Uncertainty in wave energy resource assessment. Part 1: Historic data

Mackay, Ed; Bahaj, A.S.; Challenor, Peter

doi:10.1016/j.renene.2009.10.026

Cited by 70 publications

(33 citation statements)

References 25 publications

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“…A more realistic understanding of the uncertainties in the wave energy resources assessment, especially as regards their variability and predictability, is key to any wave energy project [44,45]. From this perspective, this section will focus on evaluating the influence on the wave conditions of some parameters of the environmental matrix, especially tide and wind.…”

Section: Study Of the Tide And Wind Influences In The High Resolutionmentioning

confidence: 99%

High-Resolution Wave Energy Assessment in Shallow Water Accounting for Tides

Silva¹,

Rusu²,

Soares³

2016

Energies

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The wave energy in a shallow water location is evaluated considering the influence of the local tide and wind on the wave propagation. The target is the coastal area just north of the Portuguese city of Peniche, where a wave energy converter operates on the sea bottom. A wave modelling system based on SWAN has been implemented and focused on this coastal environment in a multilevel computational scheme. The first three SWAN computational belonging to this wave prediction system were defined using the spherical coordinates. In the highest resolution computational domain, Cartesian coordinates have been considered, with a resolution of 25 m in both directions. An in-depth analysis of the main characteristics of the environmental matrix has been performed. This is based on the results of eight-year model system simulations (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012). New simulations have been carried out in the last two computational domains with the most relevant wave and wind patterns, considering also the tide effect. The results show that the tide level, together with the wind intensity and direction, may influence to a significant degree the wave characteristics. This especially concerns the wave power in the location where the wave converter operates.

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Section: Study Of the Tide And Wind Influences In The High Resolutionmentioning

confidence: 99%

High-Resolution Wave Energy Assessment in Shallow Water Accounting for Tides

Silva¹,

Rusu²,

Soares³

2016

Energies

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“…Mackay et al [9] identify three main sources of uncertainty that influence the estimates of achievable annual electricity production:…”

Section: • Grid Integrationmentioning

confidence: 99%

“…. ) perhaps the most difficult to quantify" [9]. The main reasons are that i) it is difficult to predict failures for a new technology and ii) operational experience is scarce.…”

Section: • Grid Integrationmentioning

confidence: 99%

“…The reason for this is the relatively large variance σ 2 for both the prior and the likelihood distribution. Due to the significantly larger mean failure rate modelled for the unknown failure mode likelihood distribution, the posterior distribution is shifted to the right of the prior, yielding a 90% confidence interval CI posterior, 2 = [9,46]. Thus, in the light of the additional information the failure rate uncertainty would increase.…”

Section: Posterior Distributionmentioning

confidence: 99%

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Addressing failure rate uncertainties of marine energy converters

2012

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The interest in marine renewable energy is strong, but has not led to significant commercial scale investment and deployment, yet. To attract investors and promote the development of a marine renewable industry a clear concept of project risk is paramount, in particular issues relating to device reliability are critical. In the public domain, reliability information is often scarce or inappropriate at this early stage of development, as little operational experience has been gained. Thus, reliability estimates are fraught with large uncertainties. This paper explores sources and magnitudes of failure rate uncertainty and demonstrates the effect on reliability estimates for a notional marine energy converter. If generic failure rate data forms the basis of a reliability assessment, reliability estimates are not robust and may significantly over-or underestimate system reliability. The Bayesian statistical framework provides a method to overcome this issue. Generic data can be updated with more specific information that could not be statistically incorporated otherwise. It is proposed that adopting such an approach at an early stage in an iterative process will lead to an improved rate of certainty.

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“…The aforementioned validation studies of wave models show varying amounts of detail, but most looked within the spectra at least to point out particular case studies. Mackay et al [14] concentrates on the Measure--Correlate--Predict (MCP) method of predicting an energy yield and shows how to find uncertainty bounds on the estimate. This is a very powerful method, but if the goal of a resource assessment is to understand the fit of the model to the location of interest with more detail, or to try to make the data more accurate, this method may not be appropriate.…”

Section: Introductionmentioning

confidence: 99%

Verification within wave resource assessments. Part 2: Systematic trends in the fit of spectral values

Edwards

Cradden

Ingram

et al. 2014

International Journal of Marine Energy

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Interest in wave energy as a viable renewable energy has increased greatly in the past couple of decades. To determine the potential that a certain location has to harvest wave energy, a resource assessment must be performed for that location. As wave energy converter technologies get closer to market, it is becoming necessary to undertake more detailed resource assessments to determine the optimal location for deployment as well as the design and operating sea states. This study shows the level of sophistication that must be included in the verification process within a wave resource assessment. We describe the methodology in two articles. Part 1 described a procedure for a complete statistical analysis of the fit of the model. This paper will demonstrate how investigating systematic trends in the fit of spectral values is essential for determining the precise problem areas of the model and is thus required as part of the verification processes. Lacking this detail could mean failing to notice potentially vital issues for energy extraction at the location of interest. The identification of specific problem areas will enable a well--informed consideration of the necessary next steps for improved prediction of energy extraction.

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Uncertainty in wave energy resource assessment. Part 1: Historic data

Cited by 70 publications

References 25 publications

High-Resolution Wave Energy Assessment in Shallow Water Accounting for Tides

High-Resolution Wave Energy Assessment in Shallow Water Accounting for Tides

Addressing failure rate uncertainties of marine energy converters

Verification within wave resource assessments. Part 2: Systematic trends in the fit of spectral values

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