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BSI PD IEC/TS 62600-101:2015

$198.66

Marine energy. Wave, tidal and other water current converters – Wave energy resource assessment and characterization

Published By Publication Date Number of Pages
BSI 2015 58
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This part of IEC 62600 , which is a Technical Specification, establishes a system for estimating, analysing and reporting the wave energy resource at sites potentially suitable for the installation of Wave Energy Converters (WECs). This Technical Specification is to be applied at all stages of site assessment (from initial investigations to detailed project design) and in conjunction with the IEC Technical Specification on WEC performance ( IEC TS 62600‑100 ) enables an estimate of the annual energy production of a WEC or WEC array to be calculated. This Technical Specification is not intended for estimation of extreme wave conditions.

The wave energy resource is primarily defined using hydrodynamic models that are successfully validated against measurements. The framework and methodologies prescribed in this Technical Specification are intended to ensure that only adequate models are used, and that they are applied in an appropriate manner to ensure confidence and consistency in the reported results. Moreover, the document prescribes methods for analysing metocean data (including the data generated by modelling) in order to properly quantify and characterize the temporal and spatial attributes of the wave energy resource, and for reporting the results of a resource assessment in a comprehensive and consistent manner.

PDF Catalog

PDF Pages PDF Title
4 CONTENTS
7 FOREWORD
9 INTRODUCTION
10 1 Scope
2 Normative references
3 Terms and definitions
12 4 Symbols and units
13 5 Classes of resource assessment
5.1 Introductory remarks
5.2 Resource assessment and characterization flow chart
Tables
Table 1 – Classes of resource assessment
15 Figures
Figure 1 – Wave resource assessment and characterization flow chart
16 6 Study planning and data collection
6.1 Introductory remarks
6.2 Study area
6.3 Bathymetry
6.4 Existing wave data
Table 2 – Resolution of bathymetric data
17 6.5 Wave measurement
6.5.1 Purpose
6.5.2 Selection of measuring instrument and analysis methodology
18 6.5.3 Instrument calibration
6.5.4 Instrument deployment
Table 3 – Minimum requirements for wave measuring instruments and associated analysis
19 6.5.5 Redundancy
6.5.6 Analysis of measurements
6.6 Wind data
Table 4 – Resolution of wind data
20 6.7 Tide data
6.8 Current data
6.9 Ice coverage and/or exceptional environmental conditions
6.10 Water density
6.11 Gravitational acceleration
21 7 Numerical modelling
7.1 Introductory remarks
7.2 Suitable numerical models
Table 5 – Elements of suitable numerical models
23 7.3 Definition of boundary conditions
24 7.4 Modelling the nearshore resource
25 7.5 Effect of WEC array on wave energy resource
7.6 Validation of numerical models
7.6.1 Introductory remarks
7.6.2 Validation data specification
26 7.6.3 Procedure
27 Table 6 – Minimum validation requirements
29 7.6.4 Extent of validation
Figure 2 – Validation flow chart
30 7.7 Model tuning and calibration
31 8 Measure-Correlate-Predict (MCP)
8.1 Introductory remarks
8.2 Procedures
32 9 Data analysis
9.1 Introductory remarks
33 9.2 Characterization using two-dimensional wave spectra
9.2.1 Overview
9.2.2 Omni-directional wave power
9.2.3 Characteristic wave height
34 9.2.4 Characteristic wave period
9.2.5 Spectral width
9.2.6 Directionally resolved wave power
35 9.2.7 Wave system partitioning
9.3 Estimation of wave power using parameterized sea states
36 9.4 Aggregation and statistics of results
9.4.1 General
9.4.2 Mean
9.4.3 Standard deviation
9.4.4 Percentiles
9.4.5 Monthly variability
37 9.5 Uncertainty of the resource assessment
10 Reporting of results
10.1 Introductory remarks
Table 7 – Uncertainty categories
38 10.2 Selection of study points
10.3 Technical report
10.4 Digital database
39 10.5 Presentation of regional information
Table 8 – Summary of wave energy resource parameters to be archived and mapped
40 10.6 Presentation of information at study points
Figure 3 – Example map of mean annual wave power
42 Figure 4 – Example of a scatter table summarizing a long-term wave climate in terms of Hm0 and Te
Figure 5 – Example of a wave power rose
43 Figure 6 – Example plot showing the distribution of wave power for different months
44 Annex A (informative)A method for sensitivity analysis
A.1 General
A.2 Specification of significance
A.3 Sample sea states
Table A.1 – Recommended sensitivity thresholds
45 A.4 Condition of insensitivity
Table A.2 – Recommended condition of insensitivity
46 Annex B (normative)Evaluation of measurement uncertainty
B.1 General
B.2 Uncertainty analysis
Table B.1 – List of uncertainty components
47 Annex C (informative)Example calculation of long-term uncertainty
C.1 General
Figure C.1 – Annual wave power variability in the UK. Eleven sites in North East, North West and South West Regions [4]
48 C.2 Climatic variability
Figure C.2 – Comparison between mean annual power from the E04 model dataset and the North Atlantic Oscillation index from 1988 to 2006 [5]
Table C.1 – Comparison of Mean Average Error (MAE) and Maximum error (Max error) between the 3, 5 and 10 year averages of the data at the combined UK sites and the E04 Dataset (WaveHub)
49 Figure C.3 – Recorded North Atlantic Oscillation index from 1825 to 2010 (red bars), with a five year moving average (black line) [5]
50 Figure C.4 – Annual, 5-year, 10-year and 20-year moving averages of available wave power at the a site [7]
Figure C.5 – Annual mean power and running 5, 10 and 20 year mean values, 150 km North of Scotland [6]
51 C.3 Anthropogenic climatic variability
C.4 Conclusion
52 Annex D (informative)Nearshore resource
D.1 General
D.2 Limiting water depth
53 D.3 Bathymetry
D.4 Fluctuating water level
D.5 Currents
D.6 Validation
54 D.7 Uncertainty
55 Bibliography
BSI PD IEC/TS 62600-101:2015
$198.66