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Projects: Projects for Investigator
Reference Number NIA_NGET0128
Title Clustering effects of major offshore wind developments
Status Completed
Energy Categories Renewable Energy Sources(Wind Energy) 10%;
Other Power and Storage Technologies(Electricity transmission and distribution) 90%;
Research Types Applied Research and Development 100%
Science and Technology Fields ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 100%
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Project Contact
No email address given
National Grid Electricity Transmission
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 April 2014
End Date 01 April 2016
Duration 24 months
Total Grant Value £319,000
Industrial Sectors Power
Region London
Programme Network Innovation Allowance
Investigators Principal Investigator Project Contact , National Grid Electricity Transmission (100.000%)
Web Site http://www.smarternetworks.org/project/NIA_NGET0128
Objectives 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. 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.
Abstract The expansion in offshore wind generation coming with the round 3 projects is bringing particular uncertainty for strategic and operational planning. Wind farms of the scale now planned influence the lower atmosphere sufficiently to impact the performance of adjacent farms, therefore the power generation characteristics of a cluster of wind farms (such as that planned for Dogger Bank) are largely unknown. The current generation of wind power forecasting tools, whilst representing the best commercially available, continue to have many shortcomings with regards to accurately predicting unusual weather conditions. This will be compounded by the larger investment into construction of the larger wind farms. The manner in which turbines interact with the air-flow translate into significant uncertainties and costs for the GB National Electricity System Operator with regards to reserve planning, balancing and constraint management costs. Research This project will apply a mesoscale numerical weather prediction model to explore the atmospheric influence of the planned offshore wind farms. It is proposed to use WRF (Weather Research Forecasting), a state of the art modelling tool. This project will be structured in three work packages, aligned to the objectives described below: WP 1 - Wind farm parameterization: this work package will review the parameterization approaches currently applied within WRF, review state of the art alternatives, and collect data to enable offline investigation. WP 2 - Characterisation of the offshore cluster extreme events: this work package will use the MERRA (Modern Era-Retrospective Analysis for Research and Applications) dataset to identify extreme events, apply the WRF model to the Dogger Bank region of the North Sea and determine the power characteristics of the planned cluster of wind farms. WP 3 - Enhance the predictability of extreme events: this work package will apply statistical techniques to classify the boundary layer type (and thus near surface wind-speed characteristics) for each extreme event; determine the relationship between the boundary layer type and the synoptic conditions; and investigate the scope for improving the predictability of the extreme events.Note : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above
Publications (none)
Final Report (none)
Added to Database 10/07/18