This page contains a Flash digital edition of a book.
solar energy


the chemical reactor in which the silicon is processed to make PV cells, modelling such factors as species transfer and, at a later stage in the process, surface deposition of the silicon onto the substrate of the cells. Such simulations may involve multiphase calculations – which are very compute-intensive, he warned. Te aim is to change manufacturing


processes so that less material is used. Independently, research is going on to improve the composition of the cells so that they convert more of the sun’s radiation to electricity and waste less as heat. Alternative ways of making PV cells to increase conversion efficiencies to 30 per cent are at the heart of the US Department of Energy’s ‘SunShot’ programme, launched in February 2011, which aims to reduce the total costs of PV systems by three quarters to roughly $1 a watt (corresponding to about six cents per kilowatt-hour) which would make them cost competitive at large scale with other forms of energy.


Optimising structures Te second area is more conventional structural engineering. Ansys has a suite of programs that can be used to calculate stresses and loads in mechanical engineering but, in addition, he pointed out, solar loading – shade calculations and the best location with respect to the sun – and, especially for commercial structures, wind-loading and mobility of the mirrors need to be factored in. ‘On the mechanical side of things, reliability is important – structural integrity and reliability. What happens to that system on the rooſtop over 25 years? It’s not a simple linear structure,’ he asked. As with Ron Behee and MSC Soſtware, the issue for Haidari is the weather and fluctuating conditions. Tough some of this can be tested empirically, he said: ‘Engineering simulation tests the real-life reliability of a panel across various operating events. More goes into the design of these panels to make sure they’re there for 25 years. Tat’s where computational technology comes into play – to really test the real life variability of a panel across many applications.’ Concentrated power plant installations


present further challenges for simulation and optimisation. Te mirrors tend to be flat and smooth, and their supports have to be relatively stiff so they do not flex when the wind blows or other loads are placed on them. Te mirrors have to track the sun as it moves overhead, and this presents issues of simulating the control circuitry that keeps them pointing in the right direction. Some of these calculations can be


very compute-intensive. Ansys has been concentrating on parallelising all its code, across all applications and sectors ‘to create


46 SCIENTIFIC COMPUTING WORLD Sunlight I I Temperature


Temperature Sunlight P P Temperature


V


V


The influence of sunshine and heat on the electrical and power output of solar cells. The maximum power point is just before the ‘knee’ at the right hand side of the curve


an environment for our customers that offers realistic system design’. He sees high- performance computing (HPC) as ‘one of the enabling tools to create an environment where people can do real-life simulations.’ Te company was also looking at the programming challenges and opportunities presented by GPUs to make simulations faster. For Luxon Engineering, a mechanical


engineering consulting firm located in San Diego, California, however, Altair’s HyperWorks was the package of choice when it came to optimising a large-scale industrial panel system where components also rotate to track the sun. Luxon’s brief was to lower the manufacturing costs, and also to model wind and snow loading, so the system could be deployed in a wider range of geographical locations. Te system consisted of lenses


POWER PLANT


INSTALLATIONS PRESENT FURTHER CHALLENGES FOR SIMULATION AND OPTIMISATION


focused on photovoltaic cells separated over a large distance; if the focal distance between cell and lens shiſted, the panel lost efficiency. Luxon, therefore, worked to increase the stiffness of the plates that hold the cells in place. By optimising the topology of the drive mechanism, Luxon improved its structural performance at the same time as cutting its cost by eight per cent. Luxon also replaced the steel crank arm with cast-iron, reducing cost by 38 per cent and mass by 52 per cent. According to Billy Wight, president of


Luxon: ‘In general, we wanted to reduce mass


as much as possible, subject to constraints on stress and stiffness. Te customer wanted a “one size fits all” solution. Tere are areas of the world where the product would not be subject to very intense loads, which opens up the opportunity to further reduce cost. However, the extra work and complexity involved in managing multiple product configurations would likely offset any cost advantage.’ He said: ‘We use HyperWorks for 95 per


cent of our analysis work. For CAD we use SolidWorks, which includes a basic, linear, static finite-element solver – SolidWorks Simulation. It is, he said, easy to set up a basic analysis in SolidWorks, but harder to control mesh quality. So Luxon tries to interest its customers in applying HyperWorks. Tey mainly use the structural finite-element solutions – from simple, linear, static, implicit solutions to highly complicated, non-linear explicit solutions, the CFD capabilities, and the optimisation capabilities. ‘Most parts of the suite talk well with one another,’ he continued and ‘Te optimisation capabilities were another huge selling point for us. No other package offers this diversity of solution types under one licence scheme.’ Trying to reduce the heating effect of the sun


was an issue in this project too, and Luxon had to optimise the heatsinks (size, shape, number of fins, and so on) mounted on each solar cell: ‘We used both an assumed convection coefficient model to iterate quickly through a few designs, then moved to a CFD model to refine the promising designs.’ Ultimately, as in most engineering projects, the optimisation is not just about the physical, thermal and electrical but also about the financial constraints. According to Wight: ‘Te goal was to maximise energy production per cost (kW/$). We knew the relationships between


@scwmagazine l www.scientific-computing.com


Simulation Research


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  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52