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Frequency Control in a Microgrid Using Decentralized Brain Emotional Learning Based Intelligent Controllers

机译:基于分散脑情感学习的智能控制器的微电网频率控制

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Frequency control is very important in microgrids. It plays a vital role in the stability as well as the power quality of the microgrid. The Load Frequency Control (LFC) must posses disturbance rejection capabilities as well as robustness against parameter uncertainty. In this paper decentralized Brain Emotional Learning Based Intelligent Controllers (BELBIC) is proposed for the frequency control of a microgrid. BELBIC controllers have a good disturbance rejection and robustness to plant parameters’ variation, these make it an ideal controller for the frequency control of the microgrid. Decentralized BELBIC controllers are designed simultaneously for each of the Distributed Generation (DG) unit and the controllers’ parameters are obtained using Particle Swarm Optimization (PSO) based on the Integral Time Square Error (ITSE) criterion. The simulation results are compared to decentralized PID controllers as well as Fractional Order PID (FOPID) controllers which were designed using the same procedures, the results are reported and shows the superiority of using BELBIC controllers for this application.
机译:频率控制在微电网中非常重要。它在微电网的稳定性和电能质量中起着至关重要的作用。负载频率控制(LFC)必须具有抗干扰能力以及对参数不确定性的鲁棒性。本文提出了一种基于分散脑情感学习的智能控制器(BELBIC),用于微电网的频率控制。 BELBIC控制器具有良好的抗干扰能力和对工厂参数变化的鲁棒性,这使其成为微电网频率控制的理想控制器。分散式BELBIC控制器是为每个分布式发电(DG)单元同时设计的,并且控制器的参数是使用粒子群优化(PSO)根据积分时间平方误差(ITSE)准则获得的。将仿真结果与使用相同程序设计的分散PID控制器以及分数阶PID(FOPID)控制器进行了比较,报告了结果,并显示了在该应用中使用BELBIC控制器的优越性。

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