Hydrogen reduction-based energy management strategy of hybrid fuel cell/PV/battery/supercapacitor renewable energy system

被引:11
|
作者
Rezk H. [1 ]
Fathy A. [2 ]
机构
[1] Department of Electrical Engineering, College of Engineering in Wadi Alddawasir, Prince Sattam bin Abdulaziz University
[2] Electrical Engineering Department, Faculty of Engineering, Jouf University, Sakaka
来源
Journal of Energy Storage | 2024年 / 86卷
关键词
Energy management; Harris hawks optimizer; Hybrid renewable system; Hydrogen reduction;
D O I
10.1016/j.est.2024.111316
中图分类号
学科分类号
摘要
Fuel cells can be used in sustainable cities for a variety of purposes, including emergency backup power systems, electric vehicle recharging, and the production of clean, efficient energy for buildings. Additionally, fuel cells can support distributed energy systems, improving energy management, and lowering dependency on conventional energy sources. However, the slow time response of proton exchange membrane fuel cell (PEMFC) during high-level load variation is an issue that needs addressing. To solve this, battery storage and supercapacitor can be integrated with a hybrid generation system including fuel cell, photovoltaic (PV). It's important to have effective energy management strategies (EMSs) to ensure the photovoltaic (PV) array, PEMFC, batteries, and supercapacitors function optimally. An EMS distributes the load demand among these components while maintaining high efficiency and low hydrogen consumption. This paper proposes an effective EMS for a hybrid generating system DC microgrid (MG) having PV, FC, battery, and SC based on recent Harris hawks optimizer (HHO) to manage the energy between the equipment while minimizing the total hydrogen consumption and enhancing the system efficiency. The research work compared several algorithms, including external energy maximization strategy (EEMS), equivalent consumption minimization strategy (ECMS), frequency decoupling and state machine control (FDSMC), proportional integral (PI), Cuckoo search (CS), and grey wolf optimizer (GWO), with the proposed HHO. The EEMS-based HHO algorithm outperformed the others resulting in 18.95 %, 38.77 %, 47.34 %, 34.43 %, 33.9 %, and 20.38 % hydrogen consumption reduction compared to PI, FDSMC, ECMS, EEMS, CS, and GWO, respectively. Moreover, efficiency improved by 7.62 %, 7.77 %, 17.15 %, 11.21 %, 2.17 %, and 5.12 % compared to PI, FDSMC, ECMS, EEMS, CS, and GWO, respectively. The obtained findings demonstrated the robustness and efficacy of the suggested HHO-EMS in obtaining the lowest hydrogen consumption of the DC microgrid that was provided. © 2024 Elsevier Ltd
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