Robust Optimal Frequency Response Enhancement Using Energy Storage-Based Grid-Forming Converters

Sharara Rehimi, Hassan Bevrani (), Hadi Tarimoradi, Chiyori T. Urabe, Takeyoshi Kato () and Toshiji Kato
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Sharara Rehimi: Department of Electrical Engineering, Graduate School of Engineering, Nagoya University, Nagoya 464-0814, Japan
Hassan Bevrani: Smart/Micro Grids Research Center, Department of Electrical Engineering, University of Kurdistan, Sanandaj 1517566177, Iran
Hadi Tarimoradi: Smart/Micro Grids Research Center, Department of Electrical Engineering, University of Kurdistan, Sanandaj 1517566177, Iran
Chiyori T. Urabe: Department of Electrical Engineering, Graduate School of Engineering, Nagoya University, Nagoya 464-0814, Japan
Takeyoshi Kato: Department of Electrical Engineering, Graduate School of Engineering, Nagoya University, Nagoya 464-0814, Japan
Toshiji Kato: Department of Electrical Engineering, Graduate School of Engineering, Doshisha University, Kyoto 610-0321, Japan

Energies, 2024, vol. 17, issue 19, 1-19

Abstract: To enhance frequency and active power control performance, this research proposes a decentralized robust optimal tuning approach for power grid frequency regulation support using energy storage systems (ESSs) as the primary source of grid-forming (GFM) converters. The proposed approach employs the robust Kharitonov theory to find a family of stabilizing sets of a proportional-integral (PI)-based supplementary controller, which is used in the outer control layer of the GFM control system. A family of stabilizing parameter sets is found in the presence of system uncertainties and disturbances that are common in power grid operation. Then, using a developed Bayesian optimization algorithm, an optimal set of parameters is determined among the mentioned family member sets. The proposed sophisticated combination of a robust control theorem and an optimization algorithm provides a promising solution for the robust and optimal tuning of control system parameters in ESS-based GFM converters. The efficacy of the proposed method is demonstrated via simulation and laboratory real-time experiment results for a given detailed case study.

Keywords: energy storage systems; grid-forming converters; frequency support; robust control; Kharitonov theorem; optimal tuning; Bayesian optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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