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A classification control strategy for energy storage system in microgrid
Author(s) -
Zeng Aidong,
Xu Qingshan,
Ding Maosheng,
Yukita Kazuto,
Ichiyanagi Katsuhiro
Publication year - 2015
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.22099
Subject(s) - microgrid , reliability (semiconductor) , reliability engineering , energy storage , power (physics) , computer data storage , control (management) , stability (learning theory) , computer science , distributed generation , engineering , control engineering , automotive engineering , renewable energy , electrical engineering , physics , quantum mechanics , artificial intelligence , machine learning , operating system
Storage devices are indispensable elements in a microgrid to compensate for the power imbalance between loads and the distributed generator (DG) output. Different storage strategies give diverse performances in adjustment speed and capacity. Based on the performance of different storage devices and the features of power imbalance curve in different periods, a classification control strategy is proposed in this paper. First, storage devices are given priorities according to the adjusting speed, and the power imbalance curve is divided into two periods according to the changing speed. During an emergency, all the storages are employed to compensate the rapidly increasing power imbalance; during the steady period, storage device with higher priority is employed to track the instantaneous component of power imbalance, while storage device with lower priority is used to replace the kWh output of higher priority storage. The proposed strategy is tested in a microgrid within the subdistribution network of IEEE RBTS Bus6 system using Monte Carlo methods. Simulation results indicate that the classification control strategy could endow the system with fast adjusting ability through coordination between storages. Reliability indices of the testing system are utilized to demonstrate that the classification control strategy could improve the stability of the microgrid and reliability of the distribution network. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.