Development of a constraint non-causal wave energy control algorithm based on artificial intelligence
Li, L. and Gao, Y. and Ning, D.Z. and Yuan, Z.M. (2021) Development of a constraint non-causal wave energy control algorithm based on artificial intelligence. Renewable and Sustainable Energy Reviews, 138. 110519. ISSN 1879-0690 (https://doi.org/10.1016/j.rser.2020.110519)
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Abstract
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.
ORCID iDs
Li, L. ORCID: https://orcid.org/0000-0002-8528-3171, Gao, Y., Ning, D.Z. and Yuan, Z.M. ORCID: https://orcid.org/0000-0001-9908-1813;-
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Item type: Article ID code: 74653 Dates: DateEventMarch 2021Published3 November 2020Published Online27 October 2020AcceptedSubjects: Technology > Hydraulic engineering. Ocean engineering Department: Faculty of Engineering > Naval Architecture, Ocean & Marine Engineering Depositing user: Pure Administrator Date deposited: 19 Nov 2020 16:56 Last modified: 18 Dec 2024 11:01 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/74653