Computer scientist to optimise wind farm efficiency through rightly placed turbines
A wind farm is created when a group of wind turbines are erected in close distances to each other for the sole purpose of generating electricity. South Australia’s University of Adelaide computer science research has been inspired by evolution in order to understand where best these wind turbines may be placed in order to generate maximum electricity.
School of Computer Science senior lecturer Dr Frank Neumann has developed an approach, which he calls ‘evolutionary algorithms’ for augmenting the placement of wind turbines. He is working on wind turbine placement optimization in in collaboration with researchers from the Massachusetts Institute of Technology.
By this step by step procedure, he seeks the ‘fittest’ method that be adopted for the achieving the best possible results. Neumann efforts are inclusive of factors such as the size of land to be used in the project, wake effects, wind as a whole, wind turbines – their aerodynamics and the resulting complexities of the same.
Neumann explains the reason for his research is to help the wind farm perform better, as the world has finally woken up to the havoc it has created till date and is ready to take its charge in saving nature. This implies that more and more people soon begin to resort to renewable forms of energy and this says Neumann, is possible by leaving no stone unturned in deriving the best performance from the wind farms.
Researches in various parts of the world recently reveal that even though millions were being spent in constructing wind farms the resultants energy generated from them was nominal. In order to answer the much asked question of the placement of the turbines, the lecturer has developed the evolutionary algorithms – a math equation, a process that keeps evolving with time. Each time delivering a better result, until the best in achieved.
In order to explain his theory, Neumann compares it to human procreation – in which each offspring is born with a particular characteristic, which keeps getting better as time progress. He also compares it to the Ant Colony- in which as the ants keep accumulating food, a point comes where the ants find the shortest path to reach the food from their nests.
Neumann’s theory has proved successful in terms of fewer turbines. The efficient algorithm could be achieved up till 1000 wind turbines. Research continues as the scholars try to apply the same equation on other aspects of wind power generation such as the wake effect and complex aerodynamic factors.