DeepOPF: Deep Neural Network for DC Optimal Power Flow. - Xiang Pan; Tianyu Zhao 002; Minghua Chen 001 (SmartGridComm, 2019)

DeepOPF: A Deep Neural Network Approach for Security-Constrained DC Optimal Power Flow. - Xiang Pan; Tianyu Zhao 002; Minghua Chen 001 (CoRR, 2019)

DeepOPF+: A Deep Neural Network Approach for DC Optimal Power Flow for Ensuring Feasibility. - Tianyu Zhao 002; Xiang Pan; Minghua Chen 001; Andreas Venzke; Steven H. Low (SmartGridComm, 2020)

Ensuring DNN Solution Feasibility for Optimization Problems with Convex Constraints and Its Application to DC Optimal Power Flow Problems. - Tianyu Zhao 002; Xiang Pan; Minghua Chen 001; Steven H. Low (CoRR, 2021)

Efficient and Robust Equilibrium Strategies of Utilities in Day-Ahead Market With Load Uncertainty. - Tianyu Zhao 002; Hanling Yi; Minghua Chen 001; Chenye Wu; Yunjian Xu (IEEE Syst. J., 2022)

Optimizing Demand Response in Distribution Network with Grid Operational Constraints. - Tianyu Zhao 002; Min Zhou; Yanfang Mo; Jason Min Wang; Jun Luo 007; Xiang Pan; Minghua Chen 001 (e-Energy, 2023)

Ensuring DNN Solution Feasibility for Optimization Problems with Linear Constraints. - Tianyu Zhao 002; Xiang Pan; Minghua Chen 001; Steven H. Low (ICLR, 2023)

DeepOPF: A Feasibility-Optimized Deep Neural Network Approach for AC Optimal Power Flow Problems. - Xiang Pan; Minghua Chen 001; Tianyu Zhao 002; Steven H. Low (IEEE Syst. J., 2023)