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Analysis of wave resource model spatial uncertainty and its effect on wave energy converter power performance

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Journal of Ocean Engineering and Marine Energy Aims and scope Submit manuscript


Wave models used for wave energy resource assessments are subjected to uncertainties, which differ from one location to another over the defined model area. This is because the models are typically calibrated and validated using a single or few validation points, and the model uncertainties of the wave parameters generally grow with the distance to the validation point. The spatial uncertainty of wave resource is one of the vital considerations in wave resource numerical modelling, since it is used to estimate the confidence in site assessments of potential wave energy device locations away from the validation point and is a necessary requirement of a resource assessment to IEC TS 62600-101. This paper focuses on developing a methodology for determining the spatial uncertainty by analysing how wave parameter uncertainties may change with location over the model area. A test site is modelled using the SWAN third-generation numerical wave model and validated at a single location for several wave parameters. A set of Monte-Carlo simulations are used to generate estimates of model uncertainties for locations around the validation point and a step-wise procedure is demonstrated with appropriate justifications to evaluate the uncertainties at these locations with respect to the validation point. Finally, the obtained results are used with a Wave Energy Convertor (WEC) numerical model to estimate the uncertainties on the power capture of the device.

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Data availability

The data that support the findings of this study are available from the corresponding author, Lokuliyana R.L.K., upon reasonable request.


H m0 :

Significant wave height

T e :

Energy Period

J :

Omni-directional wave power

n :

Number of Monte-Carlo datasets

N :

Number of timesteps/sea-states

d i :

Error at the validation point of ith MC dataset (i = 1, 2, 3….n)

r i :

Error at the remote location of ith MC dataset (i = 1, 2, 3….n)

e j :

Error at the validation point relative to the measured data

M j :

Average offset error (model bias) at jth timestep (j = 1, 2, 3….N)

SD j :

Standard deviation of offset(random error) at jth timestep (j = 1, 2, 3….N)

P :

Power capture in wave energy converter

β :

Power capture bias due to model bias Mj

δ :

Power capture uncertainty due to random error SDj


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The authors express their appreciation to Sri Lanka Sustainable Energy Authority (SLSEA), Dr. P.N. Wickramanayake at the Open University of Sri Lanka and Mr. B.H.B.P.D. Baddegamage at the University of Peradeniya, Sri Lanka for providing initial support for this project and thank to the anonymous reviewers.


No funding was received to assist with the preparation of this manuscript.

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Correspondence to R. L. K. Lokuliyana.

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1.1 Appendix 1

A 150 kW class point absorber-type wave energy device is selected for WEC modelling of the analysis. Table 7 shows the dimensions of the buoy that was designed, and Figs. 8 and  9 illustrates a schematic diagram of the buoy and radiation damping of the WEC.

Table 7 Dimensions of the modelled buoy
Fig. 8
figure 8

Schematic diagram of the modelled buoy

Fig. 9
figure 9

The radiation damping of the WEC vs wave frequency

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Lokuliyana, R.L.K., Folley, M. & Gunawardane, S.D.G.S.P. Analysis of wave resource model spatial uncertainty and its effect on wave energy converter power performance. J. Ocean Eng. Mar. Energy 9, 715–729 (2023).

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