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Clustering Effects of Major Offshore Wind Developments

Network Operator:
National Grid Electricity Transmission
David Lenaghan (.box.innovationtransmission@nationalgrid.com)
Starts - Ends:
04/2014 - 04/2016
Estimated Expenditure:
Funding Mechanism:
Network Innovation Allowance
Research Area:
Environment / Low Carbon
Core Technology(ies):
Low Carbon Generation
Project Documents:
The project will focus on the cluster of wind farms planned at Dogger Bank in the North Sea. This is the largest of the round 3 offshore zones, with an area of 8660 km2, and could see as much as 9 GW of capacity installed in a number of separate wind farms.

This project will investigate the variability of the wind resource within this cluster taking into account the wake effects of the individual turbines and the shadow effect of neighbouring farms. This will be achieved through drawing on established models, with central assessment developed using the WRF system. Based on the results of this analysis, the power characteristics of the individual wind farms or the cluster of farms will be derived for a number of meteorological conditions, defined by parameters such as wind direction, wind speed, atmospheric stability and turbulence.

By considering how the cluster of wind farms will be connected to the GB power system, this approach could be applied to identify any possible network stress points. To achieve this, a full analysis will be performed to determine the power characteristics at each of the connection points for a number of extreme events, identified in the previous project TAO 22260, ‘UK-wide wind power resource: Extremes and variability’:

  • Rapid changes in wind-speed affecting power output (ramping)

  • Persistent low wind producing low power output (low wind conditions)

  • Very-high wind events (exceeding wind-turbine safety cut-out)

For each of the extreme events, previously derived techniques (e.g. Sinclair (2009)) will be used to classify the boundary layer type,n based on parameters such as stability, wind speed, wind direction, turbulence and boundary layer height. Prior observations will then be used to determine the relationship between the weather type associated with the extreme events and the characteristics of the corresponding boundary layer. For example, the winter peak demand is likely to occur in anti-cyclonic conditions with easterly flow; by considering the associated boundary layer type the impact of clustering large wind farms can be investigated using the WRF modelling. By considering different boundary layer types the potential will be explored to extend the analysis to determine whether one type is more easily forecast than others, however, at present there are significant scientific unknowns to overcome.

The objectives of the project include the following;

  • Reduce reserve planning, balancing and constraint management costs through the modelling and analysing how clusters of turbines interact in different boundary layer atmospheric conditions.

  • Identifying stress point on the network by using the WRF alongside established models to assess the power characteristics of a range of extreme events.

  • Generate knowledge from this study which can be combined with network models and climate weather data to provide added certainty of various modelling techniques when considering future investment schemes and operational running arrangements.
Expected Benefits:
The success criteria of the project will be based on the following:

  • A preliminary report to document the assessment of wind farm parameterisation in mesoscale models

  • A secondary report to identify characteristics of offshore cluster extreme events.

  • A final report which established the development of atmospheric indicator set to enhance the predictability of extreme events.
Project Document(s)
    Project Registration Document  Posted on Jul 27, 2014

     Download PDF Document (94Kb)

Progress Report(s)
    Project Progress Report 2015  Posted on Jul 30, 2015

     Download PDF Document (59Kb)

Closedown Report(s)
    Project Closedown Report  Posted on Jul 28, 2016

     Download PDF Document (81Kb)