首页|Fuzzy with adaptive membership function and deep learning model for frequency control in PV-based microgrid system
Fuzzy with adaptive membership function and deep learning model for frequency control in PV-based microgrid system
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NSTL
Springer Nature
Abstract The intricacy to integrate Distributed Generators is the major aspect in power systems, which balanced the power and regulated the voltage and frequency. If varied electrical motors are associated with PV, the rotor speed frequency and the pulse of the PV panel are assorted. Thus, this paper intends to propose Fuzzy with adaptive membership function and Deep learning Controller to control the frequency of rotor speed and the pulse of PV panel simultaneously for developing the power system performance. The main purpose defined in developed approach is to regulate the output waveform, thus minimizing the error amid the control and reference signal. In the proposed Fuzzy controller, the membership function is optimized by “Sorted Position based GWO (SP-GWO)”. The performances of adopted scheme are computed over varied controllers regarding switching time.
Distributed GeneratorsPhotovoltaicFuzzyReference signalGrey wolf optimization
NSTL
Springer Nature
