An analysis of energy storage system interaction in a multi objective model predictive control based energy management in DC microgrid

被引:0
|
作者
Raveendran Nair, Unnikrishnan [1 ]
Costa-Castello, Ramon [1 ]
机构
[1] UPC, CSIC, Inst Robot & Informot Ind, Llorens & Artigas 4-6, Barcelona 08028, Spain
来源
2019 24TH IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA) | 2019年
关键词
model predictive control; energy management; energy storages system; degradation rate; AGING MECHANISMS; OPTIMIZATION; DEGRADATION; LIFETIME; CATALYST;
D O I
10.1109/etfa.2019.8869474
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Non-deterministic generation from renewable sources have resulted in the incorporation energy storage systems in modern grids. Management of energy between different storage elements need to done optimally to ensure efficient operation of the grid. The intraday energy management problem is addressed in this work through an online model predictive control using multi objective optimisation. This work analyses the energy interaction among different storages when penalty weights in a multi objective optimisation problem is varied, in order to find an optimal scenario in terms of weight distribution. Different scenarios are identified and performance indices are proposed to achieve the same. The work also addresses implicitly the objective of minimising rate of degradation batteries. Simulation results are presented to aid in the analysis.
引用
收藏
页码:739 / 746
页数:8
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