Thursday, 29 September 2016
14:30 - 16:00 Wake modelling and forecasting
Resource assessment  
          

In the session there will be five presentations on wake modelling and forecasting. They will focus on the limitations in wake modelling including comparison with field data, and will move into short-term power production forecasting as well as studies of uncertainty in wind power forecast methods. 

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Learning objectives

• Understand the latest news regarding limitations and possibilities within wake modelling approaches;
• Exemplify forecast methods and their ability to accurately predict short time ahead production output;
• Address the importance of atmospheric stability in wind power forecasting and wake modelling;
• Determine whether simple linear wake combination methods as presently used in commercial analytical software can correctly represent turbine interactions.

This session will be chaired by:

Richard Fruehmann UL International GmbH, Germany
Co-authors:
Richard Fruehmann (1) ^F Thomas Neumann (1)
(1) UL International GmbH, Wilhelmshaven, Germany

Wake effects at FINO 1 – new observations since the construction of Trianel Borkum & Borkum Riffgrund I wind farms

Introduction

The construction of wind farms in the vicinity of the FINO 1 research platform in the North Sea began in 2008 with Alpha Ventus and its 12 turbines to the East of the platform. Operation of the wind farm began in 2009 and a measureable influence on wind measurements at FINO 1 were soon observed in the wind data. Since the spring of 2015 two new wind farms have been constructed to the West and South of FINO 1. Although these are further away – the nearest turbine is approximately 4 km distant – the wind farms are much larger, comprising 40 turbines each. The wind conditions at FINO 1 are now influenced from almost all sectors; only a narrow free sector remains to the NNE.

Approach

Effects on the wind conditions are investigated in terms of the 10 min turbulence intensities (filtered for stable conditions) and the spectral content of the wind speeds recorded over a 6 month period. The turbulence intensities are compared with data from previous years for signs of significant trends that could be associated with the new wind farms.

Main body of abstract

The influence of the Alpha Ventus wind farm can clearly be seen in the turbulence intensity data. The close proximity of the turbines to the platform means that the wakes from individual turbines (or lines of turbines in the case of AV 4-6) can be identified separately. By contrast however, the greater distance of the Borkum Riffgrund I and Trianel Borkum wind farms means that individual wakes are not as clearly identifiable. Instead, the overall turbulence spectra in the wind data, especially under stable atmospheric conditions, need to be investigated to identify turbulence scales that can be associated with the wind farms.

An influence on the mean wind speed, as has been shown to exist for Alpha Ventus, requires a long measurement period and cannot be claimed on the basis of less than a 1 year period, especially when no uninfluenced reference wind speed exist.


Conclusion

The presence of wind farms near FINO 1 has a measureable influence on the wind speeds. With the construction of large wind farms to the west, the wind field at FINO 1 can no longer be considered representative of the overall wind conditions in the North Sea. Instead, the measurements now represent a local condition within the surrounding wind farm clusters. With the ongoing construction of large wind farms in the North Sea, the wind field is becoming increasingly heterogeneous and new approaches to quantifying this wind field are required.


Learning objectives
The work demonstrates how wind conditions at FINO 1 have changed as a result of the new wind farms to the west of the platform, and how the effects differ from those resulting from Alpha Ventus which is located very much closer. The work also presents a number of different approaches to assessing or identifying these wind farm wake effects ranging from the simple turbulence intensity parameter to a more involved spectral analysis of the turbulent content.