5 citations · 11 across the 7 of their papers we have counts for
8 papers
Convex Restriction of Feasible Sets for AC Radial Networks
Ling Zhang, Daniel Tabas, Baosen Zhang
Many problems in power systems involve optimizing a certain objective function subject to power flow equations and engineering constraints. A long-standing challenge in solving the…
An Efficient Learning-Based Solver for Two-Stage DC Optimal Power Flow with Feasibility Guarantees
Ling Zhang, Daniel Tabas, Baosen Zhang
In this paper, we consider the scenario-based two-stage stochastic DC optimal power flow (OPF) problem for optimal and reliable dispatch when the load is facing uncertainty. Althou…
Learning to Solve the AC Optimal Power Flow via a Lagrangian Approach
Ling Zhang, Baosen Zhang
Using deep neural networks to predict the solutions of AC optimal power flow (ACOPF) problems has been an active direction of research. However, because the ACOPF is nonconvex, it…
An Iterative Approach to Improving Solution Quality for AC Optimal Power Flow Problems
Ling Zhang, Baosen Zhang
The existence of multiple solutions to AC optimal power flow (ACOPF) problems has been noted for decades. Existing solvers are generally successful in finding local solutions, whic…
An Iterative Approach to Finding Global Solutions of AC Optimal Power Flow Problems
Ling Zhang, Baosen Zhang
The existence of multiple solutions to AC optimal power flow (ACOPF) problems has been noted for decades. Existing solvers are generally successful in finding local solutions, whic…
A Convex Neural Network Solver for DCOPF with Generalization Guarantees
Ling Zhang, Yize Chen, Baosen Zhang
The DC optimal power flow (DCOPF) problem is a fundamental problem in power systems operations and planning. With high penetration of uncertain renewable resources in power systems…