A resilient and intelligent multi-objective energy management for a hydrogen-battery hybrid energy storage system based on MFO technique

M.H. Elkholy, Tomonobu Senjyu, Hamid Metwally, M.A. Farahat, Ahmad Shah Irshad, Ashraf M. Hemeida and Mohammed Elsayed Lotfy

Renewable Energy, 2024, vol. 222, issue C

Abstract: In this paper, a new design and flexible energy management strategy are presented for microgrids. The proposed intelligent energy management system (IEMS) achieves effective integration between the resilient microcontroller, chosen for its rapid response speed and its capability to perform multiple operations simultaneously, and the optimization techniques to enhance the power quality. The IEMS is designed using the FPGA board, chosen for its flexibility and capability to handle multiple and complex operations simultaneously. The experimental testing of the IEMS demonstrates a significant level of effectiveness in managing energy. To enhance system performance and ensure cost-effective reliability, advanced optimization techniques are employed. This study deals with a complex multi-objective optimization problem involving the limitations of energy generation, load demand, and a hydrogen-battery hybrid energy storage system. The moth-flame optimization (MFO) algorithm is chosen to solve this optimization problem due to its rapid convergence rate and accuracy. The effectiveness of the MFO algorithm is assessed by comparing it with several new algorithms. The obtained results show the robust performance of the IEMS and its high responsiveness to dynamic operational scenarios. It can observe, gather, and analyze data in real-time. It achieves a remarkable 1.287 % reduction in operating costs within a short timeframe.

Keywords: Hydrogen-battery hybrid energy storage system; Moth-flame Optimization; Operating reserve; Field Programmable Gate Array; Backup energy management system (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:222:y:2024:i:c:s096014812301683x

DOI: 10.1016/j.renene.2023.119768

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