Search Results for author: Wenqi Cui

Found 9 papers, 6 papers with code

Efficient Reinforcement Learning Through Trajectory Generation

1 code implementation30 Nov 2022 Wenqi Cui, Linbin Huang, Weiwei Yang, Baosen Zhang

Off-policy and Offline RL methods have been proposed to reduce the number of interactions with the physical environment by learning control policies from historical data.

Offline RL reinforcement-learning +1

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

1 code implementation1 Jun 2022 Wenqi Cui, Yan Jiang, Baosen Zhang, Yuanyuan Shi

We explicitly characterize the stability conditions and engineer neural networks that satisfy them by design.

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

no code implementations1 May 2022 Yan Jiang, Wenqi Cui, Baosen Zhang, Jorge Cortés

Specifically, we use RL to learn a neural network-based control policy mapping from the integral variables of DAI to the controllable power injections which provides optimal transient frequency control, while DAI inherently ensures the frequency restoration and optimal economic dispatch.

reinforcement-learning reinforcement Learning

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

no code implementations9 Mar 2022 Wenqi Cui, Baosen Zhang

Because of the intermittent nature of these resources, the stability of distribution systems under large disturbances and time-varying conditions is becoming a key issue in practical operations.

A Frequency Domain Approach to Predict Power System Transients

1 code implementation1 Nov 2021 Wenqi Cui, Weiwei Yang, Baosen Zhang

System topology and fault information are encoded by taking a multi-dimensional Fourier transform, allowing us to leverage the fact that the trajectories are sparse both in time and spatial frequencies.

Numerical Integration

Decentralized Safe Reinforcement Learning for Voltage Control

no code implementations3 Oct 2021 Wenqi Cui, Jiayi Li, Baosen Zhang

We explicitly engineer the structure of neural network controllers such that they satisfy the Lipschitz constraints by design.

reinforcement-learning reinforcement Learning +1

Lyapunov-Regularized Reinforcement Learning for Power System Transient Stability

1 code implementation5 Mar 2021 Wenqi Cui, Baosen Zhang

The learned neural Lyapunov function is then utilized as a regularization to train the neural network controller by penalizing actions that violate the Lyapunov conditions.

reinforcement-learning reinforcement Learning

Reinforcement Learning for Optimal Primary Frequency Control: A Lyapunov Approach

1 code implementation11 Sep 2020 Wenqi Cui, Yan Jiang, Baosen Zhang

As more inverter-connected renewable resources are integrated into the grid, frequency stability may degrade because of the reduction in mechanical inertia and damping.

reinforcement-learning reinforcement Learning

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