Sensor Assisted Wind farm Optimisation


An intelligent way to measure the wind field and produce more energy

Onshore and offshore wind turbines must operate at their best capacity to maximise the energy they generate. Currently, the methods used to optimise performance in wind farms focus mainly on the performance of individual turbines. Fortunately, new low-cost wind measurement technologies have been developed that can help improve the performance of multiple wind turbines in large wind farms.

Sensor-assisted wind farm optimisation (SAWOP) will enable better monitoring of the incoming wind flow using spinner anemometers and nacelle LiDAR systems. Based on the sensor data analysis, strategies can be developed to improve the energy yield of the whole wind farm.

Demonstration of the technology

Koen Hermans, an offshore wind energy researcher at TNO, says: “One of the focus points in the analysis is to determine the alignment of the rotor with the wind direction, so-called yaw alignment. The results will be used to determine the performance of the wind farm and the sensors themselves under free-stream and wake conditions."

Wind field measurement systems

"Our first test site is the onshore wind farm Klim Fjordeholme in Denmark, operated by Vattenfall. It consists of 21 Siemens turbines of 3.2 MW each featuring a rotor diameter of 113 m. Because the wind farm is close to the coast, the conditions are comparable to an offshore wind farm. Furthermore, it has the practical advantage that the turbines are more easily accessible.

At this wind farm, a measurement campaign is being carried out. Nick Jansen, team leader at Nabla Wind Hub: "The big difference between the two systems is where the wind is measured: on the turbine or hundreds of metres in front of the turbine."

A profiling LiDAR scans the incoming wind field and serves as a reference. Eight turbines are equipped with iSpin spinner anemometers, and two forward-facing nacelle LiDARs from different manufacturers are installed. During the campaign, these LiDARS are exchanged so that we can compare the results of each LIDAR at the same location. Finally, a scanning LiDAR is mapping the wake conditions, which will be enhanced by an algorithm to reconstruct the wind field. Special care is taken to calibrate all sensors to the latest standards to ensure objective measurement of turbine and sensor performance."

Reducing the wake effect

To optimise the yield of an entire wind farm, the influence of the wake effect is also investigated. Koen Hermans explains: "The turbine blades create vortices behind the rotor that may influence the yield of other turbines in the wind farm. This is called the wake effect. If we steer the front turbine in a less favourable position to the wind, its yield will decrease but the turbine behind it can produce more energy because the effect of the wake has decreased. The economic and technical models take into account the additional wear and tear and the possibly shortened lifetime of the turbines."

Jan Coelingh, Lead Engineer Wind Resource of Vattenfall agrees: “The point is to control the settings for the entire wind farm and not just for the individual turbines for the optimal result.”

Improving performance

"Taken together, these measurements provide us with a unique dataset to evaluate the performance of the sensors in the free-stream and wake conditions. Based on possible performance deficits, optimised control settings can be derived. In the final phase of the project, innovative control strategies for wind farms will be investigated. It is expected that the information from the sensors used will improve performance through the use of wind farm control".

This project aims to demonstrate that the overall energy yield of large wind farms can be increased through the use of advanced measurement devices and associated advanced control strategies. The results from this project will make a valuable contribution to the international standardisation of performance assessment using these new sensor technologies.

Another tangible outcome is the creation of a unique measurement database. From this database, the project partners will gain insights into the wind flow of an operating wind farm, the performance of the turbines and the effectiveness of the monitoring systems.

Jasper Kreeft, Senior Wind Farm Performance Lead at Shell adds, " computational and engineering models for wind resource assessments and wake modelling are continuously being developed and improved. The extensive measurement campaign within the SAWOP project provides a unique dataset to validate these models.”


This article is part of the series Project in the Spotlight. Discover more projects here.