Design of ANFIS Controller for a DC Microgrid

Don Gamage, Xibeng Zhang, A. Ukil, Chathura Wanigasekara, A. Swain
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引用次数: 2

Abstract

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.
直流微电网的ANFIS控制器设计
针对电池与超级电容器相结合的混合储能系统,提出了一种自适应神经模糊推理系统(ANFIS)控制器。电池补偿较长时间的能量需求,而SC则限制了暂态期间功率波动对电池造成的压力,交替地延长了电池的寿命,同时调节了直流链路电压常数。将所提出的ANFIS控制器与其他各种控制器的性能进行了比较,包括基于q -学习比例与积分(PI)控制器的强化控制器、模糊控制器和传统PI控制器。此外,监测电池和SC的充电状态(SOC),以确定HESS在亏缺/过剩模式下所需的最佳功率或能量。仿真结果表明,在不同负载条件下,ANFIS对直流微电网的控制性能优于其他控制器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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