Fast Optimisation of Wind and Tidal-Stream Turbine Arrays

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.

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.

Funding

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 (£18,622 in 2023/24) 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. 

This project is also eligible for the Osborne Reynolds top-up Scholarship which provides an additional £1500 per year top-up to stipend for outstanding candidates. Successful applicants will be automatically considered for this top-up.

None UK funding

The funding is open to overseas applicants if they are able to source additional funding for tuition fees. Please see Funding opportunities for postgraduate research at The University of Manchester. You may be eligible for the Dean’s Doctoral Scholarship but you will need your supervisor to nominate you for this award. 

We are also happy to consider International applicants who hold additional funding to cover the balance of fees to the higher International fee rate.

Eligibility

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. 

Before you apply

We strongly recommend that you contact the supervisors for this project before you apply.

How to apply

How to apply

Apply online through our website: https://uom.link/pgr-apply-fap

When applying, you’ll need to specify the full name of this project, the name of your supervisor, if you already having funding or if you wish to be considered for available funding through the university, details of your previous study, and names and contact details of two referees.

Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.

After you have applied you will be asked to upload the following supporting documents:

• Final Transcript and certificates of all awarded university level qualifications
• Interim Transcript of any university level qualifications in progress
• CV
• Supporting statement: A one or two page statement outlining your motivation to pursue postgraduate research and why you want to undertake postgraduate research at Manchester, any relevant research or work experience, the key findings of your previous research experience, and techniques and skills you’ve developed. (This is mandatory for all applicants and the application will be put on hold without it).
• Contact details for two referees (please make sure that the contact email you provide is an official university/work email address as we may need to verify the reference)
• English Language certificate (if applicable)

If you have any questions about making an application, please contact our admissions team by emailing FSE.doctoralacademy.admissions@manchester.ac.uk. 

Equality, diversity and inclusion

Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact.

We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.

We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).