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

Haitham S. Ramadan; Hassan Haes Alhelou; Abdelsalam A. Ahmed

doi:10.1049/rpg2.12423

journal article Open Access Feb 18, 2022

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

Haitham S. Ramadan Hassan Haes Alhelou

Abdelsalam A. Ahmed

IET Renewable Power Generation Vol. 19 No. 1 · Institution of Engineering and Technology (IET)

View at Publisher Save 10.1049/rpg2.12423

Abstract

Abstract
The balance of renewable‐energy‐based power systems has witnessed significant importance particularly with their rapid integration within these systems. The optimal sizing and control of energy storage systems (ESS) in hybrid power systems (HPSs) based on renewable energy becomes of particular interest. In this research, the HPS under study comprises PV, wind, and energy storage system. Two battery technologies, lead acid (LA) and lithium‐Ion (LI)—are conducted to reach a near‐optimal solution via metaheuristic optimization algorithms in HPS. This paper aims at reaching the equilibrium of the generation consumption for HPS through applying a novel technique, grey wolf optimization (GWO) through the optimal battery sizing of the HPS. The optimization is used for reaching the due balance between the production of power and that absorbed by the load, by minimizing the difference between the final and initial state of charge. Based on numerical simulations, the two different battery technologies are considered in the sizing of the ESS using GWO approach. From the simulation results, the proposed GWO leads to more enhanced performance with LI rather than LA by 3.1% with reduced number of parallel/series cells (Np/Ns) of 240/3450 and 270/3500. Accordingly, the GWO provides an adequate dynamic controlled performance.

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Published: Feb 18, 2022
Vol/Issue: 19(1)
License: View

Authors

H

Haitham S. Ramadan

Electrical Power and Machines Department, Faculty of Engineering Zagazig University Zagazig Egypt; ISTHY Institut International sur le Stockage de l’Hydrogène Meroux‐Moval 90400 France

H

Hassan Haes Alhelou

Department of Electrical Power Engineering Tishreen University Lattakia 2230 Syria

A

Abdelsalam A. Ahmed

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

Cite This Article

Haitham S. Ramadan, Hassan Haes Alhelou, Abdelsalam A. Ahmed (2022). Impartial near‐optimal control and sizing for battery hybrid energy system balance via grey wolf optimizers: Lead acid and lithium‐ion technologies. IET Renewable Power Generation, 19(1). https://doi.org/10.1049/rpg2.12423

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

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