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Conference programme 

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Poster session

Lead Session Chair:
Stephan Barth, Managing Director, ForWind - Center for Wind Energy Research, Germany
David Sudall University of Manchester, United Kingdom
David Sudall (1) F P Peter Stansby (1) Tim Stallard (1)
(1) University of Manchester, Manchester, United Kingdom

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Presenter's biography

Biographies are supplied directly by presenters at OFFSHORE 2015 and are published here unedited

David is currently in the second year of his PhD in the School of Mechanical, Aerospace and Civil Engineering at the University of Manchester, supervised by Prof. Peter Stansby and Dr Tim Stallard. His research interests concern hydrodynamics of turbine arrays to inform energy yield and design load prediction for wind and tidal turbines. In 2013, David graduated with first class honours from a MEng degree in Mechanical Engineering with Industrial Experience, also from the University of Manchester. He is currently supported by the Research Impact Scholarship which is awarded to outstanding graduates by the University of Manchester Alumni.


Energy yield for collocated offshore wind and tidal stream farms


In the UK, electricity generated from offshore wind turbines is expected to increase from 20 TWh/yr to 90 TWh/yr by 2030. Achieving this target will require large-scale deployment in water depths of 30-60 m. Tidal stream systems are at an earlier stage of development but could provide approximately 20TWh/yr. This project investigates the potential for reducing electricity generation costs for these technologies by deploying both types of turbine at the same location, on shared support structures. Energy yield from a co-located farm is estimated based on resource data and semi-empirical wake models of wake interaction to assess feasibility.


Energy yield for a wind farm was modelled using AWS OpenWind with a standard eddy-viscosity wake model and a generic 3MW turbine power curve. Wind resource data was from the UK Met Office Unified Model. Tidal farm yield was modelled using superposition of a self-similar wake model, based on prior experimental studies by the authors and here extended for yawed operation. A power curve for a 1 MW turbine was employed with tidal resource data sourced from the Forecasting Ocean Assimilation Model. Time histories of thrust and combined power were determined, from which the annual energy yield was obtained.

Main body of abstract

Time-varying power output has been estimated for a deployment of tidal turbines and wind turbines at a representative tidal stream site to assess combined energy yield. The MeyGen site in the Inner Sound of the Pentland Firth is considered as a case study. Phase 1c of this development is expected to comprise deployment of 20 No. 1MW tidal turbines located in an area approximately 1000 x 300 m. Energy yield has been determined for tidal and wind turbines deployed at this site with capacity ratio 4:3. By employing generic power curves, capacity factors of the tidal farm and wind farm when operating in isolation are 0.23 and 0.45, respectively. However, this is increased by reducing rated speed and increasing turbine number. The capacity factor for the combined system is then 0.33. Deployment of a wind farm at this tidal site thus increases the annual energy yield from the site by 147%, compared to operating the tidal turbines alone. It is seen that seasonal variation has greater impact on wind power output than tidal power output and hence the combined system shows reduced sensitivity to seasonal variations than operating a wind farm alone. However, there are challenges regarding the relative spacing of wind turbines to tidal turbines and how this impacts the support structure design, load conditions and feedback on energy yield and cost.


Energy yield from a co-located farm of wind and tidal turbines has been modelled to assess the potential for cost reduction offered by supporting both wind turbines and tidal stream turbines on a shared structure. Annual energy yield may be increased by up to 147% compared to operating tidal turbines alone. Seasonal variation of yield is reduced compared to wind turbines alone due to the predictable tidal cycle. Combining the two technologies can therefore enable increased MWh yield per support structure and hence cost reductions per unit of electricity. Challenges remain concerning the design of shared support structures.

Learning objectives
As a method of reducing the high cost of energy from wind and tidal stream systems, co-location of both turbine types at the same location, on shared support structures is considered. The combined energy yield is assessed based on documented performance models and resource data. The main outcomes are improved understanding of the mean and time-varying power output and awareness of some of the associated challenges.