Computational Fluid Dynamics

Similar documents
Increased Project Bankability : Thailand's First Ground-Based LiDAR Wind Measurement Campaign

ENERGY YIELD PREDICTION AN OFFSHORE GUIDE

WindProspector TM Lockheed Martin Corporation

Validation of Measurements from a ZephIR Lidar

Wind resource assessment over a complex terrain covered by forest using CFD simulations of neutral atmospheric boundary layer with OpenFOAM

Evaluation of four numerical wind flow models

Global Flow Solutions Mark Zagar, Cheng Hu-Hu, Yavor Hristov, Søren Holm Mogensen, Line Gulstad Vestas Wind & Site Competence Centre, Technology R&D

Are Advanced Wind Flow Models More Accurate? A Test of Four Models

Wind Farm Blockage: Searching for Suitable Validation Data

Wind Flow Modeling: Are computationally intensive models more accurate?

Energy capture performance

Why does T7 underperform? Individual turbine performance relative to preconstruction estimates.

Measurement and simulation of the flow field around a triangular lattice meteorological mast

Session 2a: Wind power spatial planning techniques. IRENA Global Atlas Spatial planning techniques 2-day seminar

Session 2: Wind power spatial planning techniques

On the use of rotor equivalent wind speed to improve CFD wind resource mapping. Yavor V. Hristov, PhD Plant Performance and Modeling Vestas TSS

Executive Summary of Accuracy for WINDCUBE 200S

Outline. Wind Turbine Siting. Roughness. Wind Farm Design 4/7/2015

Centre for Offshore Renewable Energy Engineering, School of Energy, Environment and Agrifood, Cranfield University, Cranfield, MK43 0AL, UK 2

Wind Flow Analysis on a Complex Terrain

EMPOWERING OFFSHORE WINDFARMS BY RELIABLE MEASUREMENTS

Comparison of flow models

OFFSHORE CREDENTIALS. Accepted for wind resource assessment onshore and offshore by leading Banks Engineers, globally

Offshore Micrositing - Meeting The Challenge

Dick Bowdler Acoustic Consultant

Flow modelling hills complex terrain and other issues

CORRELATION EFFECTS IN THE FIELD CLASSIFICATION OF GROUND BASED REMOTE WIND SENSORS

LES* IS MORE! * L ARGE E DDY S IMULATIONS BY VORTEX. WindEnergy Hamburg 2016

Rotor Average wind speed for power curve performance. Ioannis Antoniou (LAC), Jochen Cleve (LAC), Apostolos Piperas (LAC)

Available online at ScienceDirect. Procedia Engineering 126 (2015 )

Wind shear and its effect on wind turbine noise assessment Report by David McLaughlin MIOA, of SgurrEnergy

Pre Feasibility Study Report Citiwater Cleveland Bay Purification Plant

Study on wind turbine arrangement for offshore wind farms

Windcube FCR measurements

New IEC and Site Conditions in Reality

Havsnäs Pilot Project

Modelling atmospheric stability with CFD: The importance of tall profiles

PROJECT CYCLOPS: THE WAY FORWARD IN POWER CURVE MEASUREMENTS?

OPTIMIZING THE LENGTH OF AIR SUPPLY DUCT IN CROSS CONNECTIONS OF GOTTHARD BASE TUNNEL. Rehan Yousaf 1, Oliver Scherer 1

Innovative and Robust Design. With Full Extension of Offshore Engineering and Design Experiences.

10 th WindSim User Meeting June 2015, Tønsberg

Pigging as a Flow Assurance Solution Avoiding Slug Catcher Overflow

Predicting climate conditions for turbine performance

Snare Wind Monitoring Update 2016

A STUDY OF THE LOSSES AND INTERACTIONS BETWEEN ONE OR MORE BOW THRUSTERS AND A CATAMARAN HULL

Offshore wind in COWI

Can Wind Energy Be Captured in New York City? Case Study on Urban Wind based on a Feasibility Study by Orange Line Studio. Spark 101 Educator Resource

Wind Flow Validation Summary

Forest Winds in Complex Terrain

Wind Project Siting & Resource Assessment

Vertical Alignment. Concepts of design & guidelines Computing elevations along vertical curves Designing vertical curves

The Wind Resource: Prospecting for Good Sites

Inuvik Wind Monitoring Update 2016

RESOURCE DECREASE BY LARGE SCALE WIND FARMING

Site Assessment Report. Wind farm: Ascog Farm (GB)

Energy from wind and water extracted by Horizontal Axis Turbine

LiDAR Application to resource assessment and turbine control

Advanced pre and post-processing in Windsim

Session 2b: Wind power spatial planning techniques

Large-eddy simulation study of effects of clearing in forest on wind turbines

Free Surface Flow Simulation with ACUSIM in the Water Industry

H8 Signs, Supports and Poles

Tidal influence on offshore and coastal wind resource predictions at North Sea. Barbara Jimenez 1,2, Bernhard Lange 3, and Detlev Heinemann 1.

Energy Output. Outline. Characterizing Wind Variability. Characterizing Wind Variability 3/7/2015. for Wind Power Management

Lopez Community Land Trust. Final Wind Energy Report

MEMO CC: Summary. ESMWT16419: _MEM_RVO_HKZ floating LiDAR uncertainty_v3.docx 1/8

The EllipSys2D/3D code and its application within wind turbine aerodynamics

Contributions from a multidisciplinary university Finn Gunnar Nielsen Professor Geophysical Institute

A Comparison of the UK Offshore Wind Resource from the Marine Data Exchange. P. Argyle, S. J. Watson CREST, Loughborough University, UK

7 th International Conference on Wind Turbine Noise Rotterdam 2 nd to 5 th May 2017

Full Classification acc. to IEC for SoDAR AQ510 Wind Finder. Vincent Camier, Managing Director, Ammonit Measurement GmbH

Fuga. - Validating a wake model for offshore wind farms. Søren Ott, Morten Nielsen & Kurt Shaldemose Hansen

Torrild - WindSIM Case study

APPLICATION OF RESEARCH RESULTS AT LM WIND POWER

Numerical and Experimental Investigation of the Possibility of Forming the Wake Flow of Large Ships by Using the Vortex Generators

CFD ANALYSIS AND COMPARISON USING ANSYS AND STAR-CCM+ OF MODEL AEROFOIL SELIG 1223

An independent study to assess and validate the shape and size of the Potentially Impacted Areas used in BEAWARE 2 Qualitative results

SUPPLEMENTARY GUIDANCE NOTE 4: WIND SHEAR

Surrounding buildings and wind pressure distribution on a high rise building

Modelling the Output of a Flat-Roof Mounted Wind Turbine with an Edge Mounted Lip

Influence of wind direction on noise emission and propagation from wind turbines

Stefan Emeis

Can Lidars Measure Turbulence? Comparison Between ZephIR 300 and an IEC Compliant Anemometer Mast

Portuguese Market Outlook up to 2040

3D Nacelle Mounted Lidar in Complex Terrain

PARK - Main Result Calculation: PARK calculation (5 x 166m, + LT CORR + MITIGATION) N.O. Jensen (RISØ/EMD)

REMOTE SENSING APPLICATION in WIND ENERGY

Roof Mounted Wind Turbines: A Methodology for Assessing Potential Roof Mounting Locations

Wind Project Siting and Permitting Blaine Loos

Wind Flow Model of Area Surrounding the Case Western Reserve University Wind Turbine

REQUIREMENTS FOR VALIDATION OF MATHEMATICAL MODELS IN SAFETY CASES

Wake measurements from the Horns Rev wind farm

AIRFLOW GENERATION IN A TUNNEL USING A SACCARDO VENTILATION SYSTEM AGAINST THE BUOYANCY EFFECT PRODUCED BY A FIRE

WIND INDUSTRY APPLICATIONS

FINO1 Mast Correction

WIND DIRECTION ERROR IN THE LILLGRUND OFFSHORE WIND FARM

3D-simulation of the turbulent wake behind a wind turbine

Power curves - use of spinner anemometry. Troels Friis Pedersen DTU Wind Energy Professor

Workshop 1: Bubbly Flow in a Rectangular Bubble Column. Multiphase Flow Modeling In ANSYS CFX Release ANSYS, Inc. WS1-1 Release 14.

Ermenek Dam and HEPP: Spillway Test & 3D Numeric-Hydraulic Analysis of Jet Collision

Transcription:

Computational Fluid Dynamics A better understanding of wind conditions across the whole turbine rotor

INTRODUCTION If you are involved in onshore wind you have probably come across the term CFD before but may not fully understand its application and benefits. This guide describes how, if used to its full potential, CFD aids understanding of turbine performance in complex wind regimes leading to higher P90s. Why CFD matters Photo 1 - Simple terrain Photo 2 - Complex forested terrain These photos show sites with very different terrain and ground cover. These aspects, along with atmospheric stability (relative buoyancy of air, often due to temperature variation) are what primarily influence wind flow. On simple flat sites, as in photo 1, wind characteristics tend not to vary from one location to the next, so wind measurements combined with traditional flow models (eg. WAsP) do a good job of representing the wind at each turbine. Not so in photo 2, where trees and slopes cause large variations in turbulence, rendering traditional models for predicting wind speed and shear ineffective. Given that it s not economically viable to blanket a site with masts to get measurements at every turbine location, CFD allows accurate prediction of wind characteristics at these complex sites.

HOW CFD HELPS Reducing development equity A better P90/P50 ratio means less capital investment by the owner. One of the best ways to do this is to reduce uncertainty in the energy yield prediction. CFD has the double benefit of reducing both horizontal extrapolation i.e. wind flow modelling, and turbine performance uncertainties. Even if we consider a small wind farm, the reduction in equity can be up to 20 times the original cost of CFD modelling. For more detail on this, see our upcoming guide on how to reduce energy yield prediction uncertainty. Picking the best place to put turbines Imagine the kind of performance you would get driving a car down a narrow lane with two wheels on the tarmac and two in the ditch. Placing a turbine where a portion of the rotor is subject to high turbulence and shear has a similar effect with consequent impact on O&M costs and performance. CFD allows these areas to be identified for hilly and forested sites so they can be avoided. Real world turbine performance Turbine power curves are measured in simple wind conditions, as depicted in photo 1 on the previous page. If this power curve is then applied to the complex wind conditions in the other photo, as is common practice, the resulting energy yield prediction is likely to be optimistic. Many consultants use CFD to predict wind speed at hub height only, but at Prevailing we are unique in using CFD output to understand wind flow across the whole rotor. This brings realism to turbine performance predictions in complex wind conditions. CFD is advantageous for the following reasons: Higher certainty wind speed, shear and turbulence predictions; Optimal turbine positioning; Accurate turbine performance predictions; Improved project finances due to higher overall P90.

Examples 200 MW project, UK - Maximising the energy yield and P90 and reducing lifetime O&M costs. CFD was employed to highlight areas of highly volatile flow. These areas were then avoided during turbine micro-siting, maximising turbine performance and lowering lifetime operations and maintenance costs. CFD results also reduced the energy yield uncertainty, giving the developer a double benefit. 75 MW project, UK Minimising energy yield loss from trees The client needed to determine which of 3 possible felling strategies would lead to the lowest energy yield loss. The influence of each of the felling strategies on wind flow was modelled using CFD and the one with lowest energy yield loss selected. 150 MW project, Chile Improved energy yield estimate for large complex terrain site The client was developing a 35km² complex site in Chile. There were masts on site but some turbine locations were situated 11km away in locations where the wind flow differed markedly due to upwind terrain features. The use of CFD results gave the client far higher confidence in the energy yield estimate because they explained the influence of the complex terrain lying upwind of the site. Additionally, the wind conditions predicted by CFD modelling were used to decide where best to position a LiDAR in order to gather additional wind measurements.

WHAT IS CFD? You ve now grasped that CFD is essential to accurately model wind flow across complex wind farm sites, but how... Meshing Imagine a hilly, forested wind farm site in 3D. We first define the region to be considered by the model. This region is called the domain. The domain must be significantly larger than the site to allow the simulated flow to develop. Next, we divide the domain into millions of individual cubes or cells. This is referred to as a mesh. Information about topography, atmospheric physics, tree heights, dimensions of buildings or other solid obstacles and surface roughness is provided to the mesh. The 3D mesh fills the domain which covers the wind farm site and surrounding region Simulation Wind from each direction is then pushed through the domain. Fundamental equations describing fluid flows are solved iteratively within every cell of the mesh to determine how the wind will behave. The result of this calculation is a HUGE amount of data (around 100 GB for an average wind farm). The complex physics that can be included within a CFD model allows the effect of complex terrain features and atmospheric variations to be determined more accurately than ever before. Results processing The trick is to process the data produced by the simulation to obtain wind parameters such as wind speed, turbulence, shear, veer and inflow angle at all locations within the 3D mesh across the whole wind farm, then interpret these parameters in a way that provides most benefit to the wind farm development. Powerful stuff!

FAQs Do the benefits of CFD offset the cost? CFD requires some additional investment above more typical analysis methods because running the model requires a cluster of computers and interpreting the data requires a high degree of specialist knowledge. If CFD is applied at feasibility stage for an average northern European project, the capex and opex benefits from increased yield, better capex deployment, reduced wind farm O&M costs and lower energy yield estimate uncertainty far outweigh the cost. Even if CFD modelling is only used in the final financial grade study, the financial gains from the increase in P90 are considerable. Will CFD significantly increase the analysis timescale? Prevailing can typically deliver an energy yield assessment including CFD results within a 3-4 week timescale, and regularly do so to support investors in making more informed acquisition decisions. We re deliberately set up to deliver results quickly, enabling our clients to bid with confidence. Which sites benefit most from the application of CFD? Sites with steep slopes, forests or buildings are where CFD really excels. CFD applies more complex turbulence modelling, enabling flow in these areas to be more accurately predicted than by using WAsP or other simplified methods. However any site where there is a considerable distance between turbine locations and the on-site measurement location is likely to benefit from the application of CFD. At which point in the project life cycle should I apply CFD? The results from a CFD simulation remain valid throughout the project development life cycle. Therefore to get most value from the investment, CFD should be carried out as early as possible in the development of the project. Applying CFD early in the development process minimises the number of iterations required to design an optimal wind farm and provides considerable cost savings. As more on-site measurements become available the simulation results can be re-applied to subsequent energy analyses with minimal further investment. Lots of consultancies offer CFD but their services and costs vary considerably. Why the difference? For CFD to provide maximum value a high quality simulation must be carried out. It is also essential that the results of the simulation are properly interpreted to benefit the energy yield prediction. Prevailing is unique in considering flow conditions across the whole rotor and the resultant impact on turbine performance and lifetime O&M costs. We also specialise in communicating results clearly and concisely to the client.

CONTACT HEADQUARTERS UK - ENGLAND Prevailing Ltd 10th Floor Tower House Fairfax Street Bristol BS1 3BN GERMANY Prevailing Europe c/o Combinat 56 Adams-Lehmann-Strasse 56 80797 Munich UK - SCOTLAND Prevailing Ltd 2 Woodside Place Glasgow G3 7QF USA Prevailing North America 707 SW Washington Street, Suite 1100 Portland, OR 97205 tel. +44 (0)117 927 3393 enquiries@prevailinganalysis.com www.prevailinganalysis.com Correct at time of print 01/2017