【摘要】：針對基于概率密度峰值法的混合半云模型存在的模型精度易受擾動風(fēng)速影響的問題,提出了一種基于范數(shù)理論的混合半云模型峰值求解方法。首先,由風(fēng)速歷史數(shù)據(jù)獲得風(fēng)速概率密度統(tǒng)計離散點(diǎn);然后,采用范數(shù)理論選取風(fēng)速概率密度離散點(diǎn)的擬合多項(xiàng)式;最后,求取多項(xiàng)式的峰值點(diǎn),并將其對應(yīng)的風(fēng)速值作為風(fēng)速概率密度區(qū)域劃分的邊界,從而建立混合半云模型。結(jié)果表明:與基于概率密度峰值法的混合半云模型相比,所提方法可以有效地避免擾動風(fēng)速對模型概率峰值選取的影響,模型擬合度保持在99%以上。所提方法提高了混合半云模型的魯棒性和擬合精度,有效降低了"峰值偏離"對半云模型區(qū)域劃分的影響。
[Abstract]:In order to solve the problem that the model precision of mixed semi-cloud model based on probability density peak value method is easily affected by disturbed wind speed, a new method for peak value solution of mixed semi-cloud model based on norm theory is proposed. Firstly, the statistical discrete points of wind speed probability density are obtained from the historical wind speed data; then, the fitting polynomial of the wind speed probability density discrete point is selected by norm theory; finally, the peak point of the polynomial is obtained. The corresponding wind speed is taken as the boundary of the wind speed probability density region, and the mixed semi-cloud model is established. The results show that compared with the mixed semi-cloud model based on the peak probability density method, the proposed method can effectively avoid the influence of the disturbance wind speed on the selection of the probability peak value of the model, and the fitting degree of the model remains above 99%. The proposed method improves the robustness and fitting accuracy of the mixed semi-cloud model and effectively reduces the effect of "peak deviation" on the regional division of the semi-cloud model.
【作者單位】： 廣西大學(xué)廣西電力系統(tǒng)最優(yōu)化與節(jié)能技術(shù)重點(diǎn)實(shí)驗(yàn)室;
【分類號】：TK81;TM614
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本文編號：2127802