Analytics Power Solar Energy Boost
Photovoltaic cells, the much-heralded hope for the future of solar energy, are still out of reach for mass consumption due in large part to overall cost. While solar energy pioneers are still seeking ways to tweak the price performance issue, others are focusing on less obvious potential solutions.
One such group of solar cell researchers at MIT is addressing the problem of current solar technology by examining the arrangement of the cells themselves. Their findings could provide power output that is anywhere from double to up to 20 times that of current solar cell configurations.
The key to the improvement is in the arrangement of the cells, and the fastest way to testing nearly limitless configurations is by using sophisticated analytics to arrive at conclusions.
The team behind the findings began with a sophisticated algorithm to explore, as MIT described, an “enormous variety of possible configurations and developed analytics software that can test any given configuration under a whole range of latitudes, seasons and weather.”
With the results of the analytical runs in hand, the team found that by building cubes or towers that extend the solar cells upward in three-dimensional configurations, the notable performance improvements could be gleaned. These results were magnified in situations when improvement was most critical—in locations far from the equator, during the winter, and on cloudy days.
As co-author Marco Bernardi, a graduate student in MIT’s Department of Materials Science and Engineering (DMSE) describes, “The basic physical reason for the improvement in power output — and for the more uniform output over time — is that the 3-D structures’ vertical surfaces can collect much more sunlight during mornings, evenings and winters, when the sun is closer to the horizon.”
Although the analytics segment revealed the highest advantage would come from complex shapes — such as a cube where each face is dimpled inward — these would be difficult to manufacture, says co-author Nicola Ferralis, a research scientist in DMSE.
The algorithms can also be used to optimize and simplify shapes with little loss of energy. It turns out the difference in power output between such optimized shapes and a simpler cube is only about 10 to 15 percent — a difference that is dwarfed by the greatly improved performance of 3-D shapes in general, he says. The team analyzed both simpler cubic and more complex accordion-like shapes in their rooftop experimental tests, which were carried out based on the assumptions made from the analytics exercise.