Design of Rated Power Control Strategy of Wind Turbine Based on Particle Swarm Optimization

2018 2nd International Conference on Power and Energy Engineering

Yang, Y.C.^1,2,3 ; Liu, Y.^2,3 ; Song, P.^2,3 ; Cui, Y.^2,3 ; Bai, Y.^1

Department of Control and Computer Engineering, North China Electric Power University, Beijing

102206, China^1

North China Electric Power Research Institute Co., Ltd., Smart Grid and New Energy Institute, Beijing

100045, China^2

Grid-connected Oper. Technol. for Wind-Solar-Storage Hybrid Syst. State Grid Corp. Key Laboratory, China^3

关键词: Control strategies;    Design and optimization;    Operating efficiency;    Particle swarm algorithm;    PI controller parameters;    Power control strategies;    Wind speed measurement;    Wind turbine modeling;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/192/1/012041/pdf
DOI  :  10.1088/1755-1315/192/1/012041

来源: IOP

【 摘 要 】

In view of the reduction of wind turbine operating efficiency caused by wind speed measurement errors, this paper proposes a rated power control strategy for wind turbines for practical applications; in order to solve the problem that the pitch PI controller parameters of wind turbines are not easy to calculate and tune in the process of design and optimization, this paper proposes a complete set of methods for parameter tuning of pitch control PI controllers for wind turbines. This paper establishes a Bladed-Matlab co-simulation platform, uses Bladed software to build a complete model of a 2MW wind turbine, and designs a rated power control strategy for wind turbines. After the wind turbine model is linearized at different wind speed points by applying Bladed software, the linearized model for PI parameter tuning is obtained, and then the optimal PI parameters for each wind speed point are set by using particle swarm algorithm. According to the variation law between the PI parameters and the pitch angle obtained before, the PI parameters are adjusted adaptively by variable gain PI control. The simulation results show the superiority of the control strategy and parameter tuning method used in this paper.