14 citations · 16 across the 9 of their papers we have counts for
5 papers · 1 filter
A Globally Convergent Distributed Jacobi Scheme for Block-Structured Nonconvex Constrained Optimization Problems
Anirudh Subramanyam, Youngdae Kim, Michel Schanen +2
Motivated by the increasing availability of high-performance parallel computing, we design a distributed parallel algorithm for linearly-coupled block-structured nonconvex constrai…
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…
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…