30 citations · 79 across the 8 of their papers we have counts for
8 papers
DeepOPF-AL: Augmented Learning for Solving AC-OPF Problems with Multiple Load-Solution Mappings
Xiang Pan, Wanjun Huang, Minghua Chen +1
The existence of multiple load-solution mappings of non-convex AC-OPF problems poses a fundamental challenge to deep neural network (DNN) schemes. As the training dataset may conta…
Ensuring DNN Solution Feasibility for Optimization Problems with Convex Constraints and Its Application to DC Optimal Power Flow Problems
Tianyu Zhao, Xiang Pan, Minghua Chen +1
Ensuring solution feasibility is a key challenge in developing Deep Neural Network (DNN) schemes for solving constrained optimization problems, due to inherent DNN prediction error…
DeepOPF-V: Solving AC-OPF Problems Efficiently
Wanjun Huang, Xiang Pan, Minghua Chen +1
AC optimal power flow (AC-OPF) problems need to be solved more frequently in the future to maintain stable and economic power system operation. To tackle this challenge, a deep neu…
DeepOPF+: A Deep Neural Network Approach for DC Optimal Power Flow for Ensuring Feasibility
Tianyu Zhao, Xiang Pan, Minghua Chen +2
Deep Neural Networks (DNNs) approaches for the Optimal Power Flow (OPF) problem received considerable attention recently. A key challenge of these approaches lies in ensuring the f…
Multi-Granularity Modularized Network for Abstract Visual Reasoning
Xiangru Tang, Haoyuan Wang, Xiang Pan +1
Abstract visual reasoning connects mental abilities to the physical world, which is a crucial factor in cognitive development. Most toddlers display sensitivity to this skill, but…
DeepOPF: A Feasibility-Optimized Deep Neural Network Approach for AC Optimal Power Flow Problems
Xiang Pan, Minghua Chen, Tianyu Zhao +1
High percentage penetrations of renewable energy generations introduce significant uncertainty into power systems. It requires grid operators to solve alternative current optimal p…
DeepOPF: A Deep Neural Network Approach for Security-Constrained DC Optimal Power Flow
Xiang Pan, Tianyu Zhao, Minghua Chen +1
We develop DeepOPF as a Deep Neural Network (DNN) approach for solving security-constrained direct current optimal power flow (SC-DCOPF) problems, which are critical for reliable a…
DeepOPF: Deep Neural Network for DC Optimal Power Flow
Xiang Pan, Tianyu Zhao, Minghua Chen
We develop DeepOPF as a Deep Neural Network (DNN) approach for solving direct current optimal power flow (DC-OPF) problems. DeepOPF is inspired by the observation that solving DC-O…