163 citations · 534 across the 25 of their papers we have counts for
10 papers · 1 filter
Encoding Frequency Constraints in Preventive Unit Commitment Using Deep Learning with Region-of-Interest Active Sampling
Yichen Zhang, Hantao Cui, Jianzhe Liu +4
With the increasing penetration of renewable energy, frequency response and its security are of significant concerns for reliable power system operations. Frequency-constrained uni…
Hybrid Imitation Learning for Real-Time Service Restoration in Resilient Distribution Systems
Yichen Zhang, Feng Qiu, Tianqi Hong +2
Self-healing capability is one of the most critical factors for a resilient distribution system, which requires intelligent agents to automatically perform restorative actions onli…
PowerNet: Multi-agent Deep Reinforcement Learning for Scalable Powergrid Control
Dong Chen, Kaian Chen. Zhaojian Li, Tianshu Chu +3
This paper develops an efficient multi-agent deep reinforcement learning algorithm for cooperative controls in powergrids. Specifically, we consider the decentralized inverter-base…
Robust Trajectory-Constrained Frequency Control for Microgrids Considering Model Linearization Error
Yichen Zhang, Chen Chen, Tianqi Hong +3
The capability to switch between grid-connected and islanded modes has promoted adoption of microgrid technology for powering remote locations. Stabilizing frequency during the isl…
Approximating Trajectory Constraints with Machine Learning -- Microgrid Islanding with Frequency Constraints
Yichen Zhang, Chen Chen, Guodong Liu +2
In this paper, we introduce a deep learning aided constraint encoding method to tackle the frequency-constraint microgrid scheduling problem. The nonlinear function between system…
Ensemble Learning Based Convex Approximation of Three-Phase Power Flow
Ren Hu, Qifeng Li, Feng Qiu
Though the convex optimization has been widely used in power systems, it still cannot guarantee to yield a tight (accurate) solution to some problems. To mitigate this issue, this…
Multi-Agent Safe Policy Learning for Power Management of Networked Microgrids
Qianzhi Zhang, Kaveh Dehghanpour, Zhaoyu Wang +2
This paper presents a supervised multi-agent safe policy learning (SMAS-PL) method for optimal power management of networked microgrids (MGs) in distribution systems. While convent…
Robust Estimation of Reactive Power for an Active Distribution System
Zhengshuo Li, Jianhui Wang, Hongbin Sun +2
Increasing distributed energy resources (DERs) may result in reactive power imbalance in a transmission power system (TPS). An active distribution power system (DPS) having DERs re…
Multi-Period Do-Not-Exceed Limit for Variable Renewable Generation Dispatch Considering Discrete Recourse Controls
Zhigang Li, Feng Qiu, Jianhui Wang
The do-not-exceed (DNE) limit method was proposed to accommodate more variable renewable generation (VRG) securely. However, the lack of involving discrete recourse control preclud…
Data-Driven Real-Time Power Dispatch for Maximizing Variable Renewable Generation
Zhigang Li, Feng Qiu, Jianhui Wang
Traditional power dispatch methods have difficulties in accommodating large-scale variable renewable generation (VRG) and have resulted in unnecessary VRG spillage in the practical…