Search Results for author: Huayi Li

Found 8 papers, 0 papers with code

Less Conservative Robust Reference Governors and Their Applications

no code implementations4 Jan 2024 Miguel Castroviejo-Fernandez, Huayi Li, Andrés Cotorruelo, Emanuele Garone, Ilya Kolmanovsky

The applications of reference governors to systems with unmeasured set-bounded disturbances can lead to conservative solutions.

Frequency support Scheme based on parametrized power curve for de-loaded Wind Turbine under various wind speed

no code implementations2 Aug 2021 Cheng Zhong, Yueming Lv, Huayi Li, Jikai Chen, Yang Li

However, for the existing frequency regulation scheme of wind turbines, the control gains in the auxiliary frequency controller are difficult to set because of the compromise of the frequency regulation performance and the stable operation of wind turbines, especially when the wind speed remains variable.

Virtual synchronous generator of PV generation without energy storage for frequency support in autonomous microgrid

no code implementations4 Jul 2021 Cheng Zhong, Huayi Li, Yang Zhou, Yueming Lv, Jikai Chen, Yang Li

PV generation reserve a part of the active power in accordance with the pre-defined power versus voltage curve.

Energy Consumption and Battery Aging Minimization Using a Q-learning Strategy for a Battery/Ultracapacitor Electric Vehicle

no code implementations27 Oct 2020 Bin Xu, Junzhe Shi, Sixu Li, Huayi Li, Zhe Wang

Then, the result from a vehicle without ultracapacitor is used as the baseline, which is compared with the results from the vehicle with ultracapacitor using Q-learning, and two heuristic methods as the energy management strategies.

energy management Management +1

Learning Time Reduction Using Warm Start Methods for a Reinforcement Learning Based Supervisory Control in Hybrid Electric Vehicle Applications

no code implementations27 Oct 2020 Bin Xu, Jun Hou, Junzhe Shi, Huayi Li, Dhruvang Rathod, Zhe Wang, Zoran Filipi

This study aims to reduce the learning iterations of Q-learning in HEV application and improve fuel consumption in initial learning phases utilizing warm start methods.

Q-Learning Reinforcement Learning (RL)

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