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

We are pleased to offer a full 3.5 year studentship in support of this PhD that will pay Home tuition fees and provide a tax-free stipend at the standard UKRI rate (£19,237 in 2024/24) to cover living costs. European nationals who hold settled or pre-settled status under the EU Settlement and are eligible for Home fee status are very welcome to apply. The proposed start date is negotiable: 1 September 2024 - 1 January 2025.

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 congurations. 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.

Proposed Research

The project will use BEMT and an analytical wake-superposition approach to optimise the layout of arrays. Specifically it will:
(1) allow for arbitrary placement of individual turbines within a bounded region;
(2) control the operating point (speed and blade pitch) of individual devices;
(3) for tidal turbines, incorporate advanced blockage corrections;
(4) use modern evolutionary algorithms – for example, particle swarm optimisation or genetic algorithms – for optimisation;
(5) allow for different objective functions, including net array power or cost.

The software tool will be written in a modern high-level programming language (Fortran, C++ or Python), with an accessible user interface.

Applicants should have, or expect to have, a first-class honours degree or an MSc degree in Engineering, Mathematics or Physics.

Please contact the main supervisor, Dr David Apsley, before you apply: david.d.apsley@manchester.ac.uk

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