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风速影响下的风机变流器控制策略研究 被引量:4

Research on the Control Strategy of Wind Turbine Converter under Influence of Wind Speed
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摘要 风能是目前规模化开发利用的一种高效清洁的可再生能源。风力发电技术的研究备受关注,脉冲宽度调制(PWM)变流器控制研究已经成为当今风电研究领域的重要方向之一。为改善风力发电中风速变化对双馈风力异步发电机(DFIG)的影响,对风机变流器的直接功率控制方法进行研究和改进,提出了一种基于Smith预估模型的自适应模糊PI控制策略。在经典PI控制策略的基础上,采用具有自学习、自整定功能的自适应模糊PI调节,引入Smith预估模型,利用PSCAD软件进行仿真,优化变流器的控制方法,解决系统的纯滞后问题,提高系统的稳定性。仿真结果表明,在风速波动的情况下,该方案能使DFIG稳定运行,提高了系统的鲁棒性。同时,其输出电能可以满足电网电能质量要求,实现风电并网。基于Smith预估模型的自适应模糊PI控制策略具有较高的可行性和优越性。 Wind power is one of the high efficient and clean renewable energy resources,and it is the large-scale exploitation and utilization at present.The research on wind power generation technology is much to be concerned,while the topic of research on control of plulse width modulation(PWM) converter has become one of the important directions in wind power field.To improve the influence of variation of wind speed on doubly-fed induction generator(DFIG),the direct power control method of wind turbine converter is studied and improved,and an adaptive fuzzy PI control strategy based on Smith prediction model is proposed.Based on the classical PI control strategy,the adaptive fuzzy PI control with self-learning and self-tuning functions is adopted.The Smith prediction model is introduced,and the PSCAD software is used to simulate and optimize the control method of the converter and to solve the dead time problem of system,to improve the stability of system.The results show that the proposed scheme can make the doubly fed induction generator run stably,and improve the robustness of the system under wind speed fluctuation.In addition,the output power can meet the quality requirements of the grid,to achieve wind power to be grid connected.The adaptive fuzzy PI control strategy based on the Smith prediction model features good feasibility and superiority.
作者 李洁 刘岩
出处 《自动化仪表》 CAS 2017年第4期93-95,共3页 Process Automation Instrumentation
基金 商洛市科技厅基金资助项目(SK2014-01-01)
关键词 新能源 风力发电 发电机 Smith预估模型 模糊自适应 PI控制 New energy Wind power generation Generator Smith predictive model Fuzzy adaptive PI control
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