Optimal fractional sliding mode control for the frequency stability of a hybrid industrial microgrid

Dipak R. Swain; Sunita S. Biswal; Pravat Kumar Rout; P. K. Ray; R. K. Jena; Dipak R. Swain; Sunita S. Biswal; Pravat Kumar Rout; P. K. Ray; R. K. Jena

doi:10.3934/electreng.2023002

AIMS Electronics and Electrical Engineering

2023, Volume 7, Issue 1: 14-37. doi: 10.3934/electreng.2023002

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Research article

Optimal fractional sliding mode control for the frequency stability of a hybrid industrial microgrid

1.
Department of Electrical Engineering, Odisha University of Technology and Research, Bhubaneswar, India
2.
Department of Electrical and Electronics Engineering, Siksha 'O' Anusandhan University, Bhubaneswar, India
3.
Department of Electrical Engineering, Centre for Advanced Post Graduate Studies, Rourkela, India

Received: 31 August 2022 Revised: 22 October 2022 Accepted: 04 November 2022 Published: 14 December 2022

The rising proportion of inverter-based renewable energy sources in current power systems has reduced the rotational inertia of overall microgrid systems. This may cause high-frequency fluctuations in the system leading to system instability. Several initiatives have been suggested concerning inertia emulation based on other integrated external energy sources, such as energy storage systems, to combat the ever-declining issue of inertia. Hence, to deal with the aforementioned issue, we suggest the development of an optimal fractional sliding mode control (FSMC)-based frequency stabilization strategy for an industrial hybrid microgrid. An explicit state-space industrial microgrids model comprised of several coordinated energy sources along with loads, storage systems, photovoltaic and wind farms, is considered. In addition to this, the impact of electric vehicles and batteries with adequate control of the state of charge was investigated due to their short regulation times and this helps to balance the power supply and demand that in turn brings the minimization of the frequency deviations. The performance of the FSMC controller is enhanced by setting optimal parameters by employing the tuning strategy based on an iterative teaching-learning-based optimizer (ITLBO). To justify the efficacy of the proposed controller, the simulated results were obtained under several system conditions by using a vehicle simulator in a MATLAB/Simulink environment. The results reveal the enhanced performance of the ITLBO optimized fractional sliding mode control to effectively damp the frequency oscillations and retain the frequency stability with robustness, quick damping, and reliability under different system conditions.
Citation: Dipak R. Swain, Sunita S. Biswal, Pravat Kumar Rout, P. K. Ray, R. K. Jena. Optimal fractional sliding mode control for the frequency stability of a hybrid industrial microgrid[J]. AIMS Electronics and Electrical Engineering, 2023, 7(1): 14-37. doi: 10.3934/electreng.2023002

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Abstract

The rising proportion of inverter-based renewable energy sources in current power systems has reduced the rotational inertia of overall microgrid systems. This may cause high-frequency fluctuations in the system leading to system instability. Several initiatives have been suggested concerning inertia emulation based on other integrated external energy sources, such as energy storage systems, to combat the ever-declining issue of inertia. Hence, to deal with the aforementioned issue, we suggest the development of an optimal fractional sliding mode control (FSMC)-based frequency stabilization strategy for an industrial hybrid microgrid. An explicit state-space industrial microgrids model comprised of several coordinated energy sources along with loads, storage systems, photovoltaic and wind farms, is considered. In addition to this, the impact of electric vehicles and batteries with adequate control of the state of charge was investigated due to their short regulation times and this helps to balance the power supply and demand that in turn brings the minimization of the frequency deviations. The performance of the FSMC controller is enhanced by setting optimal parameters by employing the tuning strategy based on an iterative teaching-learning-based optimizer (ITLBO). To justify the efficacy of the proposed controller, the simulated results were obtained under several system conditions by using a vehicle simulator in a MATLAB/Simulink environment. The results reveal the enhanced performance of the ITLBO optimized fractional sliding mode control to effectively damp the frequency oscillations and retain the frequency stability with robustness, quick damping, and reliability under different system conditions.

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