Wind blade chord and twist angle optimization

wumingsheng

This paper shows a method to obtain optimal chord and twist distributions in wind
turbine blades by using genetic algorithms. The distributions are computed to maximize
the mean expected power depending on theWeibull wind distribution at a specific
site because in wind power systems optimization is highly site dependent [1]. This approach
avoids assumptions about optimal attack angle related to the ratio between the
lift to drag coefficients.
Genetic algorithms are global optimizers that have a wide trade-off between exploration
and explotation on the space problem. The geometry definition of a wind
blade is a problem with many degrees of freedom being suitable to fall in local optima,
which can be surpassed using evolutionary methods. Evolutionary Algorithms
are frequently used as powerful optimization methods. They are stochastic methods
inspired in the natural process of evolution[2, 3], and among their advantages are their
global search due to the management of a population of candidate solutions instead
only one, and also the only requirement of the knowledge of the fitness function value
to perform a evolutionary optimization, without any other consideration such as derivability
or continuity of the function. Many different optimum design problems in
multiple fields of sciences and engineering have been solved outperforming any other
previous results with evolutionary algorithms [4].
To optimize chord and twist distributions, an efficient implementation of the Blade-
Element and Momentum(BEM) theory [1, 5, 6] is used. It is basically a simplified
theory that is used routinely by wind power industry because it provides reasonably
accurate prediction of performance. The BEM theory has shown to give good accuracy
with respect to time cost, and at moderate wind speeds, it has sufficed for blade
geometry optimization.
In the implementation of BEM, the sophistication is dismiss to reduce computational
cost. The time required to evaluate the forces in a typical turbine is in the order
of milliseconds, which allows massive evaluation of trial turbines. The implementation
is validated by comparing power prediction with the experimental data of the

Risø test turbine that is one of six experimental turbines widely tested by the IEA. The
data are contained in the Annex XVIII report [7] and in the public database of rotor
performances at the ECN.
High quality in results is obtained until the stall zone, about wind speed of 13m/s
proximately. Predictions are used to compute the mean power that is the fitness function
in the genetic algorithm. The mean power, which is proportional to the annual
generated energy, is obtained by averaging power predictions with the probability obtained
from the Weibull distribution of the specific site. To obtain the optimal blade,
the upper and lower limits of chord and twist are needed as well as an optional upper
limit of the blade area.

samwu001

twist angle 我一直搞不懂

wumingsheng

最直觀的就是回去打開葉片切割打孔的那張圖紙，以根部界面和葉尖為參照，看葉型的偏離中軸線的角度，

然后即可
（不是距離）

wumingsheng

或者是葉型截面圖的那張，里面應(yīng)該有ｔｗｉｓｔ哪一項(xiàng)的。

chnkn

對于葉片的弦長、扭角和相對厚度分布的優(yōu)化，通常就是葉片的氣動外形優(yōu)化設(shè)計(jì)，我正好是做這個的。一般與葉片選擇的翼型族、葉片運(yùn)行最優(yōu)葉尖速比有關(guān)。

wumingsheng

陳兄，來說說。你是局內(nèi)人。

啥時(shí)候，咱們在搞漢翔這些東西的時(shí)候不用去烏克蘭求人家搞飛機(jī)翼型呢？

你認(rèn)為俺們在大飛機(jī)上面翼型會是真正的自主研發(fā)還是“借鑒”他人的研究（比如暴力美學(xué)締造者--老毛子，據(jù)說波音，空客就經(jīng)常就復(fù)雜的空氣動力學(xué)問題拋給老毛子，你的觀點(diǎn)呢？）。

chnkn

怎么不能回復(fù)帖子了？難道有敏感詞？？

chnkn

吳兄對暴力美學(xué)研究比較透徹，呵呵。

chnkn

目前，目前山寨文化深入人心，不過對于大飛機(jī)這么敏感的話題，則不敢妄言。實(shí)際上，對于空氣動力學(xué)方面研究，飛機(jī)上應(yīng)用的翼型研究應(yīng)該不是什么難點(diǎn)，難點(diǎn)在于整機(jī)空氣動力學(xué)的研究？我本人一直從事風(fēng)電機(jī)組空氣動力學(xué)研究，對于飛機(jī)，好像變得一知半解了，不好意思。

chnkn

回到風(fēng)能領(lǐng)域，有個8 6 3計(jì)劃課題，說是要研究我國自主知識產(chǎn)權(quán)的風(fēng)電機(jī)組專用翼型族，最后恐怕也是把DU？NREL S或者某個翼型族拿來作作風(fēng) 洞試 驗(yàn)了事？等著瞧吧。