activity
20182024
most citedOptimal Scheduling of Integrated Demand Response-Enabled Integrated Energy Systems with Uncertain Renewable Generations: A Stackelberg Game Approach

322 citations · 729 across the 6 of their papers we have counts for

collaborators

7 papers

eess.SY2024★ 26 cited

Physical Informed-Inspired Deep Reinforcement Learning Based Bi-Level Programming for Microgrid Scheduling

Yang Li, Jiankai Gao, Yuanzheng Li +4

To coordinate the interests of operator and users in a microgrid under complex and changeable operating conditions, this paper proposes a microgrid scheduling model considering the…

eess.SY2021★ 3 cited

Boost Distribution System Restoration with Emergency Communication Vehicles Considering Cyber-Physical Interdependence

Zhigang Ye, Chen Chen, Ruihuan Liu +5

Enhancing restoration capabilities of distribution systems is one of the main strategies for resilient power systems to cope with extreme events. However, most of the existing stud…

eess.SP2021★ 322 cited

Optimal Scheduling of Integrated Demand Response-Enabled Integrated Energy Systems with Uncertain Renewable Generations: A Stackelberg Game Approach

Yang Li, Chunling Wang, Guoqing Li +1

In order to balance the interests of integrated energy operator (IEO) and users, a novel Stackelberg game-based optimization framework is proposed for the optimal scheduling of int…

eess.SY2020

Robust Trajectory-Constrained Frequency Control for Microgrids Considering Model Linearization Error

Yichen Zhang, Chen Chen, Tianqi Hong +3

The capability to switch between grid-connected and islanded modes has promoted adoption of microgrid technology for powering remote locations. Stabilizing frequency during the isl…

eess.SY2020★ 293 cited

Improving operational flexibility of integrated energy system with uncertain renewable generations considering thermal inertia of buildings

Yang Li, Chunling Wang, Guoqing Li +3

Insufficient flexibility in system operation caused by traditional "heat-set" operating modes of combined heat and power (CHP) units in winter heating periods is a key issue that l…

eess.SY2020★ 74 cited

Approximating Trajectory Constraints with Machine Learning -- Microgrid Islanding with Frequency Constraints

Yichen Zhang, Chen Chen, Guodong Liu +2

In this paper, we introduce a deep learning aided constraint encoding method to tackle the frequency-constraint microgrid scheduling problem. The nonlinear function between system…