A novel efficient adaptive-neuro fuzzy inference system control based smart grid to enhance power quality

Dharamalla Chandra Sekhar, Pokanati Veera Venkata Rama Rao, Rachamadugu Kiranmayi


A novel adaptive-neuro fuzzy inference system (ANFIS) control algorithm-based smart grid to solve power quality issues is investigated in this paper. To improve the steady-state and transient response of the solar-wind and grid integrated system proposed ANFIS controller works very well. Fuzzy maximum power point tracking (MPPT) algorithm-based DC-DC converters are utilized to extract maximum power from solar. A permanent magnet synchronous generator (PMSG) is employed to get maximum power from wind. To maximize both power generations, back-to-back voltage source converters (VSC) are operated with an intelligent ANFIS controller. Optimal power converters are adopted this proposed methodology and improved the overall performance of the system to an acceptable limit. The simulation results are obtained for a different mode of smart grid and non-linear fault conditions and the proven proposed control algorithm works well.


Adaptive-neuro fuzzy inference system controller; MATLAB/Simulink; Maximum power point tracking; power quality; PV-wind-grid integration; smart grid;

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DOI: http://doi.org/10.11591/ijece.v12i4.pp3375-3387

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578

This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).