Proceedings of the Thirty-second (2022) International Ocean and Polar Engineering ConferenceShanghai, China, June 5–10, 2022
Copyright © 2022 by the International Society of Offshore and Polar Engineers (ISOPE)
ISBN 978-1-880653-81-4; ISSN 1098-6189

www.isope.org

Real-time Control of WECs Based on NAR,NARX and LSTM Artificial Neural Network
1

Tuo Li1, Ming Zhang2, Shuang-Rui Yu2, Zhi-Ming Yuan1,2

School of Naval Architecture and Ocean Engineering, Jiangsu University of Science and Technology,
Zhenjiang Jiangsu, China
2
Department of Naval Architecture, Ocean and Marine Engineering, University of Strathclyde,
Glasgow, UKABSTRACT

Falnes(Falnes,1995)explained the relation between wave elevation andwave excitation force is a non-linear dynamic system. Model predictivecontrol (MPC) is a method that solve a series of successive, small time
horizon, optimal control problems(Tom,2016) which requires theprediction of future wave force.The accuracy of the model of the body
dynamics strongly affect the performance of real-time control methods(Anderlini, 2017).So it is necessary that build a prediction model asaccurate as possible. A good prediction model includes not only
suitable artificial neural networks but also MPC parameters match withthe wave force prediction model. Truong(Truong,2011) has developed
a wave force prediction model based on modified grey modelMGM(1,1) for real-time control. ANN has applied to predict MPC
wave force to improve power efficiency of a heaving point absorber
WEC by Li(Li,2018). The time series of the elevation and wave
excitation force have successfully predicted by using a LSTM-

In this study, we aim to improve WECs’ performance for maximizing
energy absorption through a sub-optimal method of phase control bylatching is applied to the device.The forecasting of future wave force isrequired for the optimal control command deducted.An artificial neuralnetwork, namely LSTM (Long Short-Term Memory) is proposed toaccurately predict the short-term wave force. The hydrodynamic
properties of a point absorber is analyzed based on the 3D potential
flow theory in frequency-domain. Cummin ’ s equation and a 4th-orderstate-space model are used to efficiently represent the hydrodynamic
behavior of the WEC under irregular waves in time-domain.The
Nonlinear Autoregressive artificial neural network(NAR-ANN) andNARx network are used to verify the method proposed in this paper.
The simulation results show that the mean square error value, root
mean square error value and R2 value based on the LSTM prediction
model are better than those of the NAR prediction model. The
prediction performance of LSTM is more suitable for processing thetime series.
KEY WORDS: wave force prediction, latching control, wave energy
converter(WEC), LSTM, NAR-ANN, NARx.

NARX model to achieve more accurate WECs real-time controlby Zhang(Zhang,2020), the LSTM network is used to predict wave
elevation and wave excitation force only by output data and theNARX-ANN is used to predict wave elevation by input and output.

In section 2, a numerical time-domain model of heaving point absorberis built and expressed by state-space equation. In section 3, a real-timelatching control algorithm based on MPC is presented and give a moreinsightful understanding of chosen MPC parameters. In section 4, asimulation is conducted based on chosen WEC and MPC parameters.
The motion response of floater suggested by frequency-domainhydrodynamic analysis programme WADAM produced by DNV-GL isused to verify the WEC dynamic model. The prediction difference
between NAR and LSTM is presented by different value. The
simulation results that the MPC and prediction model parameters.

INTRODUCTION
Wave energy is a kind of marine renewable energy. It is regarded as aforward-looking solution for sustainable power generation because of
its high power density, high stability, good economic benefits andenergy flow without intermission.Furthermore,the total exploitableamount is the same as the power consumption. A mainstream Wave
energy converters (WECs) is the Oscillating Buoy(OB).To lower thelevelized cost of energy (LCOE), a real-time latching control methods
is being investigated. The latching control was first introduced by
Budal and Falnes (Budal, 1980). Power absorption is achieved bylocking and releasing the buoy alternately to keep the phase of WEC
align with the wave excitation force. Babarit and Clement (Babarit,2006) assessed the power extraction of an oscillating-body WEC withlatching control. Previous studies focus on the optimal control, whichassumed that the coming wave force was already known. But real-timelatching control is result in non-causal transfer functions, so it makesense only if future wave force is known. Meanwhile, the informationof future force is difficult to measure directly in real sea state.

DYNAMIC MODEL
According to the difference in working principle, WEC can be divided
into the following categories. Oscillating water column (OWC),
overtopping and oscillating buoy (OB). Most offshore WEC devices
belong to OB, which are located in deep water, with high energy flow
density and can exploit more abundant wave energy resources. The
research environment of this study is located in the deep ocean, using
offshore oscillating buoy wave energy conversion device, and using
direct-drive generators. Its energy conversion mechanism is to generateenergy through the relative motion of a floater subjected to wave loads359