SUPERGEN Wind Wind Energy Technology

Transcription

1 SUPERGEN Wind Wind Energy Technology SUPERGEN WIND 2 Activity Overview Offshore Wind Farm Aerodynamics & the Environment Prof Simon Watson (On behalf of consortium) Joint Supergen Wind 2 / EDP University Training Event Edinburgh 23 rd 24 th October 2012

2 Introduction Offshore wind resource Wakes and aerodynamics Radar and the environment Optimisation of farm performance Deliverable 4.2

3 Resource Case Studies Scroby Sands & Shell Flats Shell Flats

4 Mesoscale Modelling of Wind Resource CFSR Input Data WRF - ARF Simulated wind variables Model output compared to Scroby Sands PBL ensemble predictions Variability in model performance needs to be understood and addressed

5 Remote Sensing Data for Resource Assessment All Directions Limit of log layer Hemsby Radiosonde Data Scroby Sands Mast Data Wind Coming From Sea Wind Coming From Land

6 Offshore Atmospheric Stability Study of Scroby Sands and Shell Flats mast data Significant periods of nonneutral stability conditions Scroby Sands Shell Flats

7 CFD Wake Modelling and Atmospheric Stability Very stable Neutral Wake recovery faster as atmosphere more unstable Very unstable

8 Wind Farm Arrays

9 Working section: 3.5m x 1.5m x 20m long EnFlo Environmenal Wind Tunnel at University of Surrey

10 Wind Tunnel Effect of Stable Stratification Neutral: Stable: L 0 /D +3

11 Wind Tunnel Unstable Stratification X/D = 0.5 X/D = 1 X/D = 2 L 0 /D + neutral O X/D = 3 X/D = 4 X/D = 5

12 Unstable Stratification 2D L 0 /D neutral

13 Wind Farm and Radar Modelling Within Supergen accurate turbine geometry for radar scattering modelling was used The effect of radar absorbing materials was also investigated Turbine modelling is only the start The aim is to model a complete wind farm for site/radar specific assessment Environmental and inter-turbine interaction modelling Modelling the effects of local terrain Computational efficiency for rapid assessment of possible impact

14 RCS / dbms Turbine Bistatic Scattering Total Turbine STAR Bistatic RCS Bistatic Angle / Deg

15 Radar output Analysis Modelling of radar output (display) to help radar operators and developers understand the possible issues that may arise from a particular wind farm Helps identify the areas of wind farm that produce unwanted radar returns Gap filling radars are often suggested as a possible mitigation option

16 Offshore Reliability Egmond aan Zee, the Netherlands Control System Yaw System Scheduled Service Pitch System Gearbox Ambient Generator Converter Electrical Blade System Structure Grid Brake System Stop Rate and Downtime from Egmond aan Zee Wind Farm, the Netherlands, over 3 Years 36 x Vestas V90-3MW Egmond aan Zee Failure Rate, 108 Turbine Years Egmond aan Zee Downtime, 108 Turbine Years Annual Stop Frequency Downtime per Stop (days)

17 Availability (%) Availability (%) Availability (%) Availability (%) Availability and Wind Speed Scroby Sands (30 x V80) Wind Speed (m/s) Kentish Flats (V90) Wind Speed (m/s) North Hoyle (30 x V80) Wind Speed (m/s) Egmond aan Zee (36 x V90) Wind Speed (m/s)

18 Energy (MWh) Energy (MWh) Energy (MWh) Energy (MWh) Lost Energy 100% Percentage energy generated and theoretically lost for a given wind speed Scroby Sands (30 x V80) 100% Kentish Flats (V90) 80% 80% 60% 60% 40% 40% 20% 20% 0% % North Hoyle (30 x V80) Egmond aan Zee (36 x V90) 100% 100% 80% 80% 60% 60% 40% 40% 20% 20% 0% % Energy Generated Theoretical Lost Energy due to Unavailability

19 Deliverable 4.2 Integrate resource, wake and radar models to optimise turbine siting Determine availability and O & M costs for specific site Macroscale and microscale economics Produce cost of energy for specific sites within given constraints, e.g. area, water depth and cabling configurations Validation and exemplar sites