Optimized energy management and control strategy of photovoltaic/PEM fuel cell/batteries/supercapacitors DC microgrid system

被引:28
作者
Alharbi, Abdullah G. [1 ]
Olabi, A. G. [2 ,3 ]
Rezk, Hegazy [4 ,5 ]
Fathy, Ahmed [1 ]
Abdelkareem, Mohammad Ali [2 ,3 ,6 ]
机构
[1] Jouf Univ, Fac Engn, Elect Engn Dept, Sakaka, Saudi Arabia
[2] Univ Sharjah, Sustainable Energy & Power Syst Res Ctr, RISE, POB 27272, Sharjah, U Arab Emirates
[3] Univ Sharjah, Dept Sustainable & Renewable Energy Engn, POB 27272, Sharjah, U Arab Emirates
[4] Prince Sattam bin Abdulaziz Univ, Coll Engn Wadi Alddawasir, Dept Elect Engn, Al Kharj, Saudi Arabia
[5] Minia Univ, Fac Engn, Elect Engn Dept, Al Minya, Egypt
[6] Minia Univ, Fac Engn, Al Minya, Egypt
关键词
PEM fuel cell; Energy management; Microgrid; Optimization; PERFORMANCE; CHALLENGES; PROTECTION;
D O I
10.1016/j.energy.2023.130121
中图分类号
O414.1 [热力学];
学科分类号
摘要
The slow dynamics response of a PEMFC to high-level load variation must be solved. Consequently, it is necessary to integrate the DC microgrid with battery storage banks and ultracapacitors. To guarantee the DC microgrid components: PV array, PEMFC, battery bank, and supercapacitor work effectively; energy management strategies (EMSs) are essential. The EMS distributes the load with the PV array, PEMFC, lithium-ion battery, and supercapacitor considering high efficiency and low H2 consumption. An effective EMS using a recent Beluga Whale Optimization (BWO) was developed for sharing the load between the components of the DC microgrid. Sliding mode control (SMCS), classical equivalent consumption minimization strategy (ECMS) and other optimization algorithms such as White Shark Optimizer (WSO), Manta ray foraging optimization (MRFO), Harris Hawks Optimizer (HHO), soon eagle search (BES) and Artificial Hummingbird Algorithm (AHA) were considered for comparison with the suggested BWO. The results approved the superiority of the suggested ECMS-based BWO; the hydrogen consumption was reduced by 37.67 %, 46.4 %, 25.5 %, 32.58 %, 12.94 %, 12.1 %, and 9.67 % compared to SMCS, ECMS, WSO, MRFO, HHO, BES, and AHA, respectively. In addition, efficiency increased by 4.4 %, 13.49 %, 5.24 %, 10.51 %, 0.95 %, 4.52 %, and 0.32 % compared to SMCS, ECMS, WSO, MRFO, HHO, BES, and AHA, respectively.
引用
收藏
页数:16
相关论文
共 72 条
[1]  
[Anonymous], MICROGRIDS ACTIVE DI, DOI DOI 10.3390/EN14061595
[2]  
[Anonymous], 2022, Microgrid market - growth, Trends, COVID-19 Impact, and Forecast (2022 - 2027)
[3]  
[Anonymous], 2020, Industry bullish on Future of microgrid market over Next 10 Years
[4]   Smart Grid Technologies in Europe: An Overview [J].
Ardito, Luca ;
Procaccianti, Giuseppe ;
Menga, Giuseppe ;
Morisio, Maurizio .
ENERGIES, 2013, 6 (01) :251-281
[5]   Understanding PEM fuel cell dynamics: The reversal curve [J].
Arias, Ivonne Karina Pena ;
Trinke, Patrick ;
Hanke-Rauschenbach, Richard ;
Sundmacher, Kai .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2017, 42 (24) :15818-15827
[6]  
Asakimori K, 2014, INT TELECOM ENERGY
[7]  
Bader B, 2013, WORLD ELECT VEHICLE, P1
[8]   Hybrid renewable energy systems for renewable integration in microgrids: Influence of sizing on performance [J].
Bartolucci, Lorenzo ;
Cordiner, Stefano ;
Mulone, Vincenzo ;
Rocco, Vittorio ;
Rossi, Joao Luis .
ENERGY, 2018, 152 :744-758
[9]   Renewable source penetration and microgrids: Effects of MILP - Based control strategies [J].
Bartolucci, Lorenzo ;
Cordiner, Stefano ;
Mulone, Vincenzo ;
Rocco, Vittorio ;
Rossi, Joao Luis .
ENERGY, 2018, 152 :416-426
[10]   Systemic design and energy management of a standalone battery-less PV/Wind driven brackish water reverse osmosis desalination system [J].
Ben Ali, I. ;
Turki, M. ;
Belhadj, J. ;
Roboam, X. .
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2020, 42