Integrated Modeling of Power Network and Connected Flywheel Energy Storage System for Optimal Power and Energy Ratings of Flywheel

Power and energy ratings are the most important parameters of Flywheel Energy Storage System (FESS) which have a crucial influence on its dynamic performance in frequency regulation applications. In order to achieve the optimum dynamic performance of FESS, an integrated model is required which inclu...

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Bibliographic Details
Published in:IEEE transactions on energy conversion 2021-09, Vol.36 (3), p.1589-1599
Main Authors: Moghaddam, Hossein Azizi, Saeedinia, Mohammad Hosein, Mohamadian, Sobhan, Mahdavi, Mohammad Saeed, Gharehpetian, Gevork B.
Format: Article
Language:English
Subjects:
Algorithms
Dynamic response
Energy storage
Flywheel
Flywheels
Heuristic algorithms
integrated model
Linear programming
Mathematical models
Optimization
Optimization algorithms
Parameters
power and energy ratings
Power system dynamics
Power system management
Ratings
Response surface methodology
Sensitivity analysis
Taguchi method
Taguchi methods
Transfer functions
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Summary:Power and energy ratings are the most important parameters of Flywheel Energy Storage System (FESS) which have a crucial influence on its dynamic performance in frequency regulation applications. In order to achieve the optimum dynamic performance of FESS, an integrated model is required which includes key parameters of the power network and FESS. In this paper, an integrated transfer function of FESS connected to a single-bus aggregated power system is presented. The proposed model includes both power network and FESS parameters. Moreover, the model is linearized to facilitate the application of the parameter screening approach which recognizes the most influential parameters through Taguchi method. Afterwards, combined Response Surface Methodology (RSM)-GA optimization algorithm is utilized based on an accurate approximation of the system transfer function. In order to obtain FESS power and energy ratings on the basis of lowest capital price and best dynamic response objective functions, optimization algorithm is used. The simulation and experimental studies confirm the validity of the proposed modelling and optimization approach.
ISSN:0885-8969
1558-0059
DOI:10.1109/TEC.2020.3037739