10 citations · 11 across the 3 of their papers we have counts for
4 papers
A Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction
Haizhou Liu, Xuan Zhang, Xinwei Shen +1
In a modern power system, real-time data on power generation/consumption and its relevant features are stored in various distributed parties, including household meters, transforme…
A Federated Learning Framework for Smart Grids: Securing Power Traces in Collaborative Learning
Haizhou Liu, Xuan Zhang, Xinwei Shen +1
With the deployment of smart sensors and advancements in communication technologies, big data analytics have become vastly popular in the smart grid domain, informing stakeholders…
A Data-Driven Warm Start Approach for Convex Relaxation in Optimal Gas Flow
Haizhou Liu, Lun Yang, Xinwei Shen +3
In this letter, we propose a data-driven warm start approach, empowered by artificial neural networks, to boost the efficiency of convex relaxations in optimal gas flow. Case studi…
Stochastic Unit Commitment in Electricity-Gas Coupled Integrated Energy Systems based on Modified Progressive Hedging
Haizhou Liu, Xinwei Shen, Qinglai Guo +3
The increasing number of gas-fired units has significantly intensified the coupling between power and gas networks. Traditionally, the nonlinearity and nonconvexity in gas flow equ…