Security and Reliability Studies for Smart Power Networks

Institution: University of Manchester

Dept/School/Faculty: EPSRC Centre for Doctoral Training in Power Networks

PhD Supervisor: Dr K Kopsidas

Co-Supervisor: Prof S Rowland

Application Deadline: Applications accepted all year round

Funding Availability: Funded PhD Project (European/UK Students Only)

Student background required: 

Candidate should have very good programming skill on Matlab and/or DIgSILENT. A very strong knowledge on mathematical problem solving ability and modelling is required. 

Benefit to / Impact on Industry: 
The successful completion of the project will increase the power transfer capability and reliability of networks providing higher quality of supply. In addition will provide increased observability of the status/utilisation of their (overhead line and underground cable) assets. 

What novelty will the student base their PhD on? 
New method for planning and operation of (transmission/distribution) Power Networks based on the inclusion of condition monitoring data. Development of new modelling processes within a widely used by the power industry software package. 

Project overview: 
The aim of the proposed project is to develop a holistic real time thermal rating model for overhead lines (OHL) and underground cables (UGC) that considers the effects of the increasing uncertainty of weather and load data as the forecast moves into the future. Consequently, appropriate temporal and spatial weather forecasting methods will be implemented into a power network model that considers system-wide thermal ratings for the OHL and UC. The evaluation of this model will be performed on power flow network analyses that will consider demand side management, storage (and other Smart Grid) technologies to identify network’s security/reliability as a result of weather uncertainty and components (OHL, UGC) operational history. Results of the project will improve current power utility practices on operation, monitoring and maintenance of OHL and UGC assets. 

Outline Proposed Project Plan: 
Year 1: Taught courses and preparatory study 
Year 2: Learn design properties for overhead lines and underground cables that affect their power transfer capacity and investigate their ageing due to electrical and thermal stresses and create relevant models. Examine current forecasting algorithms and their implementation. Development of the models/algorithms on Matlab and Excel tool based on input and output data. 
Year 3: Implementation of 1st year’s models/algorithms within a network-wide modelling process using Matlab. The build models should interpret network power flow and reliability data as well as smart grid technologies (e.g., DSM, storage, FACTS…). Case studies will be produced indicating the effect of real time rating models and forecasting errors. 
Year 4: Creation of the developed modelling processes within DIgSILENT PowerFactory which is a tool used frequently by the power industry. 

References:

This project is funded by EPSRC, the University of Manchester and our Industry partners. Funding is available to UK candidates. EU candidates are also eligible if they have been studying or working continuously in the UK for three or more years (prior to the start date of the programme). The successful candidates will have their fees paid in full and will receive an enhanced maintenance stipend. 

See here for information on how to apply and entry requirements: www.power-networks-cdt.manchester.ac.uk/study/projects-apply