Software helps save solar energy costs
June 19th 2008 11:24 pm By Web Development in India
Engineers at Solar Power Industries have used Algor FEA software to analyse the process of casting silicon ingots inside a directional solidification furnace.
According to the US Department of Energy, photovoltaic power will be competitive in price with traditional sources of electricity within 10 years Contributing to this trend, Solar Power Industries uses Algor finite element analysis (FEA) software as a tool for developing faster, more efficient and less expensive ways to manufacture solar cells
For example, SPI used Algor FEA to analyse the process of casting silicon ingots inside a directional solidification furnace.
“These ingots are used to manufacture photovoltaic solar cells”, says Chenlei Wang, PhD, Senior Engineer with SPI.
“Algor multiphysics software helped us in optimising the furnace’s hot-zone design, which was the key factor for the project”.
Solar Power Industries manufactures solar cells at state-of-the-art automated facilities in Belle Vernon, Pennsylvania.
A rooftop solar array, which converts sunlight into electricity and feeds directly into the building’s main power supply, was installed by SPI at Carnegie Mellon University.
Further reading
FEA used to optimize wheel design on solar car
The American Solar Car Challenge was the first race for the eighth solar car designed and built by the Canadian Queen’s University Solar Vehicle Team and the first to use Algor FEA software
Formula SAE team uses Algor FEA software
FEA software from Algor is helping in the design of a new racing car for Vanderbilt University’s 16-member Formula SAE team.
FEA software optimises avalanche shovel design
When G3 Genuine Guide Gear saw the need for a strong, lightweight avalanche shovel the company optimised the design using Algor FEA with Solidworks CAD software.
Incorporated in 2003, SPI has continually improved its solar cell production operations to better serve the solar energy industry’s rapidly growing markets, particularly in Europe and Asia.
“Our current annual production capacity for processing polycrystalline silicon feedstock into completed solar cells has grown to 40MW”, says Wang.
“We are focused on becoming a leader in the production of solar cells and we plan on significantly increasing capacity to reach 250MW over the next several years”.
Latest job opportunities
Multi skilled Maintenance Engineer, Maintenance Engineer, Engineer
Maintenance Engineer (FOOD/FMCG)
Job Title: Multi skilled Maintenance Engineer, Maintenance Engineer, Engineer
Area: Middlesex, London, Hertfordshire, Berkshire, Buckinghamshire, Bedfordshire, Surrey, Kent, Home Counties, South…
Electrical, Multi-skilled, Mechanical, Maintenance Engineer
Maintenance Engineer x 2, Multi-skilled Maintenance Engineer, Electrical Maintenance
Job Title: Electrical, Multi-skilled, Mechanical, Maintenance Engineer
Area: London, Hertfordshire, Middlesex, Bedfordshire, Essex, Buckinghamshire, South…
(Embedded) Electronics Design Engineers - Graduates to Senior
(Embedded) Electronics Design Engineers - Avon Ongoing business growth at this worl leading company has created a number of challenging and rewarding career opportunities to appeal to exceptional Electronics Design Engineers with varying levels of…
SPI’s solar cell manufacturing process consists of three main steps.
First, during ingot and wafer production, high-quality silicon feedstock (containing specific quantities of dopants such as boron in order to alter electrical properties) is melted and solidified inside a directional solidification furnace to cast polycrystalline silicon ingots.
The ingots are cut into rectangular blocks with a square cross-section and then the blocks are sawed into thin multicrystalline wafers.
Secondly, in cell production the wafers are etched to remove surface damage caused by sawing.
The wafers are then processed in a series of steps to produce photovoltaic cells.
Thirdly, in module assembly individual cells are connected by soldering to flat wires.
Strings of cells are then joined to parallel connector wires and laminated to produce a solar module.
Modules can be installed in a solar energy system to convert captured sunlight into usable electricity.
For example, SPI installed a rooftop array of 120 solar panels at a building on the Carnegie Mellon University campus, which feeds directly into the main power supply, providing approximately 10% of the building’s electricity needs.
That’s enough energy to support more than 80 computers while reducing the need for fossil fuel-based electricity.
The system also reduces the output of greenhouse gases by more than 14.3 tonnes per year.
SPI received funding from the Pennsylvania Energy Development Authority (PEDA) for a research programme aimed at expanding the supply of silicon feedstock for producing ingots by the directional solidification technique.
Because casting of commercial-size ingots is expensive and time-consuming, there was a need to develop a miniature version of a directional solidification furnace (called a “minicaster”) to efficiently cast small ingots for research.
“The smaller size of the minicaster would allow for the evaluation of candidate feedstock sources and growth techniques on less material and with faster turnaround times”, says Wang.
“Thus, the minicaster would allow us to conduct research on variables such as silicon feedstock, doping and solidification cycles”.
According to Greg Hildeman, ScD, SPI’s Vice President of Engineering: “To design, fabricate and test the minicaster, Dr Wang worked as a member of an SPI project team that included Dr Daniel Meier and Vinodh Chandrasekaran”.
Part of the PEDA funding was used by SPI to purchase Algor multiphysics software for analysis of the minicaster design.
Wang explained: “The reason we chose Algor was due to its cost-effective performance and local service and training programme”.
Wang attended a one-day training course at Algor’s headquarters in Pittsburgh, Pennsylvania.
“The training was very helpful”, he says.
“While modelling the minicaster, I used Algor’s technical support service to discuss particular issues such as mesh generation and transient phase modelling”.
Inside the minicaster, silicon feedstock is loaded in a vitreous quartz crucible.
Graphite plates surround the crucible - providing mechanical support.
Surrounding the crucible is a bank of resistive heaters that uniformly heats the charge.
A movable insulation cage serves as the primary means by which the desired cooling rate and directional solidification growth is achieved.
Wang explains: “In order to assess the design of the minicaster ‘hot zone’ prior to fabricating the components, finite element modelling and analysis was first carried out for the melting phase and then the solidification phase”.
“We created a 3D model of the minicaster in Autodesk Inventor”, says Wang.
“Then, we modelled the cross-sectional geometry in Algor”.
Custom-defined, temperature-dependent orthotropic material properties were specified for the silicon feedstock, quartz crucible, graphite heaters and insulation.
Thermal loads were defined for internal heat generation, surface radiation at the outside surfaces and body-to-body radiation between exposed internal surfaces.
Fluid velocities were specified for surfaces that surrounded the silicon.
“Natural convection due to buoyancy plays an important role for transport phenomena inside the silicon melt”, says Wang.
“The strong velocity field inside the silicon melt cannot be neglected”.
“Therefore, we used Algor multiphysics analysis to couple the calculation of the silicon melt flow field and temperature field, which accounted for the effect of natural convection”.
Wang performed a steady coupled fluid flow and thermal analysis to obtain the convective fluid flow and temperature results for the melting phase.
For the solidification phase, a lower internal heat generation value was used to simulate lower temperatures while cooling.
Algor transient heat transfer analysis results allowed SPI to better understand the minicaster’s solidification process.
On examining the first silicon ingot produced by the minicaster, SPI noticed some concerns.
“Most of the ingot’s surface was flat and smooth, but there were some regions at the top of the ingot where the solidification proceeded erratically”, says Wang.
“This was thought to be associated with an undesired solidification at the top of the melt, which initiated while solidification was occurring from the bottom upward”.
“Such solidification was predicted by the thermal finite-element model of the growth”.
In order to maximise ingot quality, multiple transient heat transfer analyses of the solidification phase were conducted to determine the best placement and output power for the minicaster’s heaters.
“By adjusting the heater position and increasing the heater power level by 25%, surface solidification was prevented during the growth process”, says Wang.
“Another effective way to modify the thermal environment was by adjusting the insulation lift distance”.
“The resulting solidification interface was flat and slightly convex to the silicon melt, which is beneficial for high-quality silicon crystal growth”.
“The PEDA-funded research project was finished in 2006″, says Wang: “but research using the minicaster is still ongoing”.
“Additionally, I am using Algor to simulate other crystal growth furnaces”.
