3 citations · 3 across the 8 of their papers we have counts for
8 papers
Inference as Flexibility: Ramp Management for Transmission-Connected AI Data Centres
Zhirui Liang
The rapid growth of large AI data centres introduces new operational challenges for power systems, including rapid ramping, oscillatory load behavior, voltage fluctuations, and sup…
OpenG2G: A Simulation Platform for AI Datacenter-Grid Runtime Coordination
Jae-Won Chung, Zhirui Liang, Yanyong Mao +3
AI's growing compute demand and new datacenter buildouts present major capacity and reliability challenges for the electricity grid, leading to multi-year interconnection delays fo…
GPU-to-Grid: Voltage Regulation via GPU Utilization Control
Zhirui Liang, Jae-Won Chung, Mosharaf Chowdhury +2
While the rapid expansion of data centers poses challenges for power grids, it also offers new opportunities as flexible loads. Existing power system research often abstracts data…
Prescribing Decision Conservativeness in Two-Stage Power Markets: A Distributionally Robust End-to-End Approach
Zhirui Liang, Qi Li, Anqi Liu +1
This paper presents an end-to-end framework for calibrating wind power forecast models to minimize operational costs in two-stage power markets, where the first stage involves a di…
Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation
Zhirui Liang, Qi Li, Joshua Comden +2
Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regula…
Electricity Market-Clearing With Extreme Events
Tomas Tapia, Zhirui Liang, Charalambos Konstantinou +1
Extreme events jeopardize power network operations, causing beyond-design failures and massive supply interruptions. Existing market designs fail to internalize and systematically…
Revealing Decision Conservativeness Through Inverse Distributionally Robust Optimization
Qi Li, Zhirui Liang, Andrey Bernstein +1
This paper introduces Inverse Distributionally Robust Optimization (I-DRO) as a method to infer the conservativeness level of a decision-maker, represented by the size of a Wassers…
Multi-Objective Transmission Expansion: An Offshore Wind Power Integration Case Study
Saroj Khanal, Christoph Graf, Zhirui Liang +2
Despite ambitious offshore wind targets in the U.S. and globally, offshore grid planning guidance remains notably scarce, contrasting with well-established frameworks for onshore g…