湖南电力 ›› 2022, Vol. 42 ›› Issue (4): 40-45.doi: 10.3969/j.issn.1008-0198.2022.04.008

• 研究与试验 • 上一篇    下一篇

基于复合预测的LCL型光伏逆变器无差拍控制

李圣清1,2, 姚鑫1,2, 冯浩田1,2, 张栋1,2, 唐昕昀1,2   

  1. 1.湖南工业大学电气与信息工程学院,湖南 株洲 412007;
    2.光伏微电网智能控制技术湖南省工程研究中心,湖南 株洲 412007
  • 收稿日期:2022-03-10 修回日期:2022-04-19 出版日期:2022-08-25 发布日期:2022-10-14
  • 基金资助:
    国家自然科学基金(51977072,51807058);国家重点研发计划(2018YFB0606005)

Deadbeat Control of LCL Photovoltaic Inverter Based on Compound Prediction

LI Shengqing1,2, YAO Xin1,2, FENG Haotian1,2, ZHANG Dong1,2, TANG Xinyun1,2   

  1. 1. School of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China;
    2. Hunan Engineering Research Center for Intelligent Control Technology of Photovoltaic Microgrid, Zhuzhou 412007, China
  • Received:2022-03-10 Revised:2022-04-19 Online:2022-08-25 Published:2022-10-14

摘要: 针对光伏并网传统无差拍控制时间延时和预测精度不高的问题,提出一种基于复合预测的无差拍电流控制方法。首先分析时间延时和预测精度不高的原因;然后在负载稳定时,将拉格朗日插值法和重复预测相结合,提高电流预测精度;在负载变化时引入自适应前向线性电流预测,缩短系统振荡时间,增强动态响应能力;最后将两种方法复合控制,提前一拍预测逆变器输出电流,提前两拍预测采样参考电流,解决了时间延时问题。仿真结果表明该方法比补偿前的谐波含量降低了92%,振荡时间缩短了50%,具有更高的预测精度和动态响应能力,控制效果更佳。

关键词: 改进型无差拍控制, 拉格朗日插值法, 重复预测, 自适应前向线性电流预测, 复合预测

Abstract: Aiming at the problems of time delay and low prediction accuracy of traditional deadbeat control, a deadbeat current control based on composite prediction is proposed. This method first analyzes the reasons for the time delay and low prediction accuracy. Then, when the load is stable, Lagrange interpolation method and repeated prediction are combined to improve the current prediction accuracy. When the load changes, adaptive forward linear current prediction is introduced to shorten the system oscillation time and enhance the dynamic response ability. Finally, the two methods are combined for control. The inverter output current is predicted one beat in advance and the sampling reference current is predicted two beats in advance, which solves the problem of time delay. The simulation results show that this method reduces the harmonic content by 92% and the oscillation time by 50% compared with that before compensation. It has higher prediction accuracy and dynamic response ability, and better control effect.

Key words: improved deadbeat control, Lagrange polynomial, repeated prediction, adaptive forward linear current prediction, compound prediction

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