基于Bladed风电机组变速与变桨距控制器参数优化

系统仿真学报 ›› 2016, Vol. 28 ›› Issue (7): 1644-1651.

基于Bladed风电机组变速与变桨距控制器参数优化

高峰, 王伟, 凌新梅

华北电力大学控制与计算机工程学院,北京 102206

收稿日期:2015-03-10 修回日期:2015-11-12 出版日期:2016-07-08 发布日期:2020-06-04
作者简介:高峰(1976-), 男, 山东, 博士, 讲师, 研究方向为风电机组建模与控制; 王伟(1988-), 男, 河南, 硕士, 研究方向为风电机组控制优化; 凌新梅(1991-), 女, 河北, 硕士, 研究方向为风电机组控制优化。
基金资助:
中央高校基本科研业务费(2015MS24)

Parameters Optimization for Variable Speed and Pitch Controller of Wind Turbine Based on Bladed

Gao Feng, Wang Wei, Ling Xinmei

School of Control and Computer Engineering, North China Electric Power University, Changping District, Beijing 102206, China

Received:2015-03-10 Revised:2015-11-12 Online:2016-07-08 Published:2020-06-04

摘要/Abstract

摘要： 由于风力发电系统具有非线性和参数时变等特点,其控制器参数在设计和优化时不易计算与整定。利用Bladed软件中模型线性化结合模型降阶算法建立了适用于参数整定的机组线性化模型,应用免疫记忆粒子群算法整定控制器PI(Proportion Integral)参数,并基于Bladed参数辨识结果计算了最优转速-转矩控制的增益系数和自适应PI变桨距控制的增益因子,形成了一种基于Bladed的风电机组变速与变桨距控制器参数优化方法。仿真结果表明了该优化方法的正确性和有效性。

关键词: 风电机组, Bladed, 控制器, 优化, 免疫记忆粒子群算法

Abstract: Due to nonlinearity and time-varying parameters of wind power system, its controller parameters are hard to be calculated and tuned during the process of design and optimization. The linear model which is suitable for parameters tuning was built through model linearization of Bladed and model reducing-order algorithm. The PI parameter was tuned with the IM-PSO (Immune Memory Particle Swarm Optimization). Moreover, the gain coefficient of optimal torque control and the gain divisor of adaptive PI pitch control conducted optimizing calculation based on the identification parameters of Bladed. A set of optimization method for variable speed and pitch controller of wind turbine was established. The simulation results show the validity and advantages of the proposed methods.

Key words: wind turbine, Bladed, controller, optimization, immune memory particle swarm optimization

中图分类号:

TM614

高峰, 王伟, 凌新梅. 基于Bladed风电机组变速与变桨距控制器参数优化[J]. 系统仿真学报, 2016, 28(7): 1644-1651.

Gao Feng, Wang Wei, Ling Xinmei. Parameters Optimization for Variable Speed and Pitch Controller of Wind Turbine Based on Bladed[J]. Journal of System Simulation, 2016, 28(7): 1644-1651.

参考文献 16

[1]	G L Garrad Hassan. Bladed User Manual (Version 4.2)[M]. England: Garrad Hassan & Partners Ltd., 2011.
[2]	Y Bekakra, D B Attous.Optimal tuning of PI controller using PSO optimization for indirect power control for DFIG based wind turbine with MPPT[J]. International Journal of System Assurance Engineering and Management (S0975-6809), 2014, 5(3): 219-229.
[3]	A Ali, A Moussa, K Abdelatif, et al.Comparative performance of wind turbine driven PMSG with PI-controllers tuned using heuristic optimization algorithms[C]// IEEE International Energy Conference. Croatia: Institute of Electrical and Electronics Engineers, 2014: 120-126.
[4]	吴峰, 汪海洋, 金宇清. 基于正交优选粒子群算法的双馈风电系统控制器参数优化整定[J]. 电力系统自动化, 2014, 38(15): 19-24.
[5]	Jordi Zaragoza, Josep Pou, Antoni Arias, et al.Study and experimental verification of control tuning strategies in a variable speed wind energy conversion system[J]. Renewable Energy (S0960-1481), 2010, 36(10): 1421-1430.
[6]	Bourdoulis K M, Alexandridis T A.Rotor-side cascaded PI controller design and gain tuning for DFIG wind turbines[C]// 4th International Conference on Power Engineering, Energy and Electrical Drives. Turkey: Institute of Electrical and Electronics Engineers. USA: IEEE, 2013: 733-738.
[7]	Wei Qiao, Ganesh K Venayagamoorthy, Ronald G Harley.Design of Optimal PI Controllers for Doubly Fed Induction Generators Driven by Wind Turbines Using Particle Swarm Optimization[C]// 2006 International Joint Conference on Neural Networks. Vancouver BC Canada: Institute of Electrical and Electronics Engineers (IEEE), 2006: 1982-1987.
[8]	林今, 李国杰, 孙元章, 等. 双馈风电机组的小信号分析及其控制系统的参数优化[J]. 电力系统自动化, 2009, 33(5): 86-90.
[9]	G L Garrad Hassan. Bladed Theory Manual (Version 4.2)[M]. England: Garrad Hassan & Partners Ltd., 2011.
[10]	郭鹏. 模糊前馈与模糊PID结合的风力发电机组变桨距控制[J]. 中国电机工程学报, 2010, 30(8): 123-128.
[11]	叶杭冶. 风力发电机组监测与控制 [M]. 北京: 机械工业出版社, 2013.
[12]	Zhuang M, Atherton D P.Automatic tuning of optimum PID controllers[J]. Proceedings of IEE (S0018-9219), 1993, 140: 216-224.
[13]	薛定宇. 控制系统计算机辅助设计 [M]. 2版北京: 清华大学出版社, 2006.
[14]	Bo Gu, Xiaodan Li, Daoyin Qiu, et al.Study on PI Parameters Dynamic Tuning Based on Ant Colony Algorithm for Doubly-fed Wind Turbines[J]. International Journal of Control and Automation (S2005-4297), 2014, 7(2): 327-340.
[15]	王纪亮, 焦晓红. 变速恒频双馈风力发电系统RBF网络整定PID控制器设计[J]. 太阳能学报, 2011, 32(3): 311-317.
[16]	王爽心, 李朝霞. 变桨距风电机组自适应PI优化控制[J]. 太阳能学报, 2013, 34(9): 311-317.