The Energy Saving Technology of a Photovoltaic System's Control on the Basis of the Fuzzy Selective Neuronet

被引:0
|
作者
Engel, Ekaterina A. [1 ]
Kovalev, Igor V. [2 ]
机构
[1] Katanov State Univ Khakassia, Shetinkina 61, Abakan 655017, Russia
[2] Siberian State Aerosp Univ, Krasnoyarsky Rabochy Ave 31, Krasnoyarsk 660014, Russia
关键词
Fuzzy neural net; Neuro-evolutionary approach; Random perturbations; Photovoltaic system;
D O I
10.1007/978-3-319-41009-8_41
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents the energy saving technology of a photovoltaic system's control. Based on the photovoltaic system's state, the fuzzy selective neural net creates an effective control signal under random perturbations. The architecture of the selective neural net was evolved using a neuro-evolutionary approach. The validity and advantages of the proposed energy saving technology of a photovoltaic system's control are demonstrated using numerical simulations. The simulation results show that the proposed technology achieves real-time control speed and competitive performance, as compared to a classical control scheme with a PID controller.
引用
收藏
页码:382 / 388
页数:7
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