The OWA GloBE (Global Blockage Effect) project, introduced at the OWA GloBE webinar held in August 2024, is a precedent case in Europe where large-scale offshore wind farms are in operation, and there is much to learn from it. In particular, the methods of wind observation and numerical model analysis contain many elements that can be used as reference for Japanese offshore wind power generation projects.
Therefore, in this technical note, we will explain the contents of this webinar in two parts. This time, we will summarize the overview of this project and the results of the blockage phenomenon observed within the project. For more details,This videoIt is explained in the article. Please take a look at it.
- Project Goal
- What is the blockage effect and what is its importance?
- Project background: The need for highly accurate wind observation
- Blockage effect measurement location and period
- Main observational instruments and methods
- How to handle data supplementation and correction
- Observation results
- Industry collaboration through the JIP method
- Summary
Project Goal
The GloBE project had five key goals:
- Quantifying the blockage effect: Observation of wind speed changes and elucidation of their mechanisms
- Consensus building in industry: Building a standard model for the blockage effect
- Optimizing your measurement technique: Adoption of highly accurate measurement technology using scanning lidar
- Building the Dataset: Providing a dataset for model validation based on actual measurement data
- Improving the reliability of energy yield predictions: Minimizing forecast errors at large-scale wind power plants
What is the blockage effect and what is its importance?
The blockage effect is a phenomenon in which wind speed temporarily decreases ahead of a row of wind turbines, and is said to be particularly noticeable in large-scale offshore wind farms. This phenomenon is caused by changes in the air flow that occur when the wind turbines catch the wind, and is thought to affect the energy yield of the entire wind farm.
Traditionally, predictions of the energy yield of wind power plants have focused on the wake region.Wake EffectIn previous studies, the main focus was on blockage effect (wind speed reduction), but ignoring the blockage effect could lead to overestimation of power generation. Therefore, in this project, we quantified the blockage effect to improve the accuracy of revenue forecasts, enabling accurate design and operation planning.
For more information on the blockage effect and this project, please see our previous Relatec technical notes.
Project background: The need for highly accurate wind observation
The blockage effect has been known as a theoretical hypothesis until now.There have been no detailed observations of operational offshore wind farms.This project is the first attempt at this. It is suggested that this phenomenon will become more pronounced as the scale of offshore wind farms increases, and it is therefore important to take the blockage effect into account in order to accurately evaluate the power generation output of offshore wind power plants in Japan.
In this project,1%Slight wind speed attenuation belowThe target is wind attenuation, and extremely high-precision wind observation is essential to accurately measure this attenuation. Therefore, the observation methods and correction/complementation methods used are highly advanced, making this a noteworthy technological advancement in wind observation.
Blockage effect measurement location and period
The measurements were carried out in the German North Sea in the Deutsche Bucht area (Nord Ost offshore wind farm).Approximately nine months from September 2021 to May 9This ranges from.
Main observational instruments and methods
The following instruments and methods were employed to collect detailed data:
| Observation method | Purpose of use | Placement and range | Major features |
|---|---|---|---|
| Scanning Lidar | Measurement of horizontal wind speed gradient. Analysis of wind speed components (U, V) and wind direction. | high: 90 m, Horizontal Range: Max 4 km. | Three pairs of dual observations were carried out, incorporating earth curvature correction, dynamic motion correction, and drone angle calibration. |
| Floating Rider | Measurement of upstream reference wind speed. | Moved between three locations (near the observation point, upstream reference point, near the observation mast). | Observations using a vertical lidar mounted on a buoy, taking into account sea surface motion. Used to complement scanning lidar data. |
| Offshore wind observation mast | Data verification, ABL (boundary layer height) measurement. | Inside the Nord Ost wind farm. | Ultrasonic anemometer (max16 Hz) and weather sensors to measure atmospheric stability and sea surface temperature. |
| Boundary Layer Altimetry Lidar | Measurement of boundary layer height (ABL). | high: 0–2,000 m (mainly500 mto). | A scanning lidar was used to analyze horizontal wind speed and direction using the VAD (Velocity Azimuth Display) method. |
How to handle data supplementation and correction
To obtain accurate and reliable data, the following correction and imputation methods were adopted in this project:
| Correction and supplementation methods | Task | Workaround | Effect |
|---|---|---|---|
| Earth curvature correction | Due to the curvature of the Earth, distant altitudes are measured higher. | Altitude data is corrected to account for the curvature of the earth. | Improving the accuracy of wind speed and direction data obtained by long-distance observations using scanning lidar. |
| Dynamic Motion Compensation | Tower vibrations affect the observation beam. | The accelerometer and gyro sensor measure and correct the shaking. Maximum angular displacementLess than 0.1 degreesReduced to. | Eliminate the effects of vibration to obtain accurate data. |
| Lidar angle calibration | Error caused by deviation in the lidar beam direction. | RTK technology using drones※ 1High-precision calibration of beam direction. | The lidar beam direction is aligned with the real space to improve observation accuracy. |
| Data Completion | When missing data occurs. | Supplement floating rider and metamast data. Apply linear interpolation and power law. | Filling in missing data and reconstructing wind speed distribution. |
| Ensuring time synchronization | Time lag between instruments affects the consistency of observations. | Synchronization is achieved via line-of-sight antennas, resulting in uniform time stamps. | Ensure data consistency between all observation instruments. |
※ 1RTK (Real-Time Kinematic Positioning) technology: A satellite positioning technology for obtaining highly accurate position information in real time. Based on regular GPS and GNSS (Global Navigation Satellite System), positioning accuracy can be greatly improved by correcting data from base stations and mobile stations in real time.
Observation results
- Checking the blockage effect:
- The wind speed is highest at the front of the turbine row.5%Decline(Especially noticeable in wind speeds between 4 and 12 m/s)
- Downstream, wind speed increases by 1-3% under certain conditions (acceleration effect)
- Atmospheric Boundary Layer Height (ABL)) influence:
- It was confirmed that the blockage effect is stronger when the boundary layer height is low.
- Comparison of observations and model data shows that the boundary layer height is300~400mThis shows good agreement with the model prediction.
The observational data was used to verify a numerical model that reproduces the new blockage effect (see the second commentary for details).Narrow wind direction bin of 270°±5°The S-shaped wind speed change curve confirmed in provided important information for elucidating the mechanism of the blockage effect.
Upstream of the wind turbine row (left side of the figure below), the wind speed gradually decreases (deceleration due to blockage) and is lowest near the wind turbine row (maximum 5% decrease). Meanwhile, downstream of the wind turbine row (right side of the figure below), the wind speed recovers again and an acceleration effect (wind speed increases by 1-3%) is confirmed in some areas, resulting in an S-shaped change in the wind speed distribution against the horizontal axis (distance).
The significance of this S-curve is explained as follows:
- Modeling blockage effects
- The S-shaped wind speed change curve indicates that the blockage effect is not just a deceleration phenomenon,Interaction of the entire wind turbine array with the surrounding atmosphereThis suggests that this is a complex dynamic phenomenon
- Based on the measurement results, a new blockage effect model was verified and developed.
- Relationship between wind speed and energy yield
- Taking into account the S-curve improves the accuracy of forecasting the energy yield of the entire wind farm
- In particular, more realistic scenarios can be envisaged for the design and operation planning of entire wind turbine banks.
- The importance of measurement technology
- High accuracy measurements within narrow wind direction bins (±5 degrees) are achieved by using scanning lidar precision compensation (dynamic motion compensation and RTK technology)
- By improving observational accuracy, the previously unclear characteristics of the blockage effect can be elucidated in detail.
Industry collaboration through the JIP method
This project isCarbon Trust,The project was implemented as a Joint Industry Project (JIP) led by the Japan Offshore Wind Power Corporation, with the aim of improving profitability and reducing costs across the industry. This type of industry collaboration is an initiative that Japan's offshore wind power sector should take note of. The JIP approach has enabled the sharing of technical knowledge, improved cost efficiency, and promoted standardization, and is expected to be applied to projects in Japan.
Through the JIP approach, the project achieved the following results:
- Sharing technical knowledge: Sharing measurement techniques and modeling know-how among partners
- Increased cost efficiency: Utilizing scanning lidar to reduce the need for expensive floating lidar
- Promoting standardization: Establishing unified evaluation criteria across the industry
Based on these results, it is believed that in the future, Japan will also need to build a cooperative framework within the industry to address technical issues and deal with them more quickly.
Summary
GloBE has provided detailed measurements of blockage effects and shared technical knowledge across the industry, improving the accuracy of wind farm energy yield predictions and providing key data on which to base further research and development, marking an important milestone for the future of offshore wind.
On the other hand, the following three main issues and prospects have been pointed out as future challenges and prospects, so we will continue to pay close attention to future developments.
- Seasonal effects: Measurements were concentrated in autumn and winter, and there is a lack of summer data.
- ABL Modeling: A detailed analysis of the interaction between boundary layer height and atmospheric properties (discussed in the next post)
- The need for long-term projects: Aiming for wider data collection and technological development
This technical note summarizes actual measurements of the blockage effect at a large-scale offshore wind farm. Even if the blockage effect only reduces wind speed by about 1%, it can affect a wide area, so highly accurate wind observation is essential. In the next issue, we will introduce a numerical model of the blockage effect.
(Written by Mizuki Konagaya)
References
The Carbon Trust RWE, (2024, August 6th). OWA GloBE: Measuring the Global Blockage Effect[Video]. YouTube. https://www.youtube.com/watch?v=x-QP4X0Dfb8