Research Student Project
Supervisor name & contact details:
Aidan Duffy
Civil and Structural Engineering
aidan.duffy@dit.ie
https://sites.google.com/site/aidanduffycv/
Colin Spain
Head of Energy Markets
Gaelectric Holdings Limited
http://www.gaelectric.ie/
Research Centre Name and Website (if
applicable)
Dublin Energy Lab
www.dit.ie/dublinenergylab/
Please indicate if the intention is to transfer
from the Masters programme to the PhD
programme (if applicable)
PhD only.
Please indicate if the project is suitable for a
self-funded student
Yes
Funding Agency
DIT (Fiosriagh EPS)/Gaelectric Holdings Ltd.
Scholarship Details
€16k p.a.
Subject Area
Energy Modelling
Title of the Project
Short-term Wind Farm Power Forecasting in
Irleand
Project Description (max 300 words)
The Irish electricity market is currently being redesigned and will place significant additional
financial risk on wind energy producers which must develop accurate methods for forecasting
day-ahead hour-by-hour energy output. A variety of academic and commercial statistical,
phycisal and hybrid electricity forecasting models exist. However, some forecasting techniques
are more suitable for different terrain types or weather events (such as extreme events).
However, to date no detailed comparative analysis has been carried out on the suitability of
different forecasting models for the full range of site and weather characteristics such as those
experienced in Ireland and other similar climates. This work involves using data from Gaelectric’s
wind farms and wider wind data on a system-wide basis to undertake a comparative analysis of
power forecasting models and quantify their uncertainty with respect to forecast consistency,
quality and value under different conditions. Consumer demand forecasting will also be carried
out using weather and electricity consumption patterns. New optimisation methods will be
developed to identify the best-preforming model when subject to different weather, technology
and topographical characteristics. The work will be carried out in close collaboration with
Gaelectric’s electricity markets team based in their Dublin office.
Methods will include:



design of energy and climate measurement and monitoring programme for wind farm
sites
choosing wind forecasting datasets
working closely with the Gaelectric Wind Technical team to model power output based
on:
- time-series models which use wind or electrical power time-series data to
estimate immediate short-term power resources;
- physical models which employ meso-scale (2-5km) weather forecast data from
numerical weather prediction (NWP) models to forecast wind resource at a
particular location; and
- statistical models which use statistical relationships between NWP data and
power output to estimate future power outputs.
Please indicate the student requirements for this project
The successful candidate will be an enthusiastic, self-motivated person who has a background in
engineering, physics, meteorology, statistics or a suitable related discipline. The successful
candidate will have experience of statistical and/or physical modelling of stochastic systems,
preferably with experience in the field of weather forecasting, energy markets or wind energy.
The successful candidate will persistent, self-disciplined and have excellent written and oral
presentation skills. The candidate will have a first class honours or 2.1 degree (or equivalent)
from a recognised third-level institute; masters students are also eligible to apply.
Deadline to submit applications (only for
funded projects)
March 31st 2015