Teaching-Learning Optimization Based Adaptive Fuzzy Logic Controller for Frequency Control in an Autonomous Microgrid

Anil Kumar, Srikanth N V


This paper addresses teaching learning optimization based adaptive fuzzy logic controller (AFLC) for frequency control in an autonomous AC microgrid. This autonomous microgrid consists of various renewable energy sources like PV and Wind power with high degrees of nonlinearities and also with variable load disturbances which can significantly, influences the system frequency. By considering all these uncertainties, the microgrid frequency control problem faces new challenges. Controlling of microgrid in autonomous mode is becoming a difficult task than in grid connected mode. In this paper novel AFLC is proposed for secondary frequency control. In proposed controller fuzzy input and output membership functions (MFs) scaling factors are tuned in online according to operating conditions using teaching learning based optimization technique (TLBO). In present work diesel engine generator is responsible for generation-load balance (secondary frequency control) in microgrid (MG). The robustness of the proposed controller is compared with conventional PI controller, fuzzy PI controller and PSO tuned fuzzy PI controller.

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Microgrid; adaptive fuzzy logic controller; teaching learning based optimization; frequency control.

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