A 2.5MW Wind Turbine TL-EMPC Yaw Strategy Based on Ideal Wind Measurement By LiDAR

This paper analyzes the yaw data of the 2.5MW wind turbine of XEMC Windpower Company, and the real wind information collected by the wind farm, and proposes a two-level economic model predictive control (TL-EMPC) yaw strategy based on ideal wind measurement by light detection and ranging (LiDAR). Th...

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Main Authors: Han Zhao, Lawu Zhou, Yu Liang, Shuowang Zhang, Mianzhuo Ma
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9456969/
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author Han Zhao
Lawu Zhou
Yu Liang
Shuowang Zhang
Mianzhuo Ma
author_facet Han Zhao
Lawu Zhou
Yu Liang
Shuowang Zhang
Mianzhuo Ma
author_sort Han Zhao
collection DOAJ
description This paper analyzes the yaw data of the 2.5MW wind turbine of XEMC Windpower Company, and the real wind information collected by the wind farm, and proposes a two-level economic model predictive control (TL-EMPC) yaw strategy based on ideal wind measurement by light detection and ranging (LiDAR). This strategy comprehensively considers the power loss caused by yaw misalignment and the structural loads of the yaw bearing during the yaw process, making the yaw system more efficient and economical: In the high wind speed range, the yaw system has a higher sensitivity by setting the threshold of the yaw error angle, so as to fully capture wind energy; in the low wind speed range, fully consider the fatigue load of the critical parts of the wind turbine during the yaw process, thus Improve the economy of the wind turbine yaw system. The fatigue load and limit load of the yaw actuator at different yaw speeds are analyzed, and the best yaw speed is obtained. The finite control set of the yaw speed is established, which is used as the constraint set of the second-level minimum objective function. Finally, an external controller was used to simulate the 2.5MW wind turbine model in Bladed, and the effectiveness of the control strategy was verified.
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spelling doaj.art-ee4ea1d17a614985a5d29caf4f3dfcd52022-12-21T21:24:25ZengIEEEIEEE Access2169-35362021-01-019898668987710.1109/ACCESS.2021.30895139456969A 2.5MW Wind Turbine TL-EMPC Yaw Strategy Based on Ideal Wind Measurement By LiDARHan Zhao0https://orcid.org/0000-0001-6678-0677Lawu Zhou1Yu Liang2https://orcid.org/0000-0001-8821-1416Shuowang Zhang3https://orcid.org/0000-0002-7227-8410Mianzhuo Ma4School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, ChinaSchool of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, ChinaLinyi Power Supply Company, State Grid Shandong Power Company Ltd., Linyi, ChinaXEMC Windpower Company Ltd., Xiangtan, ChinaSchool of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, ChinaThis paper analyzes the yaw data of the 2.5MW wind turbine of XEMC Windpower Company, and the real wind information collected by the wind farm, and proposes a two-level economic model predictive control (TL-EMPC) yaw strategy based on ideal wind measurement by light detection and ranging (LiDAR). This strategy comprehensively considers the power loss caused by yaw misalignment and the structural loads of the yaw bearing during the yaw process, making the yaw system more efficient and economical: In the high wind speed range, the yaw system has a higher sensitivity by setting the threshold of the yaw error angle, so as to fully capture wind energy; in the low wind speed range, fully consider the fatigue load of the critical parts of the wind turbine during the yaw process, thus Improve the economy of the wind turbine yaw system. The fatigue load and limit load of the yaw actuator at different yaw speeds are analyzed, and the best yaw speed is obtained. The finite control set of the yaw speed is established, which is used as the constraint set of the second-level minimum objective function. Finally, an external controller was used to simulate the 2.5MW wind turbine model in Bladed, and the effectiveness of the control strategy was verified.https://ieeexplore.ieee.org/document/9456969/Model predictive controlyaw angle thresholdfatigue loadlimited control set
spellingShingle Han Zhao
Lawu Zhou
Yu Liang
Shuowang Zhang
Mianzhuo Ma
A 2.5MW Wind Turbine TL-EMPC Yaw Strategy Based on Ideal Wind Measurement By LiDAR
IEEE Access
Model predictive control
yaw angle threshold
fatigue load
limited control set
title A 2.5MW Wind Turbine TL-EMPC Yaw Strategy Based on Ideal Wind Measurement By LiDAR
title_full A 2.5MW Wind Turbine TL-EMPC Yaw Strategy Based on Ideal Wind Measurement By LiDAR
title_fullStr A 2.5MW Wind Turbine TL-EMPC Yaw Strategy Based on Ideal Wind Measurement By LiDAR
title_full_unstemmed A 2.5MW Wind Turbine TL-EMPC Yaw Strategy Based on Ideal Wind Measurement By LiDAR
title_short A 2.5MW Wind Turbine TL-EMPC Yaw Strategy Based on Ideal Wind Measurement By LiDAR
title_sort 2 5mw wind turbine tl empc yaw strategy based on ideal wind measurement by lidar
topic Model predictive control
yaw angle threshold
fatigue load
limited control set
url https://ieeexplore.ieee.org/document/9456969/
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