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Durham University

Durham Energy Institute

Wind Energy, Turbomachinery and Data-mining postgraduate research topics

PhD opportunities at Durham University.

Below you can find a selection of PhD topics connected to wind energy. If you are intersted in exploring a different topic please do get in contact either directly with the researcher you would like to be your supervisor or with evelyn.tehrani@durham.ac.uk. You can find out about our wind energy expertise and research at Durham University on our Wind Energy Research pages.

Find out about PhD opportunities through our Aura CDT

Funded PhD scholarships in offshore wind energy and the environment

Aura Centre for Doctoral Training Aura is a collaboration between major companies in the offshore wind industry, leading academic institutions and government and non-governmental organisations.

Aerodynamics of Vertical Axis Wind Turbines [PhD on offer at ECS: Dr Grant Ingram]

Infrastructure planning and operation for large-scale offshore wind farms [Dr Behzad Kazemtabrizi and Dr Christopher Crabtree, Engineering] With the recent advances in wind turbine design and manufacture resulting in larger wind turbines, the offshore wind industry is becoming more competitive. However there exists the problem of integration of such high capacities to the conventional utility grid in a safe, reliable and cost-effective manner. This research will expand on previous research at Durham by looking at infrastructure as well as operational planning decisions that may lead to improving wind farm performance and reliability.

Coordination of power converters in a wind farm to improve the total reliability of the system [Dr Mahmoud Shahbazi, Engineering] The aim of this project is to develop methods and simulations to show how the total reliability of the wind farm can be optimised, by using advanced sensing technologies and IoT to provide timely and detailed failure warning.

Coordinated Distributed Control in Offshore Wind Farms [Dr Peter Matthews, Engineering]

Data Mining Wind Farm Operational and Maitenance Data [Dr Peter Matthews, Engineering]

Design, Test and Build of Prototype Turbine Geometries: [Dr Grant Ingram, Engineering and Computer Sciences] Durham has a long tradition of turbomachinery research and we have a well known test case for turbomachinery blading known as the Durham Cascade. A number of innovative ideas have been first tested in this cascade, some of which are flying around in aeroplanes. One idea that is particularly innovative is that of tip gap profiling which we have recently completed some pilot work in the cascade. This project will involve design using 3D CFD, building of the prototype and then testing the prototype in the wind tunnel. The student will acquire skills in both experimental and computational modelling.

Experimental Measurements of Loss Mechanisms in Turbines [Dr Grant Ingram, Engineering]

Failure of Power Electronic Components in Wind Turbines [Dr Christopher Crabtree, Engineering]

Investigation of UK wind generation temporal and spatial variability. [Dr Peter Matthews and Dr Donatella Zappala, Engineering] Student background/skills: good background in statistics and data mining.

Automated data integration for wind turbine generator fault detection and diagnosis. [Dr Christopher Crabtree, Dr Katharine Brigham and Dr Donatella Zappala, Engineering]. Student background/skills: engineering degree and a good background in signal processing, statistics and machine learning.

Monitoring wind turbine drive train using non-contact shaft torque measurements [Dr Christopher Crabtree and Dr Donatella Zappala, Engineering] Student background/skills: engineering degree with previous experience of experimental work and a good background in signal processing.

Offshore geotechnics (foundations, cabling, anchors, soil models for soft sediments) (MRes or PhD) [Dr William Coombs, Engineering] Essential skills/knowledge: good first degree in civil/mechanical engineering; experience of implementing scientific models/equations into computer code; excellent written and oral communication skills; knowledge of numerical analysis techniques such as the finite element method. Desirable skills: knowledge in the area of non-linear mechanics (material or geometric);

Fracture/fatigue (wind turbine structures/monopiles, composites) (MRes or PhD) [Dr William Coombs, Engineering] Essential skills/knowledge: good first degree in civil/mechanical engineering; experience of implementing scientific models/equations into computer code; excellent written and oral communication skills; knowledge of numerical analysis techniques such as the finite element method. Desirable skills: knowledge in the area of non-linear mechanics (material or geometric); knowledge in the area of fracture mechanics

Structural optimisation (wind turbine blade cross section (MRes or PhD) [Dr William Coombs and Dr Stefano Giani , Engineering] The topic of this project is to study ways to optimize the structural design of the blades to reduce their weight and increase their reliability. This project will deliver novel numerical techniques that allow engineers to better design wind turbine blades. In the scope of this project, the methods are applied to blade designs and the results of the optimization process are analysed and assessed. Essential skills/knowledge: good first degree in civil/mechanical engineering; experience of implementing scientific models/equations into computer code; excellent written and oral communication skills; knowledge of numerical analysis techniques such as the finite element method. Desirable skills: knowledge in the area of non-linear mechanics (material or geometric); knowledge in the area of fracture mechanics (if appropriate for the subject area)

Flow Modelling over Terrain for Accurate Thermal Ratings of Cables: [Dr Grant Ingram, Engineering and Computer Sciences] In recent years at Durham we have been building up expertise of modelling the flow over terrain to improve the prediction of the thermal load on cables. The work will involve learning how to use advanced computational packages to model the flow and then link this to statistical models of the available data. In previous years we have ran simulations of Durham City and have developed the capability of including building data into our simulations. The student will run further simulations with terrain and weather data to see where the model works and where improvements are needed. The first improvement required is to add a shear stress boundary condition to the model. A second challenge is data reduction - these models produce vast quantities of data and being able to reduce the data to a short meaningful collection of variables. Improved flow modelling is important as it allows utilities to exploit the synergy between increased wind turbine output and increased cooling over power cables.

How can renewable technologies be tied into local forms of ownership, democratic governance, and community-benefit? Case studies in Durham county, and/or Scotland will provide examples of forms of community benefit that can be achieved, and outline the barriers, challenges and structures around local economic development. NB Scottish planning law now includes a presumption in favour of community benefit for installations such as wind farms, which has led to a number of interesting developments. [Professor Sandra Bell & Prof Simone Abram, Anthropology]

Morphing Structure for Turbine Diffusers: [Dr Grant Ingram, Engineering and Computer Sciences] The application of variable geometry structures such as flaps, slats etc is common in aircraft but is much less widely used in the power generation industry. However new materials based on composites make this idea a feasible alternative. This project is to carry out fluid and structural modelling on the idea of morphing diffusers with the aim of determining some realistic designs and estimates using off the shelf engineering tools. The student would be expected to be learn and use packages such as Fluent, Abacus etc. during the project and relate the results of these packages to the basic engineering science. The output would be some candidate designs that could then be tested to prove the concept, if the scope of the project is large enough then a build and test programme could be included in the project.

Optimising and calibrating steam turbines through adjoint-based, backward-in-time, high-performance computing algorithm [Dr Stefano Giani and Dr Tobias Weinzierl, Engineering and Computer Sciences] This project will deliver novel numerical techniques that allow engineers to better design turbines that meet efficiency, flexibility and ecological requirements of the future. In order to integrate renewable energy sources into existing power grids, it is necessary to increase the speed at which traditional power stations can change the regime to compensate for renewable energy production fluctuations.To achieve this, we combine discontinuous Galerkin methods with optimisation strategies that solve partial differential equations backwards in time plus groundbreaking high performance computing ingredients. While the project will make contributions in all three methodological areas, its major impact results from the fusion of these three techniques.

Perceptions and attitudes towards wind power in local communities [Dr Christopher Crabtree, Engineering and Computer Sciences and Dr Simone Abram, Anthropology]

Real-time monitoring of wind turbine blade alignment using laser displacement and strain measurement (PhD) [Dr Qing Wang, Engineering] Wind turbine blades operate in a dynamic environment, where they operate at different pitch angles, with differing wind speed, and often with an oncoming wind varying in axial velocity and angle over the height of the turbine. As such, each blade will experience a range of loadings, varying not only throughout the blade’s rotation but also span-wise along the radially axis of the turbine. Therefore, a turbine blade alignment process requires the blades to be able to move, yet still assess their alignment in terms of incidence to the hub (as opposed to pitch) even though each blade will, at an instantaneous moment in time, be under differing loading conditions.

The objective of this research is to establish whether a Laser Displacement Sensor (LDS) system and stain measurement system, designed to monitor WT blades, is more efficient than contemporary methods and, subsequently, provides early fault detection to reduce maintenance costs. In this way the mechanical operation, and therefore the aerodynamic design and loading predictions, of the turbine can be more accurately predicted and thus lead to greater optimisation and improved efficiencies.

The research will start with familiarisation of the features of the wind turbine, understanding the nature of the service requirement and reviewing different types of wind turbine systems. A laboratory test rig has been created in order to perform real-time wind turbine blade alignment. Students will be expected to understand the setting of the existing test rig, the laser measurement and strain measurement working principles, and assess and modify the test rig if necessary. A data acquisition system has been developed at Durham and the student is expected to be able to collect information on blade positional changes in relation to the hub and analyse the results in order to calculate the value of misalignment.

Sustainable and High Energy Efficiency Electrical Machines: [Christopher Donaghy-Spargo, Engineering and Computer Sciences] Rotating electrical machines play an important role in industry and in many specialist/demanding applications. High energy efficiency electric motors with low or no permanent magnet material are of great interest due to their inherent advantages over competing technologies. The permanent magnet machine, which typically utilizes expensive ‘rare earth’ magnets has been the focus of intensive research over the last decade; this PhD opportunity will explore the field of ‘reluctance motors’ which are rotating electrical machines that do not inherently contain permanent magnet material but yet provide an interesting alternative for a variety of applications. This PhD will investigate the advancement of the synchronous reluctance motor with a view to improving the energy efficiency and power factor of such machines as well as their general design and manufacture.

Wind Turbine Condition Monitoring using Power Converter Signals [Dr Christopher Crabtree ]

Wind Turbine Converter Reliability Assessment [Supervisors: Dr Christopher Crabtree and Dr Peter Matthews]

Examples of previous wind energy projects in the MSc New and Renewable Energy:

  • Flexible capacitive materials for structural health monitoring of wind turbine blades
  • Modelling of a modern offshore Wind Turbine Generator (WTG)
  • Wake Stability in Wind Farms
  • Daily Planning of Operations at a Wind Farm
  • The Aerodynamic Damping of Large Wind Turbine Blades during Fatigue Tests
  • Wind Energy Production based on Reliability of Different Wind Turbine Generator (WTG) Designs