OPTIMAL POWER CONTROL OF RBF NEURAL NETWORK STRATEGY FOR WAVE POWER GENERATION SYSTEM BASED ON RIFE ALGORITHM

Lin Huijin; Yang Junhua; Qiu Meng; Xie Zisen; Huang Weibang

doi:10.19912/j.0254-0096.tynxb.2021-0436

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Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (10) : 364-370. DOI: 10.19912/j.0254-0096.tynxb.2021-0436

OPTIMAL POWER CONTROL OF RBF NEURAL NETWORK STRATEGY FOR WAVE POWER GENERATION SYSTEM BASED ON RIFE ALGORITHM

Lin Huijin, Yang Junhua, Qiu Meng, Xie Zisen, Huang Weibang

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Abstract

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.

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Lin Huijin, Yang Junhua, Qiu Meng, Xie Zisen, Huang Weibang. OPTIMAL POWER CONTROL OF RBF NEURAL NETWORK STRATEGY FOR WAVE POWER GENERATION SYSTEM BASED ON RIFE ALGORITHM[J]. Acta Energiae Solaris Sinica. 2022, 43(10): 364-370 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0436

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