156 citations · 245 across the 19 of their papers we have counts for
19 papers
Safe Reinforcement Learning for Power System Control: A Review
Peipei Yu, Zhenyi Wang, Hongcai Zhang +1
The large-scale integration of intermittent renewable energy resources introduces increased uncertainty and volatility to the supply side of power systems, thereby complicating sys…
Customized Load Profiles Synthesis for Electricity Customers Based on Conditional Diffusion Models
Zhenyi Wang, Hongcai Zhang
Customers' load profiles are critical resources to support data analytics applications in modern power systems. However, there are usually insufficient historical load profiles for…
Optimal Planning for Electrical Collector System of Offshore Wind Farm with Double-sided Ring Topology
Xinwei Shen, Qiuwei Wu, Hongcai Zhang +1
We propose a planning method for offshore wind farm electrical collector system (OWF-ECS) with double-sided ring topology meeting the "N-1" criterion on cable faults, in which the…
Optimal Power Flow Based on Physical-Model-Integrated Neural Network with Worth-Learning Data Generation
Zuntao Hu, Hongcai Zhang
Fast and reliable solvers for optimal power flow (OPF) problems are attracting surging research interest. As surrogates of physical-model-based OPF solvers, neural network (NN) sol…
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…
District Cooling System Control for Providing Operating Reserve based on Safe Deep Reinforcement Learning
Peipei Yu, Hongxun Hui, Hongcai Zhang +2
Heating, ventilation, and air conditioning (HVAC) systems are well proved to be capable to provide operating reserve for power systems. As a type of large-capacity and energy-effic…
Scheduling HVAC loads to promote renewable generation integration with a learning-based joint chance-constrained approach
Ge Chen, Hongcai Zhang, Hongxun Hui +1
The integration of distributed renewable generation (DRG) in distribution networks can be effectively promoted by scheduling flexible resources such as heating, ventilation, and ai…
Data-Driven Dispatchable Regions with Potentially Active Boundaries for Renewable Power Generation: Concept and Construction
Yanqi Liu, Zhigang Li, Wei Wei +2
The dispatchable region of volatile renewable power generation (RPG) quantifies how much uncertainty the power system can handle at a given operating point. State-of-the-art dispat…
Topology-free optimal power dispatch for distribution network considering security constraints and flexible building thermal inertia
Ge Chen, Hongcai Zhang, Ningyi Dai +1
With the increasing integration of distributed PV generation, the distribution network requires more and more flexibility to achieve the security-constrained optimal power dispatch…
Solving Overstay in PEV Charging Station Planning via Chance Constrained Optimization
Teng Zeng, Hongcai Zhang, Scott Moura
Currently, the utilization rate of public plug-in electric vehicle (PEV) charging stations is only 15%. During the other 85% of the time, the chargers are either idle or occupied b…
Joint Fleet Sizing and Charging System Planning for Autonomous Electric Vehicles
Hongcai Zhang, Colin J. R. Sheppard, Timothy E. Lipman +1
This paper studies the joint fleet sizing and charging system planning problem for a company operating a fleet of autonomous electric vehicles (AEVs) for passenger and goods transp…
Plug-in Electric Vehicle Charging Congestion Analysis Using Taxi Travel Data in the Central Area of Beijing
Huimiao Chen, Hongcai Zhang, Zechun Hu +3
Recharging a plug-in electric vehicle is more time-consuming than refueling an internal combustion engine vehicle. As a result, charging stations may face serious congestion proble…
Coordinated Charging and Discharging Strategies for Plug-in Electric Bus Fast Charging Station with Energy Storage System
Huimiao Chen, Zechun Hu, Hongcai Zhang +1
Plug-in electric bus (PEB) is an environmentally friendly mode of public transportation and plug-in electric bus fast charging stations (PEBFCSs) play an essential role in the oper…
Data-driven Chance-constrained Regulation Capacity Offering for Distributed Energy Resources
Hongcai Zhang, Zechun Hu, Eric Munsing +2
This paper studies the behavior of a strategic aggregator offering regulation capacity on behalf of a group of distributed energy resources (DERs, e.g. plug-in electric vehicles) i…
Joint Planning of PEV Fast-Charging Network and Distributed PV Generation Using the Accelerated Generalized Benders Decomposition
Hongcai Zhang, Scott J. Moura, Zechun Hu +2
Integration of plug-in electric vehicles (PEVs) with distributed renewable resources will decrease PEVs' well-to-wheels greenhouse gas emissions, promote renewable power adoption a…
A Second Order Cone Programming Model for Planning PEV Fast-Charging Stations
Hongcai Zhang, Scott Moura, Zechun Hu +2
This paper studies siting and sizing of plug-in electric vehicle (PEV) fast-charging stations on coupled transportation and power networks. We develop a closed-form service rate mo…