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混合储能系统快速功率响应模型预测控制

Translated title of the contribution: Fast-power-response model predictive control for hybrid energy storage systems
  • School of Electrical Engineering and Automation, Harbin Institute of Technology
  • State Key Laboratory of Low-carbon Thermal Power Generation Technology and Equipment

Research output: Contribution to journalArticlepeer-review

Abstract

In order to address issues such as slow control response speed and unreasonable energy storage power distribution in the process of hybrid energy storage system stabilizing DC bus voltage fluctuation caused by high-power load mutation of microgrid, a fast power response model predictive control for hybrid energy storage systems was proposed. Firstly, according to the predicted current value of the energy storage system and the system power compensation amount, the predicted power of the energy storage system was obtained and used as the reference power. The power configuration scheme based on rational function fitting was designed to optimize the reference power to obtain the reference power of lithium battery energy storage and flywheel energy storage. In the method, the maximum utilization of the capacity of the flywheel energy storage system was realized, and the influence of the sudden power was reduced on the battery and prolongs the service life of the battery. Secondly, the reference current value was obtained through the power-current transformation relationship of the energy storage system, and the incremental model predictive control algorithm was used to unify the control of the lithium-flywheel energy storage system to obtain the optimal control output, ensuring that the actual current quickly follows the reference current to suppress DC bus voltage fluctuations. Finally, effectiveness and practicability of the proposed control strategy are verified by simulation and hardware-in-the-loop semi-physical simulation.

Translated title of the contributionFast-power-response model predictive control for hybrid energy storage systems
Original languageChinese (Traditional)
Pages (from-to)22-35
Number of pages14
JournalDianji yu Kongzhi Xuebao/Electric Machines and Control
Volume28
Issue number9
DOIs
StatePublished - Sep 2024
Externally publishedYes

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