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作 者:赵峰[1,2] 王淼 高峰阳 ZHAO Feng;WANG Miao;GAO Fengyang(The College of Electrical Engineering and Automation,Lanzhou Jiaotong University,Lanzhou 730070;Gansu Jiao Da Engineering Testing&Technology Company Limited,Lanzhou 730070)
机构地区:[1]兰州交通大学自动化与电气工程学院,兰州730070 [2]甘肃交达工程检测科技有限公司,兰州730070
出 处:《系统科学与数学》2020年第5期751-760,共10页Journal of Systems Science and Mathematical Sciences
基 金:甘肃省重点研发计划(18YF1FA058)资助课题。
摘 要:针对直驱永磁同步风电机组中出现的次同步振荡问题,建立引入次同步阻尼控制器(sub-synchronous oscillation damping controller,SSDC)后的直驱风电机组完整数学模型,在此基础上,以振荡模态特征值实部和阻尼比为目标函数建立了SSDC参数多目标优化模型.针对改进非支配解排序遗传算法(improved nondominated sorting genetic algorithm,NSGA-Ⅱ)在参数优化时种群多样性较差的问题,对其选择策略进行了改进,然后将改进后的NSGA-Ⅱ算法引入到SSDC参数优化设计中,利用空间评价方法对解集进行评价,结果表明采用改进算法所获得的Pareto最优解分布更加均匀.最后通过特征值分析和仿真验证,进一步证实了文章所优化设计得到的SSDC对发生在直驱风电机组的次同步振荡抑制具有显著效果.Aiming at the sub-synchronous oscillation in the direct-drive permanent magnet synchronous wind turbine generator,a complete mathematical model of direct-drive wind turbine with introducing the sub-synchronous oscillation damping controller(SSDC)is established.Based on it,a multi-objective optimization model of SSDC parameters is established,which takes both real part of oscillation mode eigenvalue and damping ratio as objective functions.In order to solve the problem of poor population diversity in the process of parameters optimization of improved nondominated sorting genetic algorithm(NSGA-Ⅱ),selection strategy of NSGA-Ⅱalgorithm is perfected,and the improved NSGA-Ⅱalgorithm is introduced into the design of SSDC parameters optimization,thus evaluating solution set by space evaluation method,the results show that Pareto optimal distribution obtained by the improved algorithm is more uniform.Finally,through eigenvalue analysis and simulation verification,it confirms that the SSDC optimized in this paper is of great significance to inhibit SSO in the direct-drive wind turbine.
关 键 词:直驱永磁同步风电机组 次同步振荡 次同步阻尼控制器 NSGA-Ⅱ算法
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