RESEARCH ON VARIABLE WEIGHT MULTI-MODEL PREDICTIVE CONTROL FOR FLOATING WIND TURBINE BASED ON GAP METRIC AND FUZZY CONTROL

Liu Yingming; Ma Zhenhong; Wang Xiaodong; Jiao Yifei; Li Changchuan

doi:10.19912/j.0254-0096.tynxb.2024-0901

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (9) : 189-197. DOI: 10.19912/j.0254-0096.tynxb.2024-0901

RESEARCH ON VARIABLE WEIGHT MULTI-MODEL PREDICTIVE CONTROL FOR FLOATING WIND TURBINE BASED ON GAP METRIC AND FUZZY CONTROL

Liu Yingming¹, Ma Zhenhong¹, Wang Xiaodong¹, Jiao Yifei¹, Li Changchuan²

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Abstract

This paper takes the NREL 5MW semi-submersible floating wind turbine as the research object. The nonlinear model was built through mechanisms analysiss and dynamic analysis. The linear parameter-varying （LPV） model under different working conditions was established by the online parameter identification method. The gap metric theory was used to simplify the number of linear models, and the LPV model was compared with the FAST model to verify its accuracy. A multi-model predictive control pitch controller based on fuzzy variable weighting （Fuzzy-MPC） was proposed. The Kalman filter state observer was introduced for state estimation, with to reducing power fluctuations and tower displacement as the objective function. To enhance the controller's tracking ability under different working conditions, the fuzzy control was employed to optimize the weight coefficients of the MPC objective function online, achieving adaptive control. The effectiveness of the designed controller in smoothing power, reducing tower displacement and stabilizing unit attitude is verified by comparison with FAST and fixed weight MPC controllers.

Key words

offshore wind turbines / model predictive control / fuzzy control / gap metric / linear variable parameter model

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Liu Yingming, Ma Zhenhong, Wang Xiaodong, Jiao Yifei, Li Changchuan. RESEARCH ON VARIABLE WEIGHT MULTI-MODEL PREDICTIVE CONTROL FOR FLOATING WIND TURBINE BASED ON GAP METRIC AND FUZZY CONTROL[J]. Acta Energiae Solaris Sinica. 2025, 46(9): 189-197 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0901

References

[1] 宋子秋, 冯翰宇, 余照国, 等. 基于模型预测控制的半潜漂浮式风机协调控制方法研究[J]. 中国电机工程学报, 2022, 42(12): 4330-4339.
SONG Z Q, FENG H Y, YU Z G, et al.Coordinated control of semi-submersible floating turbine with model predictive control strategy[J]. Proceedings of the CSEE, 2022, 42(12): 4330-4339.
[2] 李欣, 张明明, 杨洪磊. 张力腿漂浮式风电机组疲劳载荷智能控制研究[J]. 太阳能学报, 2020, 41(9): 278-286.
LI X, ZHANG M M, YANG H L.Numerical investigation of smart fatigue load control on tension leg platform floating wind turbine[J]. Acta energiae solaris sinica, 2020, 41(9): 278-286.
[3] 许移庆, 张友林. 漂浮式海上风电发展概述[J]. 风能, 2020(5): 56-61.
XU Y Q, ZHANG Y L.Overview of the development of floating offshore wind power[J]. Wind energy, 2020(5): 56-61.
[4] BETTI G, FARINA M, GUAGLIARDI G A, et al.Development of a control-oriented model of floating wind turbines[J]. IEEE transactions on control systems technology, 2014, 22(1): 69-82.
[5] HOMER J R, NAGAMUNE R.Physics-based 3-D control-oriented modeling of floating wind turbines[J]. IEEE transactions on control systems technology, 2018, 26(1): 14-26.
[6] SONG Z Q, LIU J Z, LIU Y J, et al.Fault-tolerant control of floating wind turbine with switched adaptive sliding mode controller[J]. IEEE transactions on automation science and engineering, 2024, 21(3): 3705-3718.
[7] SOLIMAN M, MALIK O P, WESTWICK D T.Multiple model predictive control for wind turbines with doubly fed induction generators[J]. IEEE transactions on sustainable energy, 2011, 2(3): 215-225.
[8] 徐樾, 贾立, 付轩熠. 基于Wiener模型的风力发电系统变桨距控制[J]. 系统仿真学报, 2022, 34(8): 1741-1749.
XU Y, JIA L, FU X Y.Variable pitch control of wind power generation system based on Wiener model[J]. Journal of system simulation, 2022, 34(8): 1741-1749.
[9] 黄国燕, 朱敏. 基于状态空间的漂浮式风电机组控制策略研究[J]. 太阳能学报, 2021, 42(6): 337-341.
HUANG G Y, ZHU M.Control stratege research of floating wind turbines based on state-space[J]. Acta energiae solaris sinica, 2021, 42(6): 337-341.
[10] 王会盼, 刘吉臻, 胡阳, 等. 基于预测控制的大惯量风机全工况功率调度跟踪[J]. 电网技术, 2020, 44(7): 2520-2528.
WANG H P, LIU J Z, HU Y, et al.Power dispatching tracking of large-inertia wind turbine under full operating conditions based on predictive control[J]. Power system technology, 2020, 44(7): 2520-2528.
[11] IBÁÑEZ B, INTHAMOUSSOU F A, DE BATTISTA H. Wind turbine load analysis of a full range LPV controller[J]. Renewable energy, 2020, 145: 2741-2753.
[12] 方建驹. 基于模型预测控制的大型海上风电机组降载控制[D]. 北京: 华北电力大学, 2022.
FANG J J.Load reduction of large-scale offshore wind turbines based on model predictive control[D]. Beijing: North China Electric Power University, 2022.
[13] 梁媛, 王红庆. 基于NSGA权值修正的MPC方法及其在光氢系统应用[J]. 太阳能学报, 2024, 45(11): 131-140.
LIANG Y, WANG H Q.MPC method based on NSGA weight correction and its application in photohydrogen systems[J]. Acta energiae solaris sinica, 2024, 45(11): 131-140.
[14] 李家祥, 汪凤翔, 柯栋梁, 等. 基于粒子群算法的永磁同步电机模型预测控制权重系数设计[J]. 电工技术学报, 2021, 36(1): 50-59, 76.
LI J X, WANG F X, KE D L, et al.Weighting factors design of model predictive control for permanent magnet synchronous machine using particle swarm optimization[J]. Transactions of China Electrotechnical Society, 2021, 36(1): 50-59, 76.
[15] SONG Z Q, HU Y, CAI W, et al.Control-oriented modeling and characteristic analysis of offshore semisubmersible wind turbine under wind-wave joint loads[J]. IEEE transactions on control systems technology, 2023, 31(4): 1917-1925.
[16] LASHEEN A, ELSHAFEI A L.Wind-turbine collective-pitch control via a fuzzy predictive algorithm[J]. Renewable energy, 2016, 87: 298-306.
[17] 梁栋炀, 宋子秋, 刘亚娟. 基于LPV-MPC的风电机组功率-载荷协调控制策略[J]. 可再生能源, 2024, 42(1): 38-44.
LIANG D Y, SONG Z Q, LIU Y J.Coordinated power-load control strategy for wind turbine based on LPV-MPC[J]. Renewable energy resources, 2024, 42(1): 38-44.
[18] 王永智, 景云, 王丹. 基于在线参数辨识的PWM整流器功率预测控制[J]. 控制工程, 2022, 29(5): 796-803.
WANG Y Z, JING Y, WANG D.Power prediction control of PWM rectifiers with online parameter identification[J]. Control engineering of China, 2022, 29(5): 796-803.
[19] 郭海宇, 张英豪, 刘颖明, 等. 基于动力学模型和多种群遗传算法的漂浮式风电机组调谐质量阻尼器参数优化[J]. 太阳能学报, 2023, 44(11): 217-223.
GUO H Y, ZHANG Y H, LIU Y M, et al.Optimization design of tuned mass damper for floating wind turbines based on dynamic model and multiple population genetic algorithm[J]. Acta energiae solaris sinica, 2023, 44(11): 217-223.
[20] ABDELBAKY M A, LIU X J, JIANG D.Design and implementation of partial offline fuzzy model-predictive pitch controller for large-scale wind-turbines[J]. Renewable energy, 2020, 145: 981-996.
[21] 彭春江. 海上浮式风电机整机全耦合动力学建模及动态激励特性研究[D]. 长沙: 湖南大学, 2017.
PENG C J.Full couping dynamics modeling and dynamic excitation characteristics research for offshore floating wind turbine[D]. Changsha: Hunan University, 2017.
[22] 陶响元. 基于间隙度量的非线性系统多模型预测控制[D]. 上海: 上海交通大学, 2014.
TAO X Y.Gap metric based multiple model predictive control for non-linear systems[D]. Shanghai: Shanghai Jiao Tong University, 2014.
[23] 李韶华, 杨泽坤, 王雪玮. 基于T-S模糊变权重MPC的智能车轨迹跟踪控制[J]. 机械工程学报, 2023, 59(4): 199-212.
LI S H, YANG Z K, WANG X W.Trajectory tracking control of an intelligent vehicle based on T-S fuzzy variable weight MPC[J]. Journal of mechanical engineering, 2023, 59(4): 199-212.