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PhD Studentship: Fast Optimisation of Wind and Tidal-Stream Turbine Arrays

The University of Manchester

Qualification Type: PhD
Location: Manchester
Funding for: UK Students, EU Students
Funding amount: £18,622
Hours: Full Time
Placed On: 10th October 2023
Closes: 28th April 2024

This is a 3.5 year PhD Studentship  which will cover fees and stipend set at the UKRI rate (£18,622 in 2023/24). This project is open to UK residents and EU residents who have settled status or pre-settled status.

The successful candidate will have:

  • a first-class degree in Engineering, Maths or Physics;
  • strong programming ability in at least one of C++, Fortran or Python;
  • demonstratable skills in mathematical fluid dynamics.

Aim

To create a fast, efficient, validated software tool for the layout of wind or tidal-stream turbine arrays.

Background

Wind turbines now generate more than a quarter of UK electricity. They are at the forefront of the bid to replace existing fossil-fuel plant and generate additional electricity for transport and domestic heating. Tidal-stream turbines offer the prospect of clean, extensive, predictable energy, due to the high density of water, regularity of tides and availability of sites.

Individual turbines typically generate only a few MW and so economics of scale favour operation of multiple units in an array. Because of device-interaction, total array generation depends on layout and individual operating points.

The simplest design tool for a single turbine is blade-element momentum theory (BEMT).  Based on the momentum principle and aerofoil theory this predicts thrust and power and is fast and accurate near design conditions. Multiple turbines, however, interact. For windpower this means windspeed reduced in turbine wakes. In tidal streams, however, blockage due to finite depth may provide enhanced bypass flow to judiciously placed downstream devices.

CFD with accurate meshing of individual turbines is prohibitively expensive for whole arrays. Replacing turbines by actuator disks or rotating actuator lines allows whole-array simulations, but is too expensive for optimisation requiring many simulations with different configurations. Models must be fast and flexible, with limited CFD simulations to validate the approach. Stansby and Stallard (2016) proposed using superposition of analytical self-similar wake profiles to optimise either power or cost for arrays, together with gradient-based optimisation with a modest number of free variables (turbine locations). The projected research will use modern non-gradient approaches to optimisation and will add individual turbine operating points to the optimisation variables.

We strongly recommend that you contact the supervisor(s) for this project before you apply; The Email addresses for Dr David Apsley and Dr Gregory Lane-Serff are David.apsley@manchester.ac.uk and Gregory.F.Lane-Serff @manchester.ac.uk

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