alternative energy technologies Case study


Currently in the second year of his PhD, Stuart Walker, a Tidal Power researcher at the University of Sheffield, is focusing on the optimisation of the layout of farms of tidal turbines. He explains his project and how simulation tools fit in


My current work revolves around three-blade tidal turbines that are mounted down on the sea bed and installed in arrays, and how to minimise the wake from the first row as this has a big impact on the output of all the turbines behind. At this stage I am using a tank for experimental modelling and then later in the project will be doing CFD and computational modelling. My aim is to achieve an optimised layout for a small array of turbines, which could be used as a tool for developers looking at how best to arrange their turbines. My focus is on the support structure, rather than the blades, because until now these supports have all been a simple column. By investigating different shapes and ways of attaching the supports to the sea bed, I hope to optimise designs that will be location dependant. It’s interesting that people often assume that everything is now done on a computer and when I explain that my testing work is being done in a tank, they immediately question why I don’t


3MW design turns at around 13 revolutions per minute, necessitating a high pole count. Opera’s advanced solvers allow this high degree of periodicity to be leveraged, so that the numerical model can be a fraction of the size of the complete generator – significantly reducing simulation times. Tis is particularly important for BWP because it makes exclusive use of the 3D version of Opera, which is necessarily more computationally demanding than the 2D version. While many wind turbine designers employ two-dimensional simulation for the main components in a generator, and only use three-dimensional simulation, which is adequate when three-dimensional features such as the end turns on windings do not significantly affect performance, BWP’s designers must use full 3D simulation at every stage, in order to model the generator’s novel architecture as accurately as possible.


In control Having begun in virtual instrumentation, National Instruments is another company that


www.scientific-computing.com


have a computer-based way of doing it. I do find it telling that large organisations with extensive budgets, such as Formula One, still use physical prototypes. Computing is taking over more and more of what used to be done physically, but I do struggle to see how it can remove the need for physical models as those are what validate all the computational models. These computational models will only ever be as good as the inputs you give them, and those inputs will always be derived from physical models. But more than that, I really enjoy the physical modelling because it means I can get very detailed picture of the flow behind the back of a single support structure. This is quite well understood in broad terms, but all the turbulent flows aren’t understood at all. Once I know that, it can become an input into further computational models which I will be using later in my project.


The method I will be using is particle imaging velocimetry (PIV), which is a visualisation technique that uses cameras and lasers. The water within the tank is seeded with particles that reflect the laser light at certain wavelengths and the cameras take very rapid images of the flow. Hundreds of images are taken in a short amount of time and that huge volume of data looks at how each individual particle has moved. That’s when the software really comes into play; it enables us to correlate and make sense of all that data. The resulting images look quite similar to CFD visualisations.


now offers soſtware for modelling, simulation and control. Its Labview and Labview Control and Simulation Module can simulate a full wind turbine system, including the wind turbine, mechanical drive train, generator, power grid and controller. Te Control Design and Simulation Module provides a numerical simulation environment that enables design engineers to analyse the interactions between hybrid mechanical-electrical systems. Users can also can improve the quality of existing models and explore other control strategies by simulating deep-bar induction generators and more complex drive-train models. With a variety of vendors


offering soſtware solutions in this market, one final trend coming to the fore is co-simulation. ‘Numerous tools of varying detail, from


The downside is that we have recently been having issues with processing that volume of data as the software, and hardware, is having trouble keeping up. Beyond that, the software has been designed for general use, rather than for our specific application, which means that there will always be some things that either aren’t relevant to my research or are incredibly relevant, but the software doesn’t allow for enough adjustment of those features. Another issue is that with so many options, we could change values and make adjustments forever. On the one hand this is great for research as we don’t want rigid software; we want it to be as open source as possible so that it can be modified as needed. But, there are times when I wish there could be more of an explanation or description of what these options actually are, rather than have to learn the software. Research can’t be fully effective if you don’t fully understand the software, so it would always be nice to have the person who wrote the software sitting right next to me. There really is a temptation to look at the computer as if it’s a black box and assume that the person who wrote the software knew the fields it would be applied to and understood what specific researchers would need it to do. Of course, that isn’t the reality and, speaking on a personal level, if I didn’t learn the software to ensure I fully understand each input, I would always worry that I couldn’t have full confidence in my results.


Further information


Cambridge Econometrics www.camecon.com


Cobham Technical Services


www.cobham.com


Dassault Systèmes www.3ds.com


Maplesoft www.maplesoſt.com


Modelica Association www.modelica.org


National Instruments www.ni.com


a range of vendors, are now striving to communicate with each other and figure out how to exchange information between one tool and another. As a result, co-simulation technologies are beginning to emerge and while nothing is coming out as a particular standard, one project we’re looking at very closely is FMI (functional mockup interface),’ comments Maplesoſt’s Paul Goossens. ‘It’s being driven by the Modelica Association and the idea is that as long as each of the tools comply with that standard in terms of data exchange, we will start to see a lot more stand-alone products coming together through that platform.’ Tis, he says, will enhance the role of modelling and simulation in the development of alternative energy technologies.


DECEMBER 2012/JANUARY 2013 27


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32