Optimal power control of RBF neural network strategy for wave power generation system based on Rife algorithm

被引：0
作者：
Lin H. [1 ]
Yang J. [1 ]
Qiu M. [1 ]
Xie Z. [1 ]
Huang W. [1 ]
机构：
[1] School of Automation, Guangdong University of Technology, Guangzhou
来源：
Taiyangneng Xuebao/Acta Energiae Solaris Sinica | 2022年 / 43卷 / 10期
关键词：
Maximum power point tracing; Permanent magnet linear synchronous motor; RBF neural network; Rife algorithm; Wave power;
D O I：
10.19912/j.0254-0096.tynxb.2021-0436
中图分类号：
学科分类号：
摘要：
In order to improve the power capture efficiency of the direct-drive wave power generation system under irregular sea conditions, optimal power capture condition was constructed by establishing the hydrodynamic model and linear motor model as well as analyzing the resonance state of the analog equivalent circuit. Aiming at the problem of strong noise interference in the wave environment, the Rife algorithm was used to obtain the dominant wave excitation component, which contributes to set the equivalent damping coefficient and calculates the q-axis optimal desired current tracking value. With designing the RBF neural network PI control algorithm, both the tracking accuracy of the equivalent control current signal and the dynamic performance of the system are improved. The simulation results show that the proposed strategy has high prediction accuracy for the amplitude and frequency of the main frequency band wave signals with strong noise, good tracking effect on the expected current value, strong robustness and significant optimization effect of the output power. © 2022, Solar Energy Periodical Office Co., Ltd. All right reserved.
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页码：364 / 370
页数：6
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