Model Predictive Control for Inter-Submodule State-of-Charge Balancing in Cascaded H-Bridge Converter-Based Battery Energy Storage Systems

被引:10
|
作者
Liang, Gaowen [1 ]
Rodriguez, Ezequiel [1 ]
Farivar, Glen G. [2 ]
Nunes, Enrique [3 ]
Konstantinou, Georgios [4 ]
Townsend, Christopher D. [5 ]
Leyva, Ramon [6 ]
Pou, Josep [3 ]
机构
[1] Nanyang Technol Univ, Energy Res Inst, Singapore 639798, Singapore
[2] Univ Melbourne, Dept Elect & Elect Engn, Melbourne, Vic 3010, Australia
[3] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[4] Univ New South Wales, Sch Elect Engn & Telecommun, Sydney, NSW 2052, Australia
[5] Univ Western Australia, Dept Elect Elect & Comp Engn, Crawley, WA 6009, Australia
[6] Univ Rovira i Virgili, Dept Elect Elect & Automat Engn, Tarragona 43007, Spain
基金
新加坡国家研究基金会;
关键词
Battery energy storage; cascaded H-bridge; model predictive control; optimization; state-of-charge;
D O I
10.1109/TIE.2023.3290249
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the operation of battery energy storage systems based on the cascaded H-bridge converter, it is beneficial to balance the state of charge of batteries in different submodules within the converter phase-arm. This is achieved by distributing the active power among the submodules. Although multiple methods have been proposed for this purpose, they face the challenge of rendering optimal active power distributions that maximize balancing speed while meeting power constraints in the battery energy storage system. To overcome this challenge, a model predictive control scheme is developed in this paper. The proposed method is remarkably robust against parametric uncertainties (battery voltage, capacity, etc.), as evidenced by its ability to tolerate a substantial 50% uncertainty in the parameters, resulting in a mere 0.05% steady-state error. Furthermore, because the predictive control can be executed at a low frequency, the computational burden is comparable to other existing methods.
引用
收藏
页码:5777 / 5786
页数:10
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