47 citations · 204 across the 71 of their papers we have counts for
13 papers · 1 filter
Machine Learning Assisted Inertia Estimation using Ambient Measurements
Mingjian Tuo, Xingpeng Li
With the increasing penetration of converter-based renewable resources, different types of dynamics have been introduced to the power system. Due to the complexity and high order o…
Quality Analysis of Battery Degradation Models with Real Battery Aging Experiment Data
Cunzhi Zhao, Xingpeng Li, Yan Yao
The installation capacity of energy storage system, especially the battery energy storage system (BESS), has increased significantly in recent years, which is mainly applied to mit…
Annual Benefit Analysis of Integrating the Seasonal Hydrogen Storage into the Renewable Power Grids
Jin Lu, Xingpeng Li
There has been growing interest in integrating hydrogen storage into power grids with high renewable penetration levels. The economic benefits and power grid reliability are both e…
Selectively Linearized Neural Network based RoCoF-Constrained Unit Commitment in Low-Inertia Power Systems
Mingjian Tuo, Xingpeng Li
Conventional synchronous generators are gradually being replaced by inverter-based resources, such transition introduces more complicated operation conditions. And the reduction in…
Deep Learning based Security-Constrained Unit Commitment Considering Locational Frequency Stability in Low-Inertia Power Systems
Mingjian Tuo, Xingpeng Li
With the goal of electricity system decarbonization, conventional synchronous generators are gradually replaced by converter-interfaced renewable generations. Such transition is ca…
A 100% Renewable Energy System: Enabling Zero CO2 Emission Offshore Platforms
Cunzhi Zhao, Xingpeng Li
The total electricity consumption from offshore oil/gas platforms is around 16 TWh worldwide in 2019. The majority offshore platforms are powered by the diesel generators while the…
Feasibility Layer Aided Machine Learning Approach for Day-Ahead Operations
Arun Venkatesh Ramesh, Xingpeng Li
Day-ahead operations involves a complex and computationally intensive optimization process to determine the generator commitment schedule and dispatch. The optimization process is…
An Alternative Method for Solving Security-Constrained Unit Commitment with Neural Network Based Battery Degradation Model
Cunzhi Zhao, Xingpeng Li
Battery energy storage system (BESS) can effectively mitigate the uncertainty of variable renewable generation and provide flexible ancillary services. However, degradation is a ke…
Centralized Networked Micro Water-Energy Nexus with Proportional Exchange Among Participants
Jesus Silva-Rodriguez, Xingpeng Li
This paper proposes a Networked Micro Water-Energy Nexus (NetMicroWEN) capable of co-optimizing and simultaneously supplying water and energy to local consumers in nearby communiti…
The Benefits of Hydrogen Energy Transmission and Conversion Systems to the Renewable Power Grids: Day-ahead Unit Commitment
Jin Lu, Xingpeng Li
The curtailment of renewable energy is more frequently observed as the renewable penetration levels are rising rapidly in modern power systems. It is a waste of free and green rene…
Reduced Optimal Power Flow Using Graph Neural Network
Thuan Pham, Xingpeng Li
OPF problems are formulated and solved for power system operations, especially for determining generation dispatch points in real-time. For large and complex power system networks…
Resilient Operational Planning for Microgrids Against Extreme Events
Cunzhi Zhao, Jesus Silva-Rodriguez, Xingpeng Li
This paper proposes a novel resilience index, a microgrid survivability rate (SR) under extreme events, and then proposes a novel Resilient Operational Planning (ROP) algorithm to…
Microgrid Optimal Energy Scheduling Considering Neural Network based Battery Degradation
Cunzhi Zhao, Xingpeng Li
Battery energy storage system (BESS) can effec-tively mitigate the uncertainty of variable renewable generation. Degradation is unpreventable and hard to model and predict for batt…