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A Generalized State Space Average Model for Parallel DC-to-DC Converters

Hasan Alrajhi*

Umm Al-Qura University, Makkah, 21955, Saudi Arabia

* Corresponding Author: Hasan Alrajhi. Email: email

Computer Systems Science and Engineering 2022, 41(2), 717-734. https://doi.org/10.32604/csse.2022.021279

Abstract

The high potentiality of integrating renewable energies, such as photovoltaic, into a modern electrical microgrid system, using DC-to-DC converters, raises some issues associated with controller loop design and system stability. The generalized state space average model (GSSAM) concept was consequently introduced to design a DC-to-DC converter controller in order to evaluate DC-to-DC converter performance and to conduct stability studies. This paper presents a GSSAM for parallel DC-to-DC converters, namely: buck, boost, and buck-boost converters. The rationale of this study is that modern electrical systems, such as DC networks, hybrid microgrids, and electric ships, are formed by parallel DC-to-DC converters with separate DC input sources. Therefore, this paper proposes a GSSAM for any number of parallel DC-to-DC converters. The proposed GSSAM is validated and investigated in a time-domain simulation environment, namely a MATLAB/SIMULINK. The study compares the steady-state, transient, and oscillatory performance of the state-space average model with a fully detailed switching model.

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APA Style
Alrajhi, H. (2022). A generalized state space average model for parallel dc-to-dc converters. Computer Systems Science and Engineering, 41(2), 717-734. https://doi.org/10.32604/csse.2022.021279
Vancouver Style
Alrajhi H. A generalized state space average model for parallel dc-to-dc converters. Comput Syst Sci Eng. 2022;41(2):717-734 https://doi.org/10.32604/csse.2022.021279
IEEE Style
H. Alrajhi, "A Generalized State Space Average Model for Parallel DC-to-DC Converters," Comput. Syst. Sci. Eng., vol. 41, no. 2, pp. 717-734. 2022. https://doi.org/10.32604/csse.2022.021279

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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