Visualising Forest Edge Effects Ralph Torr Senior Engineer 25 June 2013

Similar documents
2 nd generation Lidar techniques in complex forested terrain

Modelling wind flow in forested area: a parametric study

PERDIGÃO WIND TURBINE WAKE MEASUREMENT

Onshore Wind. Optimisation & Cost Reduction. All Energy 2015

Reducing Uncertainty in Wind Project Energy Estimates

SAWEP Workshop. Cape Town, 4 th March Wind farm calculations - Annual Energy Production

Forest Model WindSim 7 interim report WKN AG renewable energies for today and tomorrow

Framework for the Categorisation of Losses and Uncertainty for Wind Energy Assessments

WIND FLOW MODELING IN BUSINESS!!

Wind and Meteo: Common energy. What can we learn from each other?

Measuring a Utility-Scale Turbine Wake Using the TTUKa Mobile Research Radars

H AIR QUALITY MODELLING OF ROAD PROJECTS USING A 3D COMPUTATIONAL FLUID DYNAMICS (CFD) MODEL. Malo Le Guellec, Lobnat Ait Hamou, Amita Tripathi

Modelling Wind Turbine Inflow:

IEA Wind Task 32: Wind lidar identifying and mitigating barriers to the adoption of wind lidar

Simulation of wind conditions in forested areas: Data inputs and approaches

Lidar Measurements at SWIFT

Wind Power and Comparison to Conventional Generation

Separation between Wind Turbines and Overhead Lines Principles of Good Practice

3. IZMIR WIND SYMPOSIUM AND EXHIBITION October , 2015 TEPEKULE CONVENTION CENTRE IZMIR

Comparison of Resource and Energy Yield Assessment Procedures What have we learned and what needs to be done?

Comparison of Resource and Energy Yield Assessment Procedures What have we learned and what needs to be done?

Matthew Smith Head of Business Development measuring wind power to the highest standards

Post-construction Yield Analysis. Performance and budget analysis for probabilistic yield modeling of operational wind plant

VALIDATION OF GH ENERGY AND UNCERTAINTY PREDICTIONS BY COMPARISON TO ACTUAL PRODUCTION

INVESTIGATION OF THE IMPACT OF WAKES AND STRATIFICATION ON THE PERFORMANCE OF AN ONSHORE WIND FARM

WIND ENERGY RESOURCE ASSESSMENT: A CASE STUDY

The increased focus on reducing

Kathleen E. Moore Integrated Environmental Data, LLC, Berne, NY Loren W. Pruskowski Sustainable Energy Developments, Inc.

WIND-DRIVEN RAIN ON THE WALLS OF BUILDINGS IN METRO VANCOUVER: PARAMETERS FOR RAIN PENETRATION TESTING

Technology evolution and new market developments NZWEA Conference 2016 Daniel Belton Vestas New Zealand

H POLLUTANT DISPERSION OVER TWO-DIMENSIONAL IDEALIZED STREET CANYONS: A LARGE-EDDY SIMULATION APPROACH. Colman C.C. Wong and Chun-Ho Liu*

THE BUSINESS CASE FOR WIND TURBINES

Modelling to measurements and back

MODERN PRACTICES FOR MEASUREMENT OF GAS PATH PRESSURES AND TEMPERATURES FOR PERFORMANCE ASSESSMENT OF AN AXIAL TURBINE

BC Hydro Wind Data Study Update

Analysis of SCADA data from offshore wind farms. Kurt S. Hansen

Energy Yield Assessment for: Sudenai, Lithuania. 14 MW Wind farm 7 x Enercon E MW 78 m hub height

Impact of Forest-Elevated Turbulence Levels on Wind Farm Performance

Wind Energy. ME922/927 Wind energy 1

CFD and Wind Tunnel Study of the Performance of a Multi- Directional Wind Tower with Heat Transfer Devices

WIND RESOURCE & ENERGY YIELD ASSESSMENT PRESENTATION

Project Title: Development of a High-Resolution Virtual Wind Simulator for Optimal Design of Wind Energy Projects

Quantifying Change in Power Performance using SCADA Data

INSTITUTE FOR SUSTAINABLE FUTURES PARKES SHIRE COUNCIL: SMALL WIND SITE ASSESSMENT

Capability Statement. Energy Resource Services.

A Study on Method for Identifying Capacity Factor Declination of Wind Turbines

EXAMINATION OF TRAFFIC POLLUTION DISTRIBUTION IN A STREET CANYON USING THE NANTES 99 EXPERIMENTAL DATA AND COMPARISON WITH MODEL RESULTS

N A B C E P. Small Wind Associate Learning Objectives. NABCEP Small Wind Associate Learning Objectives

INFLUX (The Indianapolis Flux Experiment)

WINDSIM STUDY OF HYBRID WIND FARM IN COMPLEX TERRAIN. A thesis PAUL HINES

Onshore Services for. Manufacturers. of Wind Turbines & Components

Visualization of the tip vortices in a wind turbine wake

Meredith Sperling 1,2 Alexandra St. Pé 3, Aditya Choukulkar 4, Cristina L. Archer 5, Ruben Delgado 2,6

Three-Dimensional Numerical Simulation of a Model Wind Turbine

Publishable summary. 2 nd Periodic Report. Date: November, 2016 Prepared by: CIRCE

Project Financing Risk Identification/Mitigation

TropiSAR data analysis and biomass inversion

Mapping Scotland with PALSAR: An Assessment of the Importance of L-Band Polarimetry

Forestry Applications of LiDAR Data Funded by the Minnesota Environment and Natural Resources Trust Fund

Mapping Hemlocks to Estimate Potential Canopy Gaps Following Hemlock Woolly Adelgid Infestations in the Southern Appalachian Mountains

The Near-Shore Wind Resource Assessment and Power Generation at Huasai, Nakhon Si Thammarat, Southern Thailand

Capability Statement. Energy Resource Services.

Application of remote sensing by the New Zealand forest industry. Aaron Gunn

Using Information from Data Rich Sites to Improve Prediction at Data Limited Sites

Urban Wind Turbines: A Feasibility Study

MURDOCH RESEARCH REPOSITORY

Rumster Wind Energy Project

Transfer of Science to industry in Wind Energy

CFD/FEM Based Analysis Framework for Wind Effects on Tall Buildings in Urban Areas

WIND FARM PERFORMANCE ASSESSMENT UNDER DIFFERENT WAKE MODELS: A CASE STUDY IN COMPLEX TERRAIN

CHAPTER 1. Introduction

FLUID STRUCTURE INTERACTION MODELLING OF WIND TURBINE BLADES BASED ON COMPUTATIONAL FLUID DYNAMICS AND FINITE ELEMENT METHOD

Meteorological Data Requirements and Regulatory Conformance Issues

On the Effects of Directional Bin Size when Simulating Large Offshore Wind Farms with CFD

Next Generation of Wind Data. Integrating SCADA concepts for improved wind assessment and operations

3D Simulation of a fire inside a river tunnel and optimisation of the ventilation using Computational Fluid Dynamics

Flood Risk Management (Scotland) Act

Wind Analogue or Digital?

CTBUH Technical Paper

Harvesting Wind Power from Tall Buildings

PROPOSED CHANGE TO THE 2012 BUILDING CODE O. REG. 332/12 AS AMENDED

Investigation of Meteorological Tower Siting Criteria

Optimization of Wind Farm Layout taking Load Constraints into Account

Airborne Laser Scanning (ALS) for forestry applications

Woodland owners routinely want to measure property acreage,

Estimating uncertainties in multiple wind farm Annual Energy Production (AEP)

Engineering, Environmental, Biological and Geophysical Fluid Dynamics. Department of Civil Engineering College of Science and Engineering

Big Databases in forest planning and operations New national lidar campaign in Sweden

EXPERIMENTAL INVESTIGATION OF URBAN CANOPY LAYER FLOW AND DISPERSION

Appendix C, Attachment 4 June 11, Diversion Channel Outlet Hydraulic Modeling RAS and ADH

Windfarm Value Engineering & Optimisation. Dr. Christoph Hessel

Improved Wind Turbine Efficiency using Synchronized Sensors

Smoke Dispersion from Stacks on Pitched-Roof Buildings: Model Calculations Using MISKAM in Comparison with Wind Tunnel Results

Development of Design Tool for Low-Head Francis Turbine. * Corresponding author

The future of wind power

Land Seismic Acquisition

arxiv: v1 [physics.flu-dyn] 11 Oct 2013

COMPLETE MET SYSTEMS RESOURCE ASSESSMENT AND POWER PERFORMANCE

Summary of Actual vs. Predicted Wind Farm Performance Recap of WINDPOWER 2008 Clint Johnson Garrad Hassan America

SAR forest canopy penetration depth as an indicator for forest health monitoring based on leaf area index (LAI)

Transcription:

Visualising Forest Edge Effects Ralph Torr Senior Engineer 25 June 2013

Carbon Trust Project Power From Onshore Wind Farms: Advanced Measurement and Modelling (POWFARM) Acknowledgement of Work Conducted by Roy Spence & Graham More (SgurrEnergy)

Measurements near/in forestry Location of masts relative to forestry not representative of WTG locations Current heights of masts not enough Measurement of shear profile above forestry effects Hub height measurement is only half the rotor Forestry and slopes DTU assessments of forest edges using Lidar devices.

Carbon Trust POWFARM Develop improved and validated computational flow models for wind farms in complex terrain Gain an enhanced understanding of forestry and topography, influenced wind flow interactions through a combination of advanced measurement and modelling technologies Developer focus forestry Workstream 1 advanced measurements Workstream 2 advanced modelling Workstream 3 existing model assessment

Site 1: Scotland Slopes (degrees) Tree Height (0-30 m) >22 17-22 10-17

Slopes (degrees) Site 2: Wales Tree Height (0-35 m) >22 17-22 10-17

Existing model assessment using site mast datasets WAsP WAsP Engineering CFD (Meteodyn) Both sites had significant measurement campaigns conducted Site Masts Anemometers Duration 1 4 70 (x2), 60, 50 & 30 m 6+ years, 6 years, 5 years & 3 years 2 2 70 (x2), 55, 40 4.5 years & 1.5 years 1 60 (x2), 50, 40 4.5 years All site 1 masts and 1.5 year mast on site 2 have independently calibrated Vector anemometry installed. Both 4.5 year site 2 masts have one top Vector anemometer with all others being NRG anemometers for an initial period and later refitted with all Vector anemometry. All Vector anemometers have independent calibrations.

WAsP roughness/displacement models (18 in total) Digitisation complexity Roughness representation value (α) Displacement height Low Low No Low Low Yes Low Medium Yes High Low Yes High Medium No High Medium Yes High High Yes High Very High No High Very High Yes Low roughness <0.5 for 25 m trees Medium roughness >0.5 & <2 for 25 m trees High roughness >2 & < 5 for 25 m trees Very high roughness >5 for 25 m trees

Site 1: Wind speed cross predictions WAsP Complexity H H H L H L H L L H Roughness V H M M V L M M L M Displacement Y Y Y Y N Y Y Y N N

Site 2: Wind speed cross predictions WAsP Complexity H H H L H L H L L H Roughness V H M M V L M M L M Displacement Y Y Y Y N Y Y Y N N

Intermediate CFD model parameters (approx. 15 models) Height roughness * Forest density Model type Domain (km) Sector solution steps Horizontal mesh size Vertical mesh size H/30 Low Dissipative 30 30 10 2 H/20 Normal Robust 40 10 15 3 H/15 High 18 4 * H equals tree height 22 25

Site 1: Wind speed cross predictions CFD Representation 15 15 15 20 20 15 15 20 20 20 30 20 30 30 15 Density H N N H H N N N N H H H H N L Model R R R R R D D R D D R D D D R Sectors 30 30 30 30 10 30 10 30 30 10 30 30 30 30 30

Site 2: Wind speed cross predictions CFD Representation 15 15 15 20 20 15 15 20 20 20 3 20 30 30 15 Density H N N H H N N N N H H H H N L Model R R R R R D D R D D R D D D R Sectors 30 30 30 30 10 30 10 30 30 10 30 30 30 30 30

Site 2: Turbulence intensity comparison (scaled) WAsP Engineering CFD Site 2: High roughness Mast To 1 2 3 1 0.0% 2.5% 0.1% 2 2.1% 0.0% 1.0% 3 4.0% 2.4% 0.0% Site 2: TI cross prediction Mast To 1 2 3 1 0.0% 0.8% 1.0% 2 0.4% 0.0% 1.0% 3 0.0% 2.3% 0.0% Percentage of the TI percentage value

Site 2: Turbulence intensity comparison WAsP Engineering CFD Site 2: Mast 1

Site 2: Turbulence intensity comparison WAsP Engineering CFD Site 2: Mast 2

Summary WAsP can perform well in low complexity topography, but high complexity forestry WAsP s capability deteriorates significantly in moderately complex terrain and complex forestry CFD offers significant benefits in moderately complex terrain and complex forestry BUT A single forestry modelling methodology is not optimal for all sites irrespective of WAsP or CFD modelling

Summary Although there is an inherent uncertainty in modelling turbulence intensity due to the difference between modelled and measured turbulence. Cross predictions using turbulence intensities from a number of masts (concurrent datasets) appears to be within the capabilities of CFD wind flow models. WAsP Engineering has the capability to cross predict the TI rose from one location to another, but is less capable than CFD in predicting the correct mast TI rose shape. CFD provides a greater accuracy in turbulence modelling. Measurements are essential Measurements need to be representative of the site (WTG) conditions Models need to be validated

Site measurement status - current Mast measurements at site Fairly representative of the site Increasingly supplemented by remote sensing data Gain point measurements around a wind farm site Site measurement status - ideal Terrain specific wind flow Topographic flow features Forestry edge effects Measuring across rotor heights POWFARM Advanced measurements using 2 nd Generation Galion Lidar

Galion scanning options RHI (Range Height Indicator ) vertical arc PPI (Position Plan Indicator) horizontal arc Stare single line [high temporal resolution] VAD (Velocity Azimuth Display)

Site 1: Deployment and scan geometry Galion

Site 2.1: Deployment and scan geometry Galion

Galion measurements: Site 1 (wind speed) Wind direction Elevated wind speed due to upwind hill FOREST Galion Trailing edge recovery Partial recovery between forest coupes

Galion measurements: Site 2 (wind speed) [diurnal variance] Day- Galion FOREST Night- Galion Wind direction FOREST

Galion measurements - site 2 (turbulence) Elevated turbulence region at higher height Stare Beams FOREST Galion Region of increased turbulence directly behind forestry Wind direction

Advanced Lidar deployments Careful selection of deployment location Line of sight / Prevailing wind direction Scan geometry selection Accuracy / Use of hard target return (HTR) in scan set-up Measurement Modelling Advanced Measurement

Galion FOREST Galion CFD (Meteodyn) Wind direction Showing Galion minus CFD Further Galion / CFD comparison data presented by ANSYS in Modelling of wind speed and turbulence intensity for a forested site in complex terrain, C Montavon et al, presented a EWEA 2012.

Conclusions Advanced modelling and measurement capabilities are available Require detailed knowledge of the site and careful model set-up to gain most useful data They are able to capture terrain specific flows related to WTG wind regime Topographic effects Forest edge effects Models can only be as good as the measurements they are validated against

Further work Building up database of slope and forestry measurements Further validation of CFD wind flow models using the Galion measurements Forestry management questions Continuous canopy? Keyholing how large? Clear-fell - how far?

Models can only be as good as the measurements they are validated against Any questions? roy.spence@sgurrenergy.com 0141 227 1700 www.sgurrenergy.com 225 Bath Street, Glasgow, G2 4GZ