Reference Model #1 Tidal Energy: Resource

Similar documents
Tidal Resource Characterization. Profilers

Resolving Spatial Resource Gradients at Tidal Energy Sites

Tidal energy resource characterization: methodology and field study in Admiralty Inlet, Puget Sound, US

Resource Mapping at Tidal Energy Sites

Extreme Value Analysis of Tidal Stream Velocity Perturbations

A Comparison of Predicted Along-channel Eulerian Flows at Cross- Channel Transects from an EFDC-based Model to ADCP Data in South Puget Sound

Tidal Resource Characterization from Acoustic Doppler Current Profilers. Jeffrey Epler. A thesis. submitted in partial fulfillment of the

Measurements of Turbulence at Two Tidal Energy Sites in Puget Sound, WA

Inference of Turbulence Parameters from a ROMS Simulation using the k-ε Closure Scheme

This file is part of the following reference: Access to this file is available from:

8.1 SPATIAL VARIABILITY OF TIDAL CURRENTS IN PUGET SOUND, WASHINGTON. Gregory Dusek, Christina Pico, Christopher Paternostro and Paul Fanelli,

TURBULENCE MEASUREMENTS FROM 5-BEAM ACOUSTIC DOPPLER CURRENT PROFILERS

Quantifying Turbulence for Tidal Power Applications

The Parameterisation of Turbulence in the Marine Environment

TIDAL TURBULENCE SPECTRA FROM A COMPLIANT MOORING

Improving Surface Flux Parameterizations in the NRL Coupled Ocean/Atmosphere Mesoscale Prediction System

TIDAL DISTORTION AS PERTAINS TO HYDROKINETIC TURBINE SELECTION AND RESOURCE ASSESSMENT

Sediment Transport at Density Fronts in Shallow Water: a Continuation of N

Dynamics of the Ems Estuary

Hydrodynamics in Shallow Estuaries with Complex Bathymetry and Large Tidal Ranges

UC Berkeley Technical Completion Reports

Tidal stream atlases Reprinted by PC Maritime with kind permission of Proudman Laboratory

Noise correction of turbulent spectra obtained from Acoustic Doppler Velocimeters

Analysis of Physical Oceanographic Data from Bonne Bay, September 2002 September 2004

Performance of the Nortek Aquadopp Z-Cell Profiler on a NOAA Surface Buoy

HIGH RESOLUTION SEDIMENT DYNAMICS IN SALT-WEDGE ESTUARIES

DISCLAIMER FOR FRONT PAGE OF MATERIALS TO BE MADE AVAILABLE VIA ETI INTERNET SITE

Stall Dynamics of a Cross-Flow Turbine

Design, commissioning and performance of a device to vary the turbulence in a recirculating flume

Review of Anemometer Calibration Standards

Turbulent Mixing During an Admiralty Inlet Bottom Water Intrusion. Coastal and Estuarine Fluid Dynamics class project, August 2006

RPSEA Hi-Res Environmental Data for Enhanced UDW Operations Safety (S&ES)

Testing a free-stream turbine a in real turbulent tidal flow

Standard Practices for Air Speed Calibration Testing

Turbulence is a ubiquitous phenomenon in environmental fluid mechanics that dramatically affects flow structure and mixing.

centrifugal acceleration, whose magnitude is r cos, is zero at the poles and maximum at the equator. This distribution of the centrifugal acceleration

Field Measurements at River and Tidal Current Sites for Hydrokinetic Energy Development: Best Practices Manual

Circulation Through the Narrows of St. John s Harbour: Summer and Fall 1999

7. Basics of Turbulent Flow Figure 1.

SIO 210 Introduction to Physical Oceanography Mid-term examination Wednesday, November 2, :00 2:50 PM

Investigation of Flow Profile in Open Channels using CFD

Final Examination, MEA 443 Fall 2008, Lackmann

FINAL PRESENTATION: Hi-Res Environmental Data for Enhanced UDW Operations Safety - Task 5: Bottom Current Measurements and Modeling

FRICTION-DOMINATED WATER EXCHANGE IN A FLORIDA ESTUARY

MORPHODYNAMIC PROCESSES IN ESTUARIES COMPARISON OF MARINE AND LIMNIC TIDAL FLATS

Cross-Spectral Phase Method for Distinguishing Waves from Turbulence in Single-Point Boundary Layer Flow Measurements

NEW SEAFLOOR INSTALLATIONS REQUIRE ULTRA-HIGH RESOLUTION SURVEYS

Sea Level Variability in the East Coast of Male, Maldives

A 3D unstructured numerical model of Ems-Dollart estuary Observations and 3-D modeling. Pein JU, Stanev EV, Zhang YJ.

Characterization of Flow Rates in an In-Water Algal Harvesting Flume

River Current Resource Assessment and Characterization Considering Ice Conditions

The Frequency Response of Acoustic Doppler Current Profilers

Turbulence and Bottom Stress in Grand Passage and Minas Passage. Final Report. Submitted by. Alex Hay Department of Oceanography Dalhousie University

THE OPEN UNIVERSITY OF SRI LANKA

Longitudinal dispersion and lateral circulation in the intertidal zone

Flow estimations through spillways under submerged tidal conditions

Summary Results from Horizontal ADCP tests in the Indiana Harbor Canal and the White River

Combining SES and ADCP to measure mud transport processes in tide-controlled estuaries

A Study on Residual Flow in the Gulf of Tongking

HARMONIC CONSTANTS Product Specification

Assessing Storm Tide Hazard for the North-West Coast of Australia using an Integrated High-Resolution Model System

ADCP Data Quality Control

Temporal and spatial variability of vertical salt flux in a highly stratified estuary.

TEMPORAL VARIATIONS OF VERTICAL MIXING ACROSS A COASTAL PLAIN ESTUARY

Modeling the Lateral Circulation in Straight, Stratified Estuaries*

Barotropic Flow in the Vicinity of an Idealized Inlet Simulations with the ADCIRC Model

ANALYSIS OF FLOW CONDITIONS AT THE IHNC-GIWW SECTOR GATE

A novel technique for measuring the rate of turbulent dissipation in the marine environment

Storm surge forecasting and other Met Office ocean modelling

Tidal Energy Dissipation at the Sill of Sechelt Inlet, British Columbia

The near-bottom current regime and the role of the benthic. nepheloid layer in transport and accumulation of particulate matter

Prediction of changes in tidal system and deltas at Nakdong estuary due to construction of Busan new port

3.4 HYDRODYNAMIC MODELING OF ENGINEERED INLET AND CANAL EXTENSION

CASCO BAY ESTUARY PARTNERSHIP. R. Michael Doan FRIENDS OF CASCO BAY. May 2007

FORECASTING: A REVIEW OF STATUS AND CHALLENGES. Eric Grimit and Kristin Larson 3TIER, Inc. Pacific Northwest Weather Workshop March 5-6, 2010

Red Sea - Dead Sea Water Conveyance Study Program Additional Studies

Using a Broadband ADCP in a Tidal Channel. Part II: Turbulence

HORIZONTAL TURBULENT DIFFUSION AT SEA SURFACE FOR OIL TRANSPORT SIMULATION

Adapting NEMO for use as the UK operational storm surge forecasting model

Signature 55 Long Range Current Profiler Data from a Short Deployment Lee Gordon Doppler Ltd. January 7, 2015 This report presents

Changes in Marine Extremes. Professor Mikis Tsimplis. The LRET Research Collegium Southampton, 11 July 2 September 2011

MICHAEL W. STACEY. Department of Physics, Royal Military College of Canada, Kingston, Ontario, Canada S. POND

7B.4 ASSESSMENT OF THE GROSS U.S. OFFSHORE WIND ENERGY POTENTIAL

Development of Operational Storm Surge Guidance to Support Total Water Predictions

Lecture 2. Turbulent Flow

Internal Wave Modeling in Oceanic General Circulation Models

The international project on Ocean CO 2 sequestration

SEDIMENT TRANSPORT IN RIVER MOUTH ESTUARY

DETERMINATION OF THE POWER LAW EXPONENT FOR SOUTHERN HIGHLANDS OF TANZANIA

DATA ASSIMILATION FOR FLOOD FORECASTING

Investigation of the Air-Wave-Sea Interaction Modes Using an Airborne Doppler Wind Lidar: Analyses of the HRDL data taken during DYNAMO

Using a Broadband ADCP in a Tidal Channel. Part I: Mean Flow and Shear

SCIENCE CHINA Earth Sciences. Turbulence and mixing in a freshwater-influenced tidal bay: Observations and numerical modeling

Remote Monitoring of Subsurface Flow Conditions in Rivers

Sediment Transport at Density Fronts in Shallow Water

Long-Term Observations of Turbulent Reynolds Stresses over the Inner Continental Shelf

Ch. Kasprzyk, TU Dresden

The use of MIKE21 to study the. barrier beach system of Inner Dingle Bay, Co. Kerry, Ireland. Dr. Michael O Shea Malachy Walsh and Partners

Temporal and spatial variability of vertical salt flux in a highly stratified estuary

Applying Gerris to Mixing and Sedimentation in Estuaries

Transcription:

Northwest National Marine Renewable Energy Center niversity of Washington, Seattle, WA 9895 Reference Model # Tidal Energy: Resource Technical Report: W 20 02 December 20 Dr. Brian Polagye, Department of Mechanical Engineering

Table of Contents Introduction 2 Methodology 3 Results 4 4 Discussion 6 5 Conclusions 6 6 References 6

List of Figures Figure Admiralty Inlet, Washington ADCP deployment locations superimposed on bathymetry (meters relative to mean lower low water)... 2 Figure 2 Tacoma Narrows, Washington ADCP deployment locations superimposed on bathymetry (meters relative to mean lower low water)... 3 Figure 3 Normalized velocity distributions for sites in Puget Sound. Blue bars denote sites in northern Admiralty Inlet. Red bars denote sites in Tacoma Narrows. The black line denotes the generalized velocity distribution for the reference model (mean of all sites).... 5 Figure 4 Normalized velocity profiles for sites in Puget Sound. Blue profiles denote locations in northern Admiralty Inlet. Red bars denote sites in Tacoma Narrows. The black line is a power law profile with a /7 th exponent, chosen by inspection to represent the reference model distribution.... 5

List of Tables Table ADCP measurement detail for Puget Sound, Washington... 2 Table 2 Reference resource distribution for a mixed, mainly semidiurnal tidal regime... 4

Introduction Reference Model # is a tidal turbine operating in a narrow, tidal channel. The site is a generalized version of Tacoma Narrows, Puget Sound, Washington. The resource is a mixed, mainly semidiurnal tidal regime with two ebbs and floods each day of unequal strength (i.e., a diurnal inequality in which a strong ebb/flood exchange is followed by a weak exchange). The diurnal inequalities provide extended windows of weak currents for device installation and maintenance activities relative to a purely semidiurnal tidal regime, though at the expense of reduced generation potential for equivalent peak currents. Doppler profiler data from Puget Sound are used to construct a reference tidal resource (i.e., a generic mixed, mainly semidiurnal tidal regime). After Polagye and Thomson (submitted), currents measured by a Doppler profiler ( sample ) may be conceptually partitioned into deterministic ( det ), meteorological ( met ), and turbulent ( turb ) components, as well as Doppler uncertainty (n sample ) (Brumley et al. 99). sample det n. (.) met turb sample each of which are further subdivided. The deterministic currents include harmonic currents, described by harmonic constituents, as well as the aharmonic response to these currents induced by local topography and bathymetry. Aharmonic currents are not described by tidal constituents, but are repeatable, site specific flow features. Meteorological currents include wave and wind induced motion, residual currents associated with estuarine stratification, and storm surges. Turbulent currents include large scale, horizontal eddies and small scale, isotropic turbulence. In order to evaluate device performance, a generalized probability distribution and vertical profile for current speeds in a mixed, mainly semidiurnal tidal regime is required. Once the distribution of velocities is known, leading order device performance may be evaluated based on the device operating parameters at each point on the distribution. These parameters include cut in speed, rated speed, and power conversion efficiency. 2 Methodology Doppler profiler measurements from sites in Puget Sound with utility scale potential are summarized in Table. Details for northern Admiralty Inlet are given in Figure and Tacoma Narrows in Figure 2. While the reference site is patterned after Tacoma Narrows, there are a limited number of measurements for this location. Therefore, it is desirable to expand the basis for the generalized distribution to include other energetic sites in Puget Sound.

Table ADCP measurement detail for Puget Sound, Washingtonn Site Depth Dates Duration Vertical (m) (days) Resolution (m) Northern Admiralty Inlet AI AI 2 AI 4 AI 5 AI 6 AI 7 AI 8 85 67 56 65 66 56 58 08/8/07 09/9/ /07 08/8/07 09/9/ /07 05/20/09 08/03/ /09 08/05/09 /0/ /09 /2/09 0/29/ /0 02//0 05/04/ /0 05/06/0 07/09/ /0 32 32 75 97 78 82 64 2 Tacoma Narrows TN TN 2 30 55 05/30/07 07/0/ /07 07/02/07 08/02/ /07 32 3 Evans Hamilton Inc. 2 niversity of Washington, Northwest National Marine Renewable Energy Centerr Ensemble Interval (s) Source 9000 EHI 9000 EHI 30 NNMREC 2 35 NNMREC 45 NNMREC 60 NNMREC 60 NNMREC 9000 EHI 9000 EHI AI 2 AI AI 3 AI 9 AI 8 AI 4 AI 7 AI 55 AI 6 Figure Admiralty Inlet, Washingtonn ADCP deployment locations superimposed on bathymetry (meters relative to mean lower low water) 2

TN 3 TN TN 2 Figure 2 Tacoma Narrows, Washington ADCP deployment locations superimposed on bathymetry (meters relative to mean lower low water) In order to directly compare data from the sites listed in Table, all measurements are converted to a 5 minute (900 s) ensemble ( ensem ble). This greatly reduces the contribution of turbulence (Thomson et al. in revision), ensemble sa ample det met t urb n where the overbar denotes the temporal mean. This also reduces ensemble Doppler noise (n ensemble ) by a factor of N /2 relative the original Doppler noise (n sample ), where N is the number of samples in the ensemble. In comparison to the deterministic component ( d det), n ensemble iss very small and may be neglected. The fifteen minute ensembles are also likely to smooth the aharmonic component. In Polagye and Thomson (submitted), a five minute ensemble is recommended in order to preserve the deterministic and meteorological components, while filteringg out the turbulent component and Doppler noise. However, this is shorter than the sample interval for some of the available measurements and it is preferred to treat all measurement s consistently. In Puget Sound, storm surges and wind driven currents are not significant and the primary contributor to meteorological currents is estuarine circulation associated with density gradients. In Polagye and Thomson (submitted), it is demonstrated that thesee residual currents are small in comparison to deterministic currents at mid water depth, but are significant near the surface and seabed. The following procedure is applied to derive a generalized probability distribution of tidal currents. As mentioned above, dataa from each of the sites listed in Table is first standardized to a 5 minute ensemblee average. A time series of current speed (absolute value of horizontal velocity) is then sample det met, n ensemble (2.) 3

extracted at mid water depth, such that the deterministic component of the tidal currents dominates over the meteorological component. The series is then normalized by the maximum ensemble average speed in the time series ( max ), ensemble norm (2.2) max and distributed into equal size bins ranging from zero to one. The average of these normalized distributions for all sites is taken as a generalized velocity distribution for a mixed, mainly semi diurnal tidal regime. The vertical profile associated with this generalized distribution is selected by inspection of the mean vertical profile for all sites in Table. This is given in the form of a power law 2z z 0.5 (2.3) D where 0.5 is the mid water current speed, z is the depth of interest, D is the water depth, and α is the empirical power law exponent. Three aspects of this approach are worth noting. First, it is a considerable oversimplification to assume that the vertical profile is constant over all tidal cycles. Analyses (B. Polagye, unpublished results) show that the power law exponent (α) that best describes the vertical profile varies with the strength and direction of the currents. Second, α is rarely single valued for a given current velocity (e.g., at / max = 0.5, α will take on a range of values depending on whether these currents are observed during an accelerating or decelerating portion of the tidal cycle). Third, while commonly used in wind and hydrokinetic applications, the power law description of the vertical profile lacks physical basis. A log layer description based on bottom roughness and shear velocity may be preferable in future reference models. 3 Results The distribution of normalized velocities in Puget Sound and the reference distribution are shown in Figure 3 and the values for the reference distribution are given in Table 2. Table 2 Reference resource distribution for a mixed, mainly semidiurnal tidal regime / max 0 0. 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Frequency 0.04 0.33 0.5 0.57 0.50 0.36 0.03 0.07 0.040 0.06 0.003 4

Figure 3 Normalized velocity distributions for sitess in Puget Sound. Blue bars denote sites in northern Admiralty Inlet. Red bars denote sites in Tacoma Narrows. The black line denotes the generalized velocity distribution for the reference model (mean of all sites). Figure 4 shows vertical profiles for all sites in Puget Sound and the generalized, reference profile. In all cases, the profiles represent the average power law fit for all measurements at a given location. By inspection, the black line, which denotes a /7 th power law profile, is roughly in the middle of the observed profiles. Since this profile has been used in prior studies (e.g., EPRI feasibility assessments), it is selected as the reference profile. Figure 4 Normalized velocity profiles for sites in Puget Sound. Blue profiles denote locations in northern Admiralty Inlet. Red bars denote sites in Tacoma Narrows. The black line is a power law profile with a /7 th exponent, chosen by inspection to represent the reference modell distribution. h 5

4 Discussion The reference distribution given in Table 2 may be combined with the /7 th power law profile and any reasonable value for max to yield a hub height velocity distribution for tidal device performance evaluation. Based on data from Puget Sound (Polagye and Thomson submitted), 3 m/s is a reasonable value for max. This representation of the currents for performance evaluation is extremely compact, but also extremely idealized. First, the turbulent component of the tidal currents is significant (Thomson et al. in revision), but excluded from this representation. Note that, in general, the relation between turbulence and device performance has not been established for hydrokinetic turbines. Second, off axis inflow conditions are likely, due to directional variations within the tidal cycle and asymmetries between the direction of ebb and flood (i.e., ebb and flood not bidirectional). A more complete description of the tidal currents might be given by a joint probability distribution of velocity with direction. Third, as previously discussed, a single valued power law exponent does not provide a complete or physically justified description of the vertical structure of the tidal currents. These limitations could be addressed by future reference modeling efforts as their relative importance is clarified through device testing and modeling. 5 Conclusions Doppler profiler data from Puget Sound serves as a basis for a reference distribution and vertical profile of current velocities for a mixed, mainly semidiurnal tidal regime. This representation is suitable for estimating leading order device performance in the reference resource. The limitations of this representation are briefly discussed. 6 References Brumley, B.H., Cabrera, R.G., Deines, K.L, and Terray, E.A. Performance of a Broad Band Acoustic Doppler Current Profiler, IEEE Journal of Oceanic Engineering, 99, 6(4), 402 407. Polagye, B. and J. Thomson (submitted), Tidal energy resource characterization: methodology and field study in Admiralty Inlet, Puget Sound, S. Thomson, J., B. Polagye, V. Durgesh, and M. Richmond (in revision) Measurements of turbulence at two tidal energy sites in Puget Sound, WA (SA). 6