High-Resolution Stochastic Demand Modelling for Low-Carbon Energy Systems PhD
- Mechanical, Electrical and Manufacturing Engineering
- Entry requirements:
- 3 years
- 6 years
- Reference number:
- Start date:
- 01 April 2019
- UK/EU fees:
- International fees:
- Application deadline:
- 10 September 2018
in the UK for research quality
in the UK for Mechanical Engineering
The Complete University Guide 2018
of 2 Queen's Anniversary Prizes
Loughborough University is a top-ten rated university in England for research intensity (REF2014) and an outstanding 66% of the work of Loughborough’s academic staff who were eligible to be submitted to the REF was judged as ‘world-leading’ or ‘internationally excellent’, compared to a national average figure of 43%.
In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career.
Efficient design and operation of low-carbon energy supply systems requires detailed and accurate quantification of energy demands. Historic recorded data can provide a useful starting point but technologies and usage patterns are set to change significantly with, for example, the introduction of electric vehicles and electrification of heating. The temporal and geographic correlation of these demands is critical to the operation of electricity networks and techniques to accurately predict these highly variable demands are required in the planning of efficient and reliable systems. This PhD project will aim to develop high-resolution stochastic energy demand modelling techniques, building on CREST's strong track record in this area.
Primary supervisor: Dr Murray Thomson
Secondary supervisor: Dr Andrew Cross
Find out more
To find out more about the School of Mechanical, Electrical and Manufacturing Engineering, please visit our website.
- Eoghan McKenna and Murray Thomson (2016) "High-resolution stochastic integrated thermal-electrical domestic demand model", Applied Energy, http://dx.doi.org/10.1016/j.apenergy.2015.12.089
- Ian Richardson and Murray Thomson (2012) "Integrated simulation of photovoltaic micro-generation and domestic electricity demand: a one-minute resolution open-source model", Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, http://dx.doi.org/10.1177/0957650912454989
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in a strongly numeric science or engineering subject.
A relevant Master’s degree and/or experience in one or more of the following will be an advantage: energy, engineering, computing.
All students must also meet the minimum English Language requirements.
Fees and funding
Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment. Special arrangements are made for payments by part-time students.
This is an open call for candidates who are sponsored or who have their own funding. If you do not have funding, you may still apply, however Institutional funding is not guaranteed. Outstanding candidates (UK/EU/International) without funding will be considered for funding opportunities which may become available in the School.