Photovoltaic System Control Model on the Basis of a Modified Fuzzy Neural Net

被引：1
|
作者：
Engel, Ekaterina A. [1 ]
Engel, Nikita E. [1 ]
机构：
[1] Katanov State Univ Khakassia, Shetinkina 61, Abakan 655017, Russia
来源：
ADVANCES IN NEURAL COMPUTATION, MACHINE LEARNING, AND COGNITIVE RESEARCH III | 2020年 / 856卷
关键词：
Modified fuzzy neural net; Random perturbations; Photovoltaic system; Maximum power point tracking;
D O I：
10.1007/978-3-030-30425-6_4
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 represents the photovoltaic system control model on the basis of a modified fuzzy neural net. Based on the photovoltaic system condition, the modified fuzzy neural net provides a maximum power point tracking under random perturbations. The architecture of the modified fuzzy neural net was evolved using a neuro-evolutionary algorithm. The validity and advantages of the proposed photovoltaic system control model on the basis of a modified fuzzy neural net are demonstrated using numerical simulations. The simulation results show that the proposed photovoltaic system control model on the basis of a modified fuzzy neural net achieves real-time control speed and competitive performance, as compared to a classical control scheme with a PID controller based on perturbation & observation, or incremental conductance algorithm.
引用
收藏
页码：45 / 52
页数：8
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