5 citations · 10 across the 9 of their papers we have counts for
4 papers · 2 filters
Efficient constraint learning for data-driven active distribution network operation
Ge Chen, Hongcai Zhang, Yonghua Song
Scheduling flexible sources to promote the integration of renewable generation is one fundamental problem for operating active distribution networks (ADNs). However, existing works…
Deep-quantile-regression-based surrogate model for joint chance-constrained optimal power flow with renewable generation
Ge Chen, Hongcai Zhang, Hongxun Hui +1
Joint chance-constrained optimal power flow (JCC-OPF) is a promising tool to manage uncertainties from distributed renewable generation. However, most existing works are based on p…
Chance-constrained DC Optimal Power Flow with Non-Gaussian Distributed Uncertainties
Ge Chen, Hongcai Zhang, Yonghua Song
Chance-constrained programming (CCP) is a promising approach to handle uncertainties in optimal power flow (OPF). However, conventional CCP usually assumes that uncertainties follo…
Chance-constrained regulation capacity offering for HVAC systems under non-Gaussian uncertainties with mixture-model-based convexification
Ge Chen, Hongcai Zhang, Hongxun Hui +1
Heating, ventilation, and air-conditioning (HVAC) systems are ideal demand-side flexible resources to provide regulation services. However, finding the best hourly regulation capac…