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基于模糊補(bǔ)償?shù)腗PC獨(dú)立變槳減載控制

來(lái)源：電工電氣發(fā)布時(shí)間：2025-07-24 15:24瀏覽次數(shù)：74

基于模糊補(bǔ)償?shù)腗PC獨(dú)立變槳減載控制

張浩，張宇琪

(湖南工業(yè)大學(xué) 交通與電氣工程學(xué)院，湖南株洲 412007)

摘要：為降低獨(dú)立變槳控制中的葉根載荷并保持輸出功率的穩(wěn)定性，對(duì)風(fēng)力機(jī)進(jìn)行線性化處理，建立狀態(tài)空間方程，并將其轉(zhuǎn)換至 dq 坐標(biāo)系。在此基礎(chǔ)上，構(gòu)建適用于獨(dú)立變槳模型預(yù)測(cè)控制(MPC)的預(yù)測(cè)方程，并根據(jù)控制目標(biāo)與約束條件對(duì)輸入輸出權(quán)重進(jìn)行調(diào)整。為進(jìn)一步降低 MPC 獨(dú)立變槳控制器的偏航彎矩和俯仰彎矩，設(shè)計(jì)了模糊補(bǔ)償減載控制器，對(duì)傳統(tǒng)模型預(yù)測(cè)控制算法中 dq 坐標(biāo)系下的槳距角信號(hào)進(jìn)行補(bǔ)償，從而進(jìn)一步降低葉根載荷并提高了輸出功率的穩(wěn)定性。通過(guò) OpenFAST 與 Simulink 軟件的聯(lián)合仿真，結(jié)果表明，基于模糊補(bǔ)償?shù)哪Ｐ皖A(yù)測(cè)獨(dú)立變槳控制在功率穩(wěn)定性和降載效果上優(yōu)于基于 PI 控制和傳統(tǒng)模型預(yù)測(cè)控制的方法。

關(guān)鍵詞： 模糊補(bǔ)償；模型預(yù)測(cè)控制；獨(dú)立變槳；減載控制

中圖分類號(hào)：TK83 ；TM571 文獻(xiàn)標(biāo)識(shí)碼：A 文章編號(hào)：1007-3175(2025)07-0029-08

MPC Independent Pitch and Load Reduction Control

Based on Fuzzy Compensation

ZHANG Hao, ZHANG Yu-qi

（School of Traffic and Electrical Engineering, Hunan University of Technology, Zhuzhou 412007, China）

Abstract: To reduce the blade root load in individual pitch control and maintain output power stability, this paper linearizes the wind turbine and establishes its state-space equations, which are then transformed into the dq coordinate system. On this basis, a prediction equation suitable for the model predictive control (MPC) of the independent pitch model is constructed, and the input and output weights are adjusted according to the control objective and constraint conditions. To further reduce the yaw bending moment and pitch bending moment of the MPC independent pitch controller, a fuzzy compensation load reduction controller was designed to compensate for the pitch angle signal in the dq coordinate system of the traditional MPC algorithm, thereby further reducing the blade root load and improves the stability of the output power. Through the joint simulation of OpenFAST and Simulink software, the results show that the model prediction independent pitch control based on fuzzy compensation is superior to the methods based on PI control and traditional model predictive control in terms of power stability and load reduction effect.

Key words: fuzzy compensation; model predictive control; independent pitch; load reduction control

參考文獻(xiàn)

[1] 李輝，楊超，胡姚剛，等. 抑制風(fēng)力機(jī)疲勞載荷的直接比例諧振獨(dú)立變槳控制策略[J] . 電力自動(dòng)化設(shè)備，2016，36(3) ：79-85.

[2] 郭百順，秦斌，邵軍，等. 風(fēng)電機(jī)組獨(dú)立變槳距控制策略研究[J]. 湖南工業(yè)大學(xué)學(xué)報(bào)， 2014，28(2) ：42-45.

[3] MULDERS S P, VAN WINGERDEN J W.On the importance of the azimuth offset in a combined 1P and 2P SISO IPC implementation for wind turbine fatigue load reductions[C]//2019 American Control Conference(ACC)，2019 ：3506-3511.

[4] LARA M, GARRIDO J, VAN WINGERDEN J W, et al.Optimization with genetic algorithms of individual pitch control design with and without azimuth offset for wind turbines in the full load region[J].IFAC-PapersOnLine，2023，56(2) ：342-347.

[5] MULDERS S P, PAMOSOSURYO A K, DISARIO G E, et al.Analysis and optimal individual pitch control decoupling by inclusion of an azimuth offset in the multiblade coordinate transformation[J].Wind Energy，2019，22(3) ：341-359.

[6] LI Jianshen, WANG Shuangxin.Dual multivariable model-free adaptive individual pitch control for load reduction in wind turbines with actuator faults[J].Renewable Energy，2021，174 ：293-304.

[7] WANG Xin , ZHOU Jianshu , QIN Bin , et al .Individual pitch control of wind turbines based on SVM load estimation and LIDAR measurement[J].IEEE Access，2021，9 ：143913-143921.

[8] 孔維杰，秦斌，王欣. 風(fēng)機(jī)獨(dú)立變槳減載模型預(yù)測(cè)控制研究[J]. 電工技術(shù)，2024(4) ：17-21.

[9] 曹松青，郝萬(wàn)君，陳歆婧，等. 基于模型預(yù)測(cè)控制的風(fēng)電機(jī)組載荷控制[J]. 蘇州科技大學(xué)學(xué)報(bào)(自然科學(xué)版)，2019，36(3) ：79-84.

[10] 田德，方建駒，劉楓，等. 大型風(fēng)電機(jī)組模型預(yù)測(cè)獨(dú)立變槳控制器設(shè)計(jì)[J] . 太陽(yáng)能學(xué)報(bào)，2022，43(4) ：461-467.

[11] 梁棟煬，宋子秋，劉亞娟. 基于 LPV-MPC 的風(fēng)電機(jī)組功率-載荷協(xié)調(diào)控制策略[J] . 可再生能源，2024，42(1) ：38-44.

[12] 王多睿，王維慶，蔡鑫. 基于 NMPC-PID 的風(fēng)力機(jī)獨(dú)立變槳距控制策略研究[J] . 太陽(yáng)能學(xué)報(bào)，2017，38(9) ：2520-2526.

[13] KAYEDPOUR N, SAMANI A E, DE KOONING J D M, et al.Model predictive control with a cascaded Hammerstein neural network of a wind turbine providing frequency containment reserve[J].IEEE Transactions on Energy Conversion，2021，37(1) ：198-209.

[14] PETROVIC V, JELAVIC M, BAOTIC M.MPC framework for constrained wind turbine individual pitch control[J].Wind Energy，2021，24(1) ：54-68.

[15] COLLET D, ALAMIR M, DI DOMENICO D, et al.Datadriven fatigue-oriented MPC applied to wind turbines individual pitch control[J].Renewable Energy，2021，170 ：1008-1019.

[16] EL-BAKLISH S K, EL-BADAWY A A, FRISON G, et al.Nonlinear model predictive pitch control of aero-elastic wind turbine blades[J].Renewable Energy，2020，161 ：777-791.

[17] RAACH S, SCHLIPF D, SANDNER F, et al.Nonlinear model predictive control of floating wind turbines with individual pitch control[C]//2014 American Control Conference，2014 ：4434-4439.

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基于模糊補(bǔ)償?shù)腗PC獨(dú)立變槳減載控制