1 citations · 1 across the 7 of their papers we have counts for
7 papers
Artificial Intelligence for Power-Converter-Rich Electrical Systems: A Review
Pengfeng Lin, Yuan Gao, Yuxi Tang +8
Power-converter-rich electrical systems, formed by renewable generation, electrified transportation, and inverter-based resources, exhibit strongly nonlinear dynamics, multi-physic…
Coordinated Optimal Power Quality Management in Distribution Systems Using The Residual Capacity of Community IBRs
Tiantian Ji, Pengfeng Lin, Miao Zhu +3
This letter proposes a network-wide coordinated optimization model to mitigate voltage unbalance (VU) by unleashing the remaining capacity of community inverter-based resources (IB…
Collaborative Optimization Framework of Battery Charging / Swapping Stations for eVTOLs Based on Closed-Loop Supply Chain and Space-Time Network
Pengfeng Lin, Miao Zhu, Jiahui Sun +3
Electric vertical take-off and landing (eVTOL) aircraft, by virtue of their advantages such as high efficiency, environmental friendliness, and low noise, are regarded as an effect…
Full-Time-Scale Power Management Strategy for Hybrid AC/DC/DS Microgrid with Dynamic Concatenation and Autonomous Frequency / Voltage Restorations
Qingzuo Meng, Pengfeng Lin, Yujie Wang +4
Hybrid AC/DC microgrids with distributed energy storage (DS) improve power reliability in remote areas. Existing power management methods either focus on steady-state power sharing…
Transient Power Allocation Control Scheme for Hybrid Hydrogen Electrolyzer-Supercapacitor System with Autonomous Inertia Response
Pengfeng Lin, Guangjie Gao, Jianjun Ma +3
This paper proposes a hybrid hydrogen electrolyzer-supercapacitor system (HESS) with a novel control strategy for renewable-dominant power grids. The HESS consists of alkaline elec…
GenControl: Generative AI-Driven Autonomous Design of Control Algorithms
Chenggang Cui, Jiaming Liu, Peifeng Hui +2
Designing controllers for complex industrial electronic systems is challenging due to nonlinearities and parameter uncertainties, and traditional methods are often slow and costly.…
On Physics-Informed Neural Network Control for Power Electronics
Peifeng Hui, Chenggang Cui, Pengfeng Lin +3
Considering the growing necessity for precise modeling of power electronics amidst operational and environmental uncertainties, this paper introduces an innovative methodology that…