The mean wake model and its novel characteristic parameter of H-rotor VAWTs based on random forest method

被引：12

作者：

Dong, Zhikun ^{[1
]}

Chen, Yaoran ^{[1
]}

Zhou, Dai ^{[1
,2
,3
]}

Su, Jie ^{[1
]}

Han, Zhaolong ^{[1
,2
,3
,4
]}

Cao, Yong ^{[1
]}

Bao, Yan ^{[1
,3
]}

Zhao, Feng ^{[1
]}

Wang, Rui ^{[1
]}

Zhao, Yongsheng ^{[1
,2
]}

Xu, Yuwang ^{[1
,2
]}

机构：

[1] Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, Shanghai 200240, Peoples R China

[2] Shanghai Jiao Tong Univ, State Key Lab Ocean Engn, Shanghai 200240, Peoples R China

[3] Shanghai Jiao Tong Univ, Key Lab Hydrodynam, Minist Educ, Shanghai 200240, Peoples R China

[4] Shanghai Jiao Tong Univ, Inst Polar & Ocean Technol, Inst Marine Equipment, Shanghai 200240, Peoples R China

来源：

ENERGY | 2022年 / 239卷

基金：

中国国家自然科学基金;

关键词：

Vertical axis wind turbine; Wake model; Wake analysis; Random forest; Feature importance; AXIS WIND TURBINES; COMPUTATIONAL FLUID-DYNAMICS; PERFORMANCE; SIMULATION; FLOW; DESIGN;

D O I：

10.1016/j.energy.2021.122456

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

Using the random forest (RF) algorithm, this study presented a key parameter to characterize the mean wake of H-rotor VAWTs while modelling the wake. First, the RF algorithm was used to establish the regression relationship between the average wake velocity distribution and the rotor features. Next, the feature crosses method was combined with the RF algorithm to analyze the interaction and importance of the inputs. It was found that the normalized importance of a synthetic feature in wake modelling occupied a considerable significance, reaching 0.884 out of 1. The RF wake model with this parameter as the only input feature could successfully reconstruct the wake. It was found that this feature may reflect the ability of incident wind passing through the operating rotor and played a decisive role in the wake velocity distribution, including initial velocity deficit and wake recovery rate. The universality of this parameter was proved through cases analysis of wind turbines under different sizes and operating conditions. The study of the wake field is important for the modelling of the H-rotor VAWT wake field, and hence affects the optimal configuration of the wind farm. (C) 2021 Elsevier Ltd. All rights reserved.

引用

页数：14

共 56 条

[1] Data-driven modeling of the wake behind a wind turbine array [J].