Intelligent control of PV system on the basis of the fuzzy recurrent neuronet*

19th International Scientific Conference Reshetnev Readings 2015

Engel, E.A.^1 ; Kovalev, I.V.^2 ; Engel, N.E.^3

First Russian Doctoral Degree in Computer Sciences, Katanov State University of Khakassia, Abakan, Russia^1

Second Russian Doctoral Degree in Computer Sciences, Siberian State Aerospace University, Krasnoyarsk, Russia^2

Katanov State University of Khakassia, Abakan, Russia^3

关键词: Classical control;    Competitive performance;    Maximum power point;    PV system;    Random perturbations;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/122/1/012006/pdf
DOI  :  10.1088/1757-899X/122/1/012006

来源: IOP

【 摘 要 】

This paper presents the fuzzy recurrent neuronet for PV system's control. Based on the PV system's state, the fuzzy recurrent neural net tracks the maximum power point under random perturbations. The validity and advantages of the proposed intelligent control of PV system are demonstrated by numerical simulations. The simulation results show that the proposed intelligent control of PV system achieves real-time control speed and competitive performance, as compared to a classical control scheme on the basis of the perturbation & observation algorithm.