10 citations · 23 across the 19 of their papers we have counts for
19 papers
Analytical Power-Aware Provisioning for Prefill-Decode Disaggregated AI Inference
Mingyuan Yan, Haiyu Wang, Linxuan Biao +3
Power availability increasingly constrains the operation of AI inference fleets, creating a need for provisioning methods that jointly consider serving capacity and power consumpti…
Measured Joules, Learned Routes: Learning to Route for Energy-Efficient LLM Serving
Muhammad Abdur Rab Siddiqui, Daniela Rojas, Chen Yang +3
Large language models (LLMs) and agentic AI systems are creating rapidly growing inference energy demands as model sizes grow and reasoning trajectories extend. While in practice,…
Switching-Reference Voltage Control for Distribution Systems with AI-Training Data Centers
Mingyuan Yan, Trager Joswig-Jones, Baosen Zhang +2
Large-scale AI training workloads in data centers exhibit rapid and periodic power swings that can induce voltage deviations in power distribution systems. Existing voltage control…
Leveraging Predictions in Power System Voltage Control: An Adaptive Approach
Wenqi Cui, Yiheng Xie, Steven Low +2
High variability of solar PV and sudden changes in load (e.g., electric vehicles and storage) can lead to large voltage fluctuations in the distribution system. In recent years, a…
Fast and Reliable Contingency Screening with Input-Convex Neural Networks
Nicolas Christianson, Wenqi Cui, Steven Low +2
Power system operators must ensure that dispatch decisions remain feasible in case of grid outages or contingencies to prevent cascading failures and ensure reliable operation. How…
Online Event-Triggered Switching for Frequency Control in Power Grids with Variable Inertia
Jie Feng, Wenqi Cui, Jorge Cortés +1
The increasing integration of renewable energy resources into power grids has led to time-varying system inertia and consequent degradation in frequency dynamics. A promising solut…
Structured Neural-PI Control with End-to-End Stability and Output Tracking Guarantees
Wenqi Cui, Yan Jiang, Baosen Zhang +1
We study the optimal control of multiple-input and multiple-output dynamical systems via the design of neural network-based controllers with stability and output tracking guarantee…
Leveraging Predictions in Power System Frequency Control: an Adaptive Approach
Wenqi Cui, Guanya Shi, Yuanyuan Shi +1
Ensuring the frequency stability of electric grids with increasing renewable resources is a key problem in power system operations. In recent years, a number of advanced controller…
Equilibria of Fully Decentralized Learning in Networked Systems
Yan Jiang, Wenqi Cui, Baosen Zhang +1
Existing settings of decentralized learning either require players to have full information or the system to have certain special structure that may be hard to check and hinder the…
Bridging Transient and Steady-State Performance in Voltage Control: A Reinforcement Learning Approach with Safe Gradient Flow
Jie Feng, Wenqi Cui, Jorge Cortés +1
Deep reinforcement learning approaches are becoming appealing for the design of nonlinear controllers for voltage control problems, but the lack of stability guarantees hinders the…
Efficient Reinforcement Learning Through Trajectory Generation
Wenqi Cui, Linbin Huang, Weiwei Yang +1
A key barrier to using reinforcement learning (RL) in many real-world applications is the requirement of a large number of system interactions to learn a good control policy. Off-p…
Structured Neural-PI Control for Networked Systems: Stability and Steady-State Optimality Guarantees
Wenqi Cui, Yan Jiang, Baosen Zhang +1
We study the control of networked systems with the goal of optimizing both transient and steady-state performances while providing stability guarantees. Linear proportional-integra…
Stable Reinforcement Learning for Optimal Frequency Control: A Distributed Averaging-Based Integral Approach
Yan Jiang, Wenqi Cui, Baosen Zhang +1
Frequency control plays a pivotal role in reliable power system operations. It is conventionally performed in a hierarchical way that first rapidly stabilizes the frequency deviati…
Equilibrium-Independent Stability Analysis for Distribution Systems with Lossy Transmission Lines
Wenqi Cui, Baosen Zhang
Power distribution systems are becoming much more active with increased penetration of distributed energy resources. Because of the intermittent nature of these resources, the stab…
A Frequency Domain Approach to Predict Power System Transients
Wenqi Cui, Weiwei Yang, Baosen Zhang
The dynamics of power grids are governed by a large number of nonlinear differential and algebraic equations (DAEs). To safely operate the system, operators need to check that the…
Decentralized Safe Reinforcement Learning for Voltage Control
Wenqi Cui, Jiayi Li, Baosen Zhang
Inverter-based distributed energy resources provide the possibility for fast time-scale voltage control by quickly adjusting their reactive power. The power-electronic interfaces a…
Lyapunov-Regularized Reinforcement Learning for Power System Transient Stability
Wenqi Cui, Baosen Zhang
Transient stability of power systems is becoming increasingly important because of the growing integration of renewable resources. These resources lead to a reduction in mechanical…
Reinforcement Learning for Optimal Primary Frequency Control: A Lyapunov Approach
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. A common ap…
Multi-state Operating Reserve Model of Aggregate Thermostatically-Controlled-Loads for Power System Short-Term Reliability Evaluation
Yi Ding, Wenqi Cui, Shujun Zhang +3
Thermostatically-controlled-loads (TCLs) have been regarded as a good candidate for maintaining the power system reliability by providing operating reserve. The short-term reliabil…