Impartial near‐optimal control and sizing for battery hybrid energy system balance via grey wolf optimizers: Lead acid and lithium‐ion technologies-Reference-Cited by-同舟云学术

Impartial near‐optimal control and sizing for battery hybrid energy system balance via grey wolf optimizers: Lead acid and lithium‐ion technologies

Published:2022-02-18 Issue: Volume: Page:
ISSN:1752-1416
Container-title:IET Renewable Power Generation
language:en
Short-container-title:IET Renewable Power Gen

Author:

Ramadan Haitham S.¹²^ORCID,Haes Alhelou Hassan³^ORCID,Ahmed Abdelsalam A.⁴^ORCID

Affiliation:

1. Electrical Power and Machines Department, Faculty of Engineering Zagazig University Zagazig Egypt

2. ISTHY Institut International sur le Stockage de l’Hydrogène Meroux‐Moval 90400 France

3. Department of Electrical Power Engineering Tishreen University Lattakia 2230 Syria

4. Laboratory of Electric and Hybrid Electric Vehicles Technology Department of Electrical Power and Machines Engineering Faculty of Engineering Tanta University Tanta Egypt

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/rpg2.12423

Reference59 articles.

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3. Global Wind Statistics 2021 Global Wind Energy Council.https://gwec.net/green‐recovery‐data‐analysis/

4. Photovoltaic power systems programme annual report 2020.https://iea‐pvps.org/annual‐reports/

5. Hamza E.J.:Cοntributiοn à l'estimatiοn de l'état de santé en vue de la prédictiοn de la durée de vie utile résiduelle des batteries au lithium iοn. Αpplicatiοn : véhicules électriques Pour obtenir le diplôme de doctorat Spécialité Genie Electrique Préparée au sein de l'Université de Caen Normandie (2021)

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