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Towards the Evolution of Novel Vertical Axis Turbines. Richard Preen & Larry Bull UWE, Bristol. Introduction. Evolutionary computing has been applied widely. Over 70 examples of “human competitive” performance have been noted [ Koza , 2010]. - PowerPoint PPT Presentation
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Towards the Evolution of Novel Vertical Axis Turbines
Richard Preen & Larry BullUWE, Bristol
IntroductionEvolutionary computing has been applied widely.Over 70 examples of “human competitive”
performance have been noted [Koza, 2010].Most of this work has included simulation or
models.When simulations are costly, surrogate models
can be used.Data mining techniques are used to create
approximations of the function space from sample points gathered from the simulator/model.
Embodied Evolution 1Some hard problems are difficult to model or
simulate in a useful way.Small amount of work using simulated
evolutionary design directly on a task:Jet nozzle [Rechenberg, 1971]Mobile robotics [Nolfi, 1992]Electronic circuits [Thompson, 1998]Unconventional computing [Harding & Miller,
2004]Chemical systems [Theis et al., 2007]
Embodied Evolution 2Explore use of surrogate models in
conjunction with direct solution evaluation only for complex tasks.
No best-guess simulator or model used.Combine with emerging rapid-fabrication (3D
printing) technology.Potential for truly unexpected results in a
wide range of domains.Many issues, of course: time, noise in
evaluations, representations, kinds of surrogates, etc.
An Example: Wind Turbines
Wind Energy“In theory, small-scale wind energy has the potential to
generate 41.3 TWh of electricity and save 17.8 MtCO2 in the UK annually” [Carbon Trust, 2008].
Wind flow is rarely constant and consistent, rather it is usually veering and turbulent, and the influences of nearby obstacles can significantly alter wind flow patterns.
Vertical axis wind turbines (VAWT) represent a very effective approach to harnessing wind power in many situations – especially urban areas.
In comparison to the more common horizontal axis wind turbine (HAWT), VAWT can also be easier to manufacture, may scale more easily, and are typically inherently light-weight with little or no noise pollution.
A Simple RepresentationConfined design space to a four-blade Savonius
VAWT with alterations in blade shape (profile and twist) possible.
Genome [5,8,2,4] defines offsets from central spindle.
Embodied Evolution of VAWTTurbines of 30mm3 volumePopulation size 20Tournament selectionTip speed used as fitness measureDirect evaluations for first three generations
(60 fabs)MLP surrogate model of fitnessMLP trained for 1000 epochs per generationBest and random individual fabricated per
generation
Single VAWT
Single VAWT: Z-axis design
Beyond ModellingEvolutionary computing has previously been
used to design both HAWT and VAWT via CFD models.
Essentially impossible for turbine arrays where interactions are considered.
Dabiri et al. have recently highlighted how the spacing constraints of HAWT arrays often do not apply for VAWT, and even that performance can be increased by exploitation of inter-turbine flow effects.
View wind farm as an energy-capture ecosystem and coevolve heterogeneous, interacting VAWT.
Embodied CoevolutionTwo “species” of turbine.Two populations and surrogate models (L, R).Each evaluated with best individual from
other population.Evolve alternately.Seed with 10 best from single VAWT
experiments.Allow counter-rotation.All other features the same as before.
Paired VAWT
Example
ResultsSpeciation seen – L and R physically
different.Homogeneous pairing of either species not as
effective as the heterogeneous case.Counter-rotation not seen in fittest solutions
here.Approach potentially unaffected by array size
increase.CFD modelling impossible.