Energy management strategy for a novel multi-stack integrated hydrogen energy storage system based on hybrid rules and optimization

被引:3
作者
Lu, Xinyu [1 ]
Gang, Wenjie [2 ]
Cai, Shanshan [1 ]
Tu, Zhengkai [1 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Energy & Power Engn, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Environm Sci & Engn, Wuhan 430074, Peoples R China
关键词
PEMEC; PEMFC; Online parameter estimation; Voltage degradation; Q; -learning; POWER ALLOCATION METHOD; FUEL-CELL; PEMFC; ELECTROLYZER; PERFORMANCE; EFFICIENCY; ALGORITHM;
D O I
10.1016/j.apenergy.2024.125189
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
To improve the performance of off-grid energy systems, based on a novel multi-stack integrated hydrogen energy storage system, a full life cycle energy management strategy (EMS) with hybrid rules and optimization is proposed. Such a system consists of four PEMECs, four PEMFCs, and a battery pack. The proposed EMS includes online parameter estimation, rule-based primary allocation, and optimization-based secondary allocation. The power is firstly allocated among PEMEC/PEMFC stacks according to a daisy-chained rule based on high efficiency range and multi-stack voltage degradation consistency. The remaining fluctuating power is then preferentially absorbed by the battery using a Q-learning reinforcement learning algorithm. Under stochastic wind power, photovoltaic, and regular load, a comparative analysis with three common EMS validates the feasibility of the proposed EMS. Compared to Q-DC and SOC-DC, the voltage degradation of the multi-stack PEMFCs is reduced by 13.9 %, and the lifetime is improved by 17.2 % and 15.7 %, saving 1315 kg and 1190 kg of hydrogen, respectively. Compared to SOC-PDC and SOC-DC, the lifetime of the battery is improved by 18.8 % and 20.8 %, respectively. The annualized cost of system based on the proposed EMS is the smallest, with reductions of 3 %, 7.4 %, and 9.2 %, respectively.
引用
收藏
页数:18
相关论文
共 53 条
[1]   Multi-objective genetic algorithm based sizing optimization of a stand-alone wind/PV power supply system with enhanced battery/supercapacitor hybrid energy storage [J].
Abdelkader, Abbassi ;
Rabeh, Abbassi ;
Ali, Dami Mohamed ;
Mohamed, Jemli .
ENERGY, 2018, 163 :351-363
[2]   Improving fuel economy and performance of a fuel-cell hybrid electric vehicle (fuel-cell, battery, and ultra-capacitor) using optimized energy management strategy [J].
Ahmadi, Saman ;
Bathaee, S. M. T. ;
Hosseinpour, Amir H. .
ENERGY CONVERSION AND MANAGEMENT, 2018, 160 :74-84
[3]  
[Anonymous], 2019, Energy Storage Technology and Cost Characterization Report, s
[4]   Novel electrochemical and thermodynamic conditioning approaches and their evaluation for open cathode PEM-FC stacks [J].
Becker, F. ;
Cosse, C. ;
Gentner, C. ;
Schulz, D. ;
Liphardt, L. .
APPLIED ENERGY, 2024, 363
[5]   Efficient degradation prediction of PEMFCs using ELM-AE based on fuzzy extension broad learning system [J].
Deng, Zhihua ;
Chan, Siew Hwa ;
Chen, Qihong ;
Liu, Hao ;
Zhang, Liyan ;
Zhou, Keliang ;
Tong, Sirui ;
Fu, Zhichao .
APPLIED ENERGY, 2023, 331
[6]   Q-learning based energy management strategy for a hybrid multi-stack fuel cell system considering degradation [J].
Ghaderi, Razieh ;
Kandidayeni, Mohsen ;
Boulon, Loic ;
Trovao, Joao P. .
ENERGY CONVERSION AND MANAGEMENT, 2023, 293
[7]   Online Health-Conscious Energy Management Strategy for a Hybrid Multi-Stack Fuel Cell Vehicle Based on Game Theory [J].
Ghaderi, Razieh ;
Kandidayeni, Mohsen ;
Soleymani, Mehdi ;
Boulon, Loic ;
Trovao, Joao Pedro Fernandes .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (06) :5704-5714
[8]   Performance evaluation of a solid oxide fuel cell multi-stack combined heat and power system with two power distribution strategies [J].
Gong, Chengyuan ;
Luo, Xiaobing ;
Tu, Zhengkai .
ENERGY CONVERSION AND MANAGEMENT, 2022, 254
[9]   Investigation of PEM electrolyzer modeling: Electrical domain, efficiency, and specific energy consumption [J].
Hernandez-Gomez, Angel ;
Ramirez, Victor ;
Guilbert, Damien .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2020, 45 (29) :14625-14639
[10]   A novel power allocation strategy considering multi-objective comprehensive optimization for hybrid electric vehicles [J].
Hua, Zhiguang ;
Wang, Tianhong ;
Li, Xianglong ;
Zhao, Dongdong ;
Wang, Yuanlin ;
Dou, Manfeng .
ENERGY CONVERSION AND MANAGEMENT, 2023, 286