Multiple hydrogen-based hybrid storage systems operation for microgrids: A combined TOPSIS and model predictive control methodology

被引:43
作者
Li, Bei [1 ]
Miao, Hongzhi [2 ]
Li, Jiangchen [3 ]
机构
[1] Shenzhen Univ, Coll Chem & Environm Engn, Shenzhen 518060, Peoples R China
[2] Dalian Maritime Univ, Coll Transportat Engn, Dalian 116026, Peoples R China
[3] Univ Alberta, Dept Civil & Environm Engn, Edmonton, AB T6G 1H9, Canada
关键词
Microgrid; Hydrogen storage system; Two-dimension model; TOPSIS; Allocating-and-dispatching; Model predictive control; ENERGY MANAGEMENT STRATEGIES; OPTIMIZATION; POWER;
D O I
10.1016/j.apenergy.2020.116303
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
Hydrogen-based hybrid storage system has a high energy density, which can operate as the long-term storage system, and play an important role in future smart cities. In the hydrogen storage system, fuel cell, hydrogen tanks, and electrolyzer are often combined together and operating with complex electrochemical reactions. How to efficiently operate the hydrogen storage system and considering the convoluted electrochemical reactions is a problem. In addition, multiple hydrogen storage systems are often grouped together to supply the demands. Thus, cooperating the dispatching of these storage systems is another complicated problem. In this paper, we first present a two-dimension model considering temperature influences for hydrogen based microgrid, where a regression method is adopted. Moreover, a combined allocating-and-dispatching methodology involving two layers is proposed to cooperate the multiple storage systems. Specifically, both TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) and fuzzy logic are adopted as the first-layer allocating algorithm. Then, the model predictive control (MPC) is utilized as the second-layer dispatching algorithm. Based on the combined method, power is firstly allocated to hybrid storage system considering each hybrid storage system health conditions, and secondly scheduled to battery storage and hydrogen storage based on MPC method. The simulation results showed that with the combined Dematel-TOPSIS and MPC algorithm, the degradation index and operation cost were the smallest among three algorithms, and can further extend the lifetime of hybrid hydrogen storage systems in microgrids.
引用
收藏
页数:14
相关论文
共 40 条
[31]   Simultaneous optimization of sizing and energy management-Application to hybrid train [J].
Poline, Marie ;
Gerbaud, Laurent ;
Pouget, Julien ;
Chauvet, Frederic .
MATHEMATICS AND COMPUTERS IN SIMULATION, 2019, 158 :355-374
[32]   Hierarchical energy management control for islanding DC microgrid with electric-hydrogen hybrid storage system [J].
Pu, Yuchen ;
Li, Qi ;
Chen, Weirong ;
Liu, Hong .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2019, 44 (11) :5153-5161
[33]   Energy and cost analysis of a solar-hydrogen combined heat and power system for remote power supply using a computer simulation [J].
Shabani, Bahman ;
Andrews, John ;
Watkins, Simon .
SOLAR ENERGY, 2010, 84 (01) :144-155
[34]   A data-driven robust optimization approach to scenario-based stochastic model predictive control [J].
Shang, Chao ;
You, Fengqi .
JOURNAL OF PROCESS CONTROL, 2019, 75 :24-39
[35]   Energy management strategies comparison for electric vehicles with hybrid energy storage system [J].
Song, Ziyou ;
Hofmann, Heath ;
Li, Jianqiu ;
Hou, Jun ;
Han, Xuebing ;
Ouyang, Minggao .
APPLIED ENERGY, 2014, 134 :321-331
[36]   Modeling of advanced alkaline electrolyzers: a system simulation approach [J].
Ulleberg, O .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2003, 28 (01) :21-33
[37]   Assessment of economic and environmental energy performance of EU countries using CV-TOPSIS technique [J].
Vavrek, Roman ;
Chovancova, Jana .
ECOLOGICAL INDICATORS, 2019, 106
[38]  
Wei Q, IEEE T IND ELECT, V62, P4203
[39]   Adaptive power allocation using artificial potential field with compensator for hybrid energy storage systems in electric vehicles [J].
Wu, Yue ;
Huang, Zhiwu ;
Liao, Hongtao ;
Chen, Bin ;
Zhang, Xiaoyong ;
Zhou, Yanhui ;
Liu, Yongjie ;
Li, Heng ;
Peng, Jun .
APPLIED ENERGY, 2020, 257 (257)
[40]   Composite Energy Storage System Involving Battery and Ultracapacitor With Dynamic Energy Management in Microgrid Applications [J].
Zhou, Haihua ;
Bhattacharya, Tanmoy ;
Tran, Duong ;
Siew, Tuck Sing Terence ;
Khambadkone, Ashwin M. .
IEEE TRANSACTIONS ON POWER ELECTRONICS, 2011, 26 (03) :923-930