135 citations · 497 across the 36 of their papers we have counts for
9 papers · 1 filter
Data-driven Model Predictive Control Method for DFIG-based Wind Farm to Provide Primary Frequency Regulation Service
Zizhen Guo, Wenchuan Wu
As wind power penetration increases, the wind farms are required by newly released grid codes to provide frequency regulation service. The most critical challenge is how to formula…
A Nested Decomposition Method and Its Application for Coordinated Operation of Hierarchical Electrical Power Grids
Chenhui Lin, Wenchuan Wu
Multilevel, multiarea, and hierarchically interconnected electrical power grids confront substantial challenges with the increasing integration of many volatile energy resources. T…
Data-driven Inverter-based Volt/VAr Control for Partially Observable Distribution Networks
Tong Xu, Wenchuan Wu, Yiwen Hong +2
For active distribution networks (ADNs) integrated with massive inverter-based energy resources, it is impractical to maintain the accurate model and deploy measurements at all nod…
A Quadratic Convex Approximation of Optimal Power Flow in Distribution System with Application in Loss Allocation
Tianshu Yang, Ye Guo, Lirong Deng +2
In this paper, a novel quadratic convex optimal power flow model, namely, MDOPF, is proposed to determine the optimal dispatches of distributed generators. Based on the results of…
A Linear Branch Flow Model for Radial Distribution Networks and its Application to Reactive Power Optimization and Network Reconfiguration
Tianshu Yang, Ye Guo, Lirong Deng +2
This paper presents a cold-start linear branch flow model named modified DistFlow. In modified DistFlow, the active and reactive power are replaced by their ratios to voltage magni…
Stochastic Flexibility Evaluation for Virtual Power Plant by Aggregating Distributed Energy Resources
Siyuan Wang, Wenchuan Wu
To manage huge amount of flexible distributed energy resources (DERs) in the distribution networks, the virtual power plant (VPP) is introduced in industry. The VPP can optimally d…
Online Multi-agent Reinforcement Learning for Decentralized Inverter-based Volt-VAR Control
Haotian Liu, Wenchuan Wu
The distributed Volt/Var control (VVC) methods have been widely studied for active distribution networks(ADNs), which is based on perfect model and real-time P2P communication. How…
Two-stage Deep Reinforcement Learning for Inverter-based Volt-VAR Control in Active Distribution Networks
Haotian Liu, Wenchuan Wu
Model-based Vol/VAR optimization method is widely used to eliminate voltage violations and reduce network losses. However, the parameters of active distribution networks(ADNs) are…
Linear Programming Contractor for Interval Distribution State Estimation Using RDM Arithmetic
VietCuong Ngo, Wenchuan Wu
State estimation (SE) of distribution networks heavily relies on pseudo measurements that introduce significant errors, since real-time measurements are insufficient. Interval SE m…