Funded PhD Case Studentship with National Grid (Available to start from January 2016)
Mathematical Baseline and error Detection Techniques for the Analysis of Unaccounted For Gas (UAG)
Management of natural gas pipelines is a difficult and complex task. The network operator must monitor the flow through the network of pipelines to correctly allocate costs to each user, guarantee safety and reduce emissions. The balancing of input/output should be a trivial task since leakages are unlikely but the reliability of measuring equipment at both ends of the system means that there is often a difference - the Unaccounted for Gas (UAG).
The aim of this project is to use advanced stochastic and statistical theory to build up a dynamic model for expected measurement error, which will depend on the flow rates through the system. Using this model, we will be able to build up an idea of what is normal so that unexplained errors can be quickly identified. Once measurement errors are understood, we will be able to use Mathematical Finance techniques to determine optimal investment opportunities in the operation of the network.
Working closely with National Grid UK, the student will have access to a full set of data and visits to the measurement stations. The students will need a strong background in both applied mathematics and statistics.