Applications of Maths in the Energy Sector
Jun 25, 2009
University of Strathclyde
Organisers
| Name |
Institution |
| Bridle, Helen |
ICMS |
| Mulholland, Tony |
University of Strathclyde |
Scotland has a thriving diverse energy sector with the ambitious target, set by the Scottish Executive, to generate 40 per cent of its electricity from renewable means by 2020. In addition to the extensive tidal, wave and wind energy resources available in Scotland, new oil fields are still being discovered and Scotland is expected to retain its place as a global leader in oil and gas for many years. Maths has been widely used in the energy sector including:
- Simulations of flows in reservoirs in the oil and gas industry
- Forecasting of oil reserves to determine whether exploitation is economically feasible
- Condition monitoring of the transmission grid to assist in operational decisions
- Simulation of wind farm output
- Forecasting electricity demand
- Quantification of energy savings depending upon ventilation strategy in low energy buildings
More examples of applications of maths in the Energy sectors can be found on the Industrial Maths KTN webpage under Sectors and Energy and Utilities.
This event will be a full day workshop hosted by the University of Strathclyde.
The day starts with coffee and registration at 11.00 in the foyer outside room P.515 (first floor) in the Graham Hills Building. A map showing the location can be found on http://www.strath.ac.uk/maps/grahamhillsbuilding/
Programme
See Presentation section below for the details of each talk.
11:00 Registration / Coffee
11.30 Welcome & Introduction
(Helen Bridle, ICMS and Tony Mulholland, University of Strathclyde)
11.45 Overview of Applications of Maths in the Energy Sector
12:00 Industry Problem 1: Optimising the ratings, cost targets and operating strategy for energy storage at a wind farm
13:00 Buffet Lunch
14:00 Industry Problem 2: Sensor reduction in down-hole linear permanent magnet machines
Download copy of Industry Problem 2 here.
15:00 Coffee
15:30 Industry Problem 3: Understanding marine turbulence for development of robust tidal turbines
Download copy of Industry Problem 3 here.
16:30 Mechanisms for funding collaborations
(ICMS, Bridging the Gaps, Smith Institute, RenewNet)
Download copy of ICMS presentation on funding mechanisms.
Discussions will continue over dinner.
Download report of all discussions here.
Presentations:
| Presentation Details |
|
| Brown, Deryck |
| Sensor reduction in down-hole linear permanent magnet machines |
View Abstract
Hide Abstract
 
|
Traditional applications of a linear permanent magnet motor have required
accurate position feedback to the variable-speed drive to control the speed and
position of the motor. This feedback is often provided by an optically-based
sensor that requires many signal wires between the sensor and the drive.
In our application, we aim to use a linear permanent magnet motor to power a
pump that will be located 3 kilometres down a natural gas well. Whilst the
linear motor and pump are deployed down-hole, the drive unit remains on the
surface, and is connected to the motor using a four-conductor cable that
consists of the three motor supply cables and one communications cable. In this
environment, both the optical nature of traditional position sensors, and the
requirement for many connecting wires are impractical for a cost-effective and
reliable pumping system.
One possible approach to controlling the motor is an alternative position sensor
that can withstand the extreme environment, and send its output signal over the
single communications wire to the surface, where it can be used to generate the
normal feedback signals to the drive. However, this solution has several
disadvantages, not least that a failure of this sensor or its connecting cable
would render the entire system inoperative. A better solution would replace this
down-hole sensor with various measurements taken at the surface that could
estimate the motor position.
Recent work on permanent magnet motors has considered the theoretical aspects of
various sensor-reduction techniques. These techniques use a mathematical model
to estimate the motor position, using various parameters including the voltage,
current and induced back EMF on each of the three motor supply conductors.
Unfortunately, this work has tended to focus on rotary rather than linear
motors, and has ignored the problems that would arise from the large distance
between motor and drive in our application.
Our problem is to develop a suitable mathematical model of sensor reduction that
can be applied to our linear motor over a long cable length, which could be used
in practice.
|
| Hunter, Ray |
| Optimising the ratings, cost targets and operating strategy for energy storage at a wind farm |
|
View Abstract
Hide Abstract
|
Wind energy is largely stochastic although it has clearly defined
statistical attributes and general daily and seasonal trends.
For much of the time, power levels from a wind farm are well below rated
power, although in annual terms a significant proportion of overall
energy is delivered at higher powers.
This results in relatively poor use being made of grid assets where
asset usage broadly matches the capacity factor of the wind farm.
However, grid assets(available capacity) are often in short supply.
Storage is seen as a method of smoothing the delivery of power from a
wind farm to a network which would make better use of network capacity -
rather than linking a 30MW wind farm to the network using a 30MW rated
connection, one idea might be to only use 20MW of network capacity but
to have a local energy store with a 10MW transfer capacity.
The problem I'd like to pose is:
for a given financial structure epitomised by an energy income tariff
and by a network capacity charge, what would be the optimum energy
capacity and power transfer ratings for the store and what control
algorithm should be employed. As a partial corollary, what should the
cost targets be for energy storage devices before they could generally
be regarded as being commercially attractive in this application.
All of this could be sorted out using oodles of time domain simulation,
but is there a more analytical, statistical approach that will give
greater insights?
|
| Thomson, Mat |
| Understanding marine turbulence for development of robust tidal turbines |
|
View Abstract
Hide Abstract
|
Tidal stream devices offer an attractive source of renewable energy due
to the predictable nature of tidal currents. But whilst the prediction
of the mean tidal flow velocity is an established science and can
provide estimates of steady power capture and device loadings, the
understanding of the higher frequency flow fluctuations is limited.
If cost-effective design solutions are to be achieved then it is a
prerequisite to have a detailed description of the environmental
conditions. Initial analysis at typical sites suggests that the level
of ambient turbulence intensity will have a major impact on device
loading and performance. Hence there is a need for a good understanding
and robust representation of the incident flow on to the device.
The problem is twofold. Firstly we need to better understand the
intensity, length scales, frequency spectrum and spatial correlation
characteristics of the turbulent flow, so that we can then go on to
develop better representations as the basis of more reliable
calculations of the hydrodynamic loading of tidal stream devices.
The emerging tidal energy industry is reliant upon the input of expert
knowledge from many different disciplines and there is a clear need for
collaborative R&D to move this new area of science forward.
|
Participants
| Name |
Institution |
| Barlow, Euan |
University of Strathclyde |
| Brand, Craig |
ScottishPower |
| Bros-Williamson, Julio |
Edinburgh Napier University |
| Brown, Deryck |
Zi-Lift Ltd |
| Coles, Andrew |
University of Strathclyde |
| Coles, Christopher |
University of Strathclyde |
| Copeland, Graham |
Strathclyde University |
| David, Hall |
Plurion Ltd |
| Estrada, Ernesto |
University of Strathclyde |
| Fletcher, John |
University of Strathclyde |
| Fletcher, Roger |
University of Dundee |
| Grist, Eric |
Environmental Research Institute (Marine and Tidal) |
| Grothey, Andreas |
University of Edinburgh, School of Mathematics |
| Gupta, Meetu |
University of Strathclyde |
| Halliday, Sam |
ThinkTank Maths Ltd |
| Harper, Nigel |
Energyinvest Group Ltd |
| Hill, David |
University of Strathclyde |
| Hunter, Ray |
Renewable Energy Systems Limited |
| Junaidi, Haroon |
Edinburgh Napier University |
| Khalid, Hassan |
University of Strathclyde |
| Kirkby, Adrian |
Centrica Storage Limited |
| Mathis, Angela |
ThinkTank Maths Ltd |
| Mottram, Nigel |
University of Strathclyde (Tidal) |
| Natarajan, Sundararajan |
University of Glasgow |
| Rajaniemi, Hannu |
ThinkTank Maths Ltd |
| Richards, Andrew |
Heriot-Watt University |
| Rix, Oliver |
Redpoint Energy |
| Rose, Alasdair |
EPSRC |
| Szpruch, Lukasz |
University of Strathclyde |
| Thomson, Mat |
Garrad Hassan |
| Tracy, Philip |
Cairn Energy PLC |