High-Resolution Stochastic Demand Modelling for Low-Carbon Energy Systems - Ref: MTUF2018

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.

Entry requirements
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.

How to apply
All applications should be made online. Under programme name select Electronic, Electrical and Systems Engineering. Please quote reference number: MTUF2018