High-gain observer-based sensorless control of a flywheel energy storage system for integration with a grid-connected variable-speed wind generator

Mansour, M.M.; Said, Salim Hadj; Bendoukha, Samir; Berrayana, W.; Mansouri, Mohamed; Mimouni, Mohamed Faouzi

doi:10.1007/s00500-019-04564-5

Cited by 2 publications

(1 citation statement)

References 32 publications

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“…Therefore, most of them will improve SMO, mainly using other functions to replace the symbolic function. For example, the combination of hyperbolic tangent function, sigmoid function, Gaussian error function and saturation function [39][40][41][42] .…”

Section: Sensor-less Controlmentioning

confidence: 99%

Control technology and development status of flywheel energy storage system

Jia

Zhang

et al. 2022

ITM Web Conf.

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Flywheel energy storage technology has attracted more and more attention in the energy storage industry due to its high energy density, fast charge and discharge speed, long service life, clean and pollution-free characteristics. It is wwidely used in uninterruptible power system, grid frequency modulation, energy recovery and reuse and other fields. With the development of flywheel rotor materials, motors, bearings and control technology, flywheel energy storage technology has been greatly developed. Introducing the basic structure of the flywheel energy storage system in the above three applications. Typical charge-discharge control strategies are given for the three sensor-less algorithms of model reference adaptive control, sliding mode observer andextended Kalman filter, which are suitable for flywheel energy storage devices.

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Section: Sensor-less Controlmentioning

confidence: 99%

Control technology and development status of flywheel energy storage system

Jia

Zhang

et al. 2022

ITM Web Conf.

View full text Add to dashboard Cite

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Control Strategy of Flywheel Energy Storage System for Improved Model Reference Adaptive System Based on Tent-Sparrow Search Algorithm

Song,

Wu,

Zheng

et al. 2024

Electronics

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This study addresses speed sensor aging and electrical parameter variations caused by prolonged operation and environmental factors in flywheel energy storage systems (FESSs). A model reference adaptive system (MRAS) flywheel speed observer with parameter identification capabilities is proposed to replace traditional speed sensors. The proposed method uses reference and adjustable models to identify the stator resistance and permanent magnet flux (PM Flux) to mitigate the adverse effects of electrical parameter changes on control performance. The Tent chaotic mapping-improved Sparrow Search Algorithm (SSA) optimizes the Proportional-Integral (PI) controller parameters for the dual closed-loop and MRAS speed adaptation laws of the flywheel motor. Moreover, a self-switching parameter identification (SSPI) scheme, which constructs a cost function based on the current, parameter identification, and speed errors, is proposed to prevent inaccuracies in parameter identification. The MRAS observer selects the appropriate PI adaptive mechanism based on the error values, thereby enhancing identification accuracy. Simulink simulations show significant improvements in the rapidity and accuracy of the Tent-SSA optimized MRAS flywheel speed observer, enhancing the stability and robustness of the flywheel rotor. Experimental validation on a constructed FESS platform confirms the feasibility of this method.

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High-gain observer-based sensorless control of a flywheel energy storage system for integration with a grid-connected variable-speed wind generator

Cited by 2 publications

References 32 publications

Control technology and development status of flywheel energy storage system

Control technology and development status of flywheel energy storage system

Control Strategy of Flywheel Energy Storage System for Improved Model Reference Adaptive System Based on Tent-Sparrow Search Algorithm

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