Postgraduate Studentships
Proposed Project Title: Data Mining and Energy Forecasting with Increased Renewable Generation
Principal Supervisor: Prof Seán McLoone, Dr. Xueqin (Amy) Liu
Industrial Collaborator: System Operator Northern Ireland

Project Description:

Ireland has adopted a renewable power generation target stipulating that 40% of electricity will be produced from renewable sources by 2020. In order to achieve such ambitious targets Ireland is expected to have 6000 MW of wind power generation installed by 2020, with more than 2000 MW installed at present. However, the variability and uncertainty associated with wind power generation and the nature of the technology creates operational challenges. In such an environment, new, more intelligent tools are needed by the power system operator.

A major area of importance is the development of energy forecasts that can be used by the power system operator to schedule generation in a secure and economic manner. The focus of this project will be to develop ensemble energy forecasting models, that combine both physical models and statistical models. It is intended to produce an energy forecasting model for use in Northern Ireland, and that the resultant model will display the level of uncertainty, and confidence band associated with the forecast.

Objectives:

1. Conduct a literature survey on "state-of-the-art" energy forecasting methods
2. Investigate how the model can self retune, or continually learn, to improve accuracy
3. Quantify the uncertainty of energy forecasts vs. time horizon
4. Develop ensemble model combining data-driven statistical and physical forecasting methods
5. Investigate metrics for measuring energy forecast accuracy and uncertainty
6. Demonstrate model performance for Northern Ireland

Academic Requirements:

A minimum 2.1 honours degree or equivalent in Computer Science or Electrical and Electronic Engineering or relevant degree is required.

GENERAL INFORMATION

This 3 year PhD studentship, potentially funded by the Department for Employment and Learning (DEL), commences on 1 October 2015.

Eligibility for both fees and maintenance (£13,863 in 2014/15, 2015/16 TBC) depends on the applicants being either an ordinary UK resident or those EU residents who have lived permanently in the UK for the 3 years immediately preceding the start of the studentship. Non UK residents who hold EU residency may also apply but if successful may receive fees only.

Please note: DEL awards are available for Home and EU candidates only.

Applicants should apply electronically through the Queen’s online application portal at:
https://dap.qub.ac.uk/portal/

Further information available at:
http://www.qub.ac.uk/schools/eeecs/StudyattheSchool/PhDProgrammes

Contact detail

Supervisor Name: Prof. Seán McLoone, Dr Amy Liu 
Tel: +44 (0)28 9097 4125

QUB Address: Queens University of Belfast
School of EEECS
Ashby Building, 
Stranmillis Road, 
Belfast 
BT9 5AH

Email: s.mcloone<στο>qub.ac.uk; x.liu<στο>qub.ac.uk

Deadline for submission of applications is: 27 February, 2015

For further information on Research Area click on link below: http://www.qub.ac.uk/research-centres/EPIC/