Wind Farm Efficiency to be Improved Using “Evolutionary Algorithms”
Evolution inspires. And it has inspired some computer science researchers from the University of Adelaide and MIT to find out how to better place wind turbines in order to maximize their productivity.
“Senior Lecturer Dr Frank Neumann, from the School of Computer Science, is using a ‘selection of the fittest’ step-by-step approach called ‘evolutionary algorithms’ to optimise wind turbine placement,” the University of Adelaide reports. “This takes into account wake effects, the minimum amount of land needed, wind factors and the complex aerodynamics of wind turbines.”
While larger and larger turbines are being built to maximize efficiency and production, and thus lower costs, the placement of wind turbines apparently hasn’t been perfected yet and offers another way to increase productivity/efficiency and reduce costs. Hopefully, this work from Neumann and his colleagues will bring us forward a stride or two.
The placement of wind turbines to achieve maximum efficiency is a highly complex matter, though, Neumann notes. And some patience is in order (sorry). “An evolutionary algorithm is a mathematical process where potential solutions keep being improved a step at a time until the optimum is reached,” he says.
“You can think of it like parents producing a number of offspring, each with differing characteristics…. As with evolution, each population or ‘set of solutions’ from a new generation should get better. These solutions can be evaluated in parallel to speed up the computation.” Interesting way to look at it.
Neumann went to the University of Adelaide after working in Germany at the Max Planck Institute. He is working on this wind turbine placement project in coordination with researchers from the Massachusetts Institute of Technology.
h/t TreeHugger
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Photo via McBeth
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