New Intelligent Control Strategy Hybrid Grey–RCMAC Algorithm for Ocean Wave Power Generation Systems

Kai-Hung Lu, Chih-Ming Hong, Zhigang Han and Lei Yu
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Kai-Hung Lu: School of Electronic and Electrical Engineering, Minnan University of Science and Technology, Quanzhou 362700, China
Chih-Ming Hong: Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan
Zhigang Han: School of Electronic and Electrical Engineering, Minnan University of Science and Technology, Quanzhou 362700, China
Lei Yu: School of Electronic and Electrical Engineering, Minnan University of Science and Technology, Quanzhou 362700, China

Energies, 2020, vol. 13, issue 1, 1-21

Abstract: In this article, the characteristics of the wave energy converter are considered and a novel dynamic controller (NDC) for a permanent magnet synchronous generator (PMSG) is proposed for Wells turbine applications. The proposed NDC includes a recursive cerebellum model articulation controller (RCMAC) with a grey predictor and innovative particle swarm optimization (IPSO). IPSO is developed to adjust the learning speed and improve learning capability. Based on the supervised learning method, online adjustment law of RCMAC parameters is derived to ensure the system’s stability. The NDC scheme is designed to maintain a supply–demand balance between intermittent power generation and grid power supply. The proposed NDC exhibits an improved power regulation and dynamic performance of the wave energy system under various operation conditions. Furthermore, better results are obtained when the RCMAC is used with the grey predictive model method.

Keywords: recurrent cerebellar model articulation controller; grey predictor; innovative particle swarm optimization; ocean wave energy; permanent magnet synchronous generator (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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