1 citations · 1 across the 3 of their papers we have counts for
3 papers
math.OC2022★ 1 cited
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…
math.OC2022
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…
math.OC2022
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…