Wind Farm Productivity Via Evolution

Wednesday, May 11, 2011 @ 04:05 PM gHale

Productivity is a huge factor in manufacturing and it is becoming a big factor in wind farms.

To increase wind farm productivity, taking a look at evolution is helping place wind turbines in the proper position.

A “selection of the fittest” step-by-step approach called “evolutionary algorithms” can optimize wind turbine placement, said University of Adelaide Senior Lecturer Dr. Frank Neumann, who works in the School of Computer Science. This takes into account wake effects, the minimum amount of land needed, wind factors and the complex aerodynamics of wind turbines.

“Renewable energy is playing an increasing role in the supply of energy worldwide and will help mitigate climate change,” Neumann said. “To further increase the productivity of wind farms, we need to exploit methods that help to optimize their performance.”

Neumann said the question of exactly where wind turbines should go to gain maximum efficiency is highly complex. “An evolutionary algorithm is a mathematical process where potential solutions keep being improved a step at a time until the optimum is reached.”

“You can think of it like parents producing a number of offspring, each with differing characteristics,” he said. “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.”

Neumann came to the University of Adelaide from the Max Planck Institute in Germany. He is working on wind turbine placement optimization in collaboration with researchers at Massachusetts Institute of Technology.

“Current approaches to solving this placement optimization can only deal with a small number of turbines,” Neumann said. “We have demonstrated an accurate and efficient algorithm for as many as 1000 turbines.”

Researchers are now looking to fine-tune the algorithms even further using different models of wake effect and complex aerodynamic factors.

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