Publications

Structured Neural-PI Control with End-to-End Stability and Output Tracking Guarantees

This paper bridges the gap between neural network-based controller design and the need for performance guarantees.

Wenqi Cui, Yan Jiang, Baosen Zhang, Yuanyuan Shi

Reinforcement Learning for Optimal Frequency Control: A Lyapunov Approach

we propose to explicitly engineer the structure of neural network based controllers such that they guarantee system stability for all topologies and parameters. This is done by using a Lyapunov function to guide their structures. A recurrent neural network based reinforcement learning architecture is used to efficiently train the weights of controllers.

Wenqi Cui, Yan Jiang, Baosen Zhang

Reinforcement Learning for Optimal Frequency Control: A Lyapunov Approach

Efficient Reinforcement Learning Through Trajectory Generation

This paper proposes a trajectory generation algorithm, which adaptively generates new trajectories as if the system is being operated and explored under the updated control policies.

Wenqi Cui, Linbin Huang, Weiwei Yang, Baosen Zhang

Equilibrium-Independent Stability Analysis for Distribution Systems with Lossy Transmission Lines

This paper proposes a novel equilibrium-independent transient stability analysis of distribution systems with lossy lines.

Wenqi Cui, Baosen Zhang

Stable Reinforcement Learning for Optimal Frequency Control: A Distributed Averaging-Based Integral Approach

This paper aims to leverage nonlinear optimal controllers to simultaneously achieve optimal transient frequency control and find the most economic power dispatch for frequency restoration.

Yan Jiang, Wenqi Cui, Baosen Zhang, Jorge Cortés

Structured Neural-PI Control for Networked Systems: Stability and Steady-State Optimality Guarantees

This paper bridges the gap between neural network-based controller design and the need for performance guarantees.

Wenqi Cui, Yan Jiang, Baosen Zhang, Yuanyuan Shi

Decentralized Safe Reinforcement Learning for Voltage Control

This paper proposes a decentralized safe learning approach for voltage control.

Wenqi Cui, Jiayi Li, Baosen Zhang

Review of Market Power Assessment and Mitigation In the Reshaping of Power Systems: State-of-Art Status and Potential Research Studies

Deregulation of the power industry requires avoiding market power abuse for maintaining market competitiveness. To this end, a sequence …

Nan Shang, Yi Ding, Wenqi Cui

Design of a Graphical User Interface for Few-Shot Machine Learning Classification of Electron Microscopy Data

The recent growth in data volumes produced by modern electron microscopes requires rapid, scalable, and flexible approaches to image segmentation and analysis. Few-shot machine learning, which can richly classify images from a handful of user-provided examples, is a promising route to high-throughput analysis. However, current command-line implementations of such approaches can be slow and unintuitive to use, lacking the real-time feedback necessary to perform effective classification. Here we report on the development of a Python-based graphical user interface that enables end users to easily conduct and visualize the output of few-shot learning models. This interface is lightweight and can be hosted locally or on the web, providing the opportunity to reproducibly conduct, share, and crowd-source few-shot analyses.

Christina Doty, Shaun Gallagher, Wenqi Cui, Wenya Chen, Shweta Bhushan, Marjolein Oostrom, Sarah Akers, Steven R. Spurgeon

Predicting Power System Dynamics and Transients: A Frequency Domain Approach

This paper proposes a decentralized safe learning approach for voltage control.

Wenqi Cui, Weiwei Yang, Baosen Zhang

Lyapunov-Regularized Reinforcement Learning for Power System Transient Stability

This paper proposes a Lyapunov regularized RL approach for optimal frequency control for transient stability in lossy networks.

Wenqi Cui, Baosen Zhang

Multi-state operating reserve model of aggregate thermostatically-controlled-loads for power system short-term reliability evaluation

Thermostatically-controlled-loads (TCLs) have been regarded as a good candidate for maintaining the power system reliability by …

Yi Ding, Wenqi Cui

Evaluation and sequential dispatch of operating reserve provided by air conditioners considering lead–lag rebound effect

Air conditioners (ACs) are widely considered as good candidates to provide operating reserve. Demand response rebound, i.e., the …

Wenqi Cui, Yi Ding

Design of capacity incentive and energy compensation for demand response programs

Variability and Uncertainties caused by renewable energy sources have called for large amount of balancing services. Demand side …

Zhoubin Liu, Wenqi Cui

Two-stage payback model for the assessment of curtailment services provided by air conditioners

Demand-side resources (DSRs) show great potential to help maintain the real-time balance of power system through demand response (DR) …

Wenqi Cui, Yi Ding