Development of a constraint non-causal wave energy control algorithm based on artificial intelligence

RENEWABLE & SUSTAINABLE ENERGY REVIEWS

卷:138

Article

Li, L.¹  Gao, Y.^1,2  Ning, D. Z.³  Yuan, Z. M.¹ 

[1] Univ Strathclyde, Dept Naval Architecture Ocean & Marine Engn, Glasgow G4 0LZ, Lanark, Scotland

[2] Tianjin Univ, State Key Lab Hydraul Engn Simulat & Safety, Tianjin 300072, Peoples R China

[3] Dalian Univ Technol, State Key Lab Coastal & Offshore Engn, Dalian 116024, Peoples R China

关键词: Wave energy control;    Non-causality;    Wave force prediction;    Artificial intelligence;    Power extraction;    Control constraint;   

DOI  :  10.1016/j.rser.2020.110519

来源: Elsevier

【 摘 要 】

The real-time implementation of wave energy control leads to non-causality as the wave load that comes in the next few seconds is used to optimize the control command. The present work tackles non-causality through online forecasting of future wave force using artificial intelligence technique. The past free surface elevation is used to forecast the incoming wave load. A feedforward artificial neural network is developed for the forecasting, which learns to establish the intrinsic link between past free surface elevation and future wave force through machine learning algorithm. With the implementation of the developed online wave force prediction algorithm, a real-time discrete control algorithm taking constraint on response amplitude into account is developed and implemented to a bi-oscillator wave energy converter in the present research. The dynamic response and the wave power extraction are simulated using a state-space hydrodynamic model. It is shown that the developed real-time control algorithm enhances the power capture substantially whereas the motion of the system is hardly increased. The prediction error effect on power extraction is investigated. The reduction of power extraction is mainly caused by phase error, whilst the amplitude error has minimal influence. A link between the power capture efficiency and the constraint on control is also identified.

【 授权许可】

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