Design of ANFIS Controller for a DC Microgrid

被引：7

作者：

Gamage, Don ^{[1
]}

Zhang, Xibeng ^{[1
]}

Ukil, Abhisek ^{[1
]}

Wanigasekara, Chathura ^{[1
]}

Swain, Akshya ^{[1
]}

机构：

[1] Univ Auckland, Dept Elect Comp & Software Engn, Auckland, New Zealand

来源：

2020 3RD INTERNATIONAL CONFERENCE ON ENERGY, POWER AND ENVIRONMENT: TOWARDS CLEAN ENERGY TECHNOLOGIES (ICEPE 2020) | 2021年

关键词：

Adaptive Neuro-Fuzzy Inference; Q-Learning; Energy Storage Systems; ENERGY MANAGEMENT;

D O I：

10.1109/ICEPE50861.2021.9404439

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：

An adaptive neuro-fuzzy inference system (ANFIS) controller is developed and presented in this study to control hybrid energy storage system (HESS) which combines the battery and super-capacitor (SC). The battery compensates the energy requirement for a longer duration while the SC limits the stress on battery caused by the power fluctuations during transient period which alternately gives longer life span for the battery while regulate the DC link voltage constant. The proposed ANFIS controller is being compared for performance with various other controllers including the reinforcement controller based on Q-learning proportional and integral (PI) controller, fuzzy controller and conventional PI controller. Further, the state of charge (SOC) of the battery and SC are monitored in order to decide the required optimal amount of power or energy for the HESS in deficit/excess modes. The results of the simulation, in different loading conditions, indicate that the ANFIS's controller performance for the DC microgrid is superior compared to others.

引用

页数：6

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