…
Numerical Performance of Different Formulations for Alternating Current Optimal Power Flow
Sayed Abdullah Sadat, Kibaek Kim
Alternating current optimal power flow (ACOPF) problems are nonconvex and nonlinear optimization problems. Utilities and independent service operators (ISO) require ACOPF to be sol…
Leveraging GPU batching for scalable nonlinear programming through massive Lagrangian decomposition
Youngdae Kim, François Pacaud, Kibaek Kim +1
We present the implementation of a trust-region Newton algorithm ExaTron for bound-constrained nonlinear programming problems, fully running on multiple GPUs. Without data transfer…
Differentially Private Federated Learning via Inexact ADMM
Minseok Ryu, Kibaek Kim
Differential privacy (DP) techniques can be applied to the federated learning model to protect data privacy against inference attacks to communication among the learning agents. Th…