Advanced Energy Management Strategy of Photovoltaic/PEMFC/Lithium-Ion Batteries/Supercapacitors Hybrid Renewable Power System Using White Shark Optimizer

被引:8
|
作者
Alhumade, Hesham [1 ,2 ,3 ]
Rezk, Hegazy [4 ,5 ]
Louzazni, Mohamed [6 ]
Moujdin, Iqbal Ahmed [2 ,7 ]
Al-Shahrani, Saad [1 ]
机构
[1] King Abdulaziz Univ, Fac Engn, Chem & Mat Engn Dept, Jeddah 21589, Saudi Arabia
[2] King Abdulaziz Univ, Ctr Excellence Desalinat Technol, Jeddah 21589, Saudi Arabia
[3] King Abdulaziz Univ, KA CARE Energy Res & Innovat Ctr, Jeddah 21589, Saudi Arabia
[4] Prince Sattam bin Abdulaziz Univ, Coll Engn Wadi Alddawasir, Dept Elect Engn, Wadi Alddawasir 11991, Saudi Arabia
[5] Minia Univ, Fac Engn, Dept Elect Engn, Al Minya 61519, Egypt
[6] Chouaib Doukkali Univ El Jadida, Natl Sch Appl Sci, Sci Engineer Lab Energy, El Jadida 24000, Morocco
[7] King Abdulaziz Univ, Dept Mech Engn, Jeddah 21589, Saudi Arabia
关键词
energy management systems; hydrogen fuel; renewable energy; microgrid; optimization; FUEL-CELL; ELECTRIC VEHICLE; BATTERY; MODEL; HEVS;
D O I
10.3390/s23031534
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The slow dynamic response of a proton exchange membrane fuel cell (PEMFC) to high load change during deficit periods must be considered. Therefore, integrating the hybrid system with energy storage devices like battery storage and/or a supercapacitor is necessary. To reduce the consumed hydrogen, an energy management strategy (EMS) based on the white shark optimizer (WSO) for photovoltaic/PEMFC/lithium-ion batteries/supercapacitors microgrid has been developed. The EMSs distribute the load demand among the photovoltaic, PEMFC, lithium-ion batteries, and supercapacitors. The design of EMSs must be such that it minimizes the use of hydrogen while simultaneously ensuring that each energy source performs inside its own parameters. The recommended EMS-based-WSO was evaluated in regard to other EMSs regarding hydrogen fuel consumption and effectiveness. The considered EMSs are state machine control strategy (SMCS), classical external energy maximization strategy (EEMS), and optimized EEMS-based particle swarm optimization (PSO). Thanks to the proposed EEMS-based WSO, hydrogen utilization has been reduced by 34.17%, 29.47%, and 2.1%, respectively, compared with SMCS, EEMS, and PSO. In addition, the efficiency increased by 6.05%, 9.5%, and 0.33%, respectively, compared with SMCS, EEMS, and PSO.
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页数:17
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