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永磁同步风力发电系统的最大功率跟踪模糊分数阶控制OA北大核心CSTPCD

MPPT Fuzzy Fractional Control of Permanent-magnet Synchronous Wind Power Generation System

中文摘要英文摘要

在"双碳"背景下,风电作为零碳电力和新能源发电的主力军,在助力社会全面绿色低碳转型方面发挥了关键性作用.在保证发电稳定的前提下实现风能的最大化利用,提升风力发电系统发电量至为重要.文中针对永磁同步风力发电系统的最大功率跟踪(maximum power point tracking,MPPT)问题进行研究.首先建立了永磁同步风力发电系统的机理仿真模型,用两电平双PWM全功率换流器连接风力发电机与电网.然后基于以上模型,分别设计了整数阶PI控制器、分数阶PIλ控制器、模糊分数阶PIλ控制器以实现MPPT控制.最后对以上控制策略进行了仿真研究.结果表明,无论在阶跃风速还是随机风速下,模糊分数阶PIλ控制器相较于其他两种均具有更出色的MPPT性能与更强的鲁棒性.

As the the main force of zero-carbon electricity and renewable energy generation,wind power plays a key role in assisting the comprehensive green and low-carbon transforma-tion of society in the context of"dual carbon".It is crucial to maximize the utilization of wind energy and to increase the wind power generation system output while ensuring stable power generation.The maximum power point tracking(MPPT)problem of permanent-magnet synchronous wind power gener-ation system was investigated.Firstly,a mechanism simulation model of permanent-magnet synchronous wind power genera-tion system was established and a two-level dual-PWM full-power converter was used to connect the wind turbine to the grid.Secondly,based on the above model,an integer-order PI controller,fractional-order PIλcontroller and fuzzy fractional-order PI λ controller were designed to implement MPPT con-trol.Finally,simulation research was conducted on the above control strategics.The results show that the fuzzy fractional-or-der PIλ controller has better MPPT performance and better ro-bustness than the other two types,regardless of whether it is in step or random wind speed.

姜礼洁;王晓燕;苏杰;张镇韬

华北电力大学控制与计算机工程学院,河北省保定市 071003||河北省发电过程仿真与优化控制技术创新中心(华北电力大学),河北省保定市 071003华北电力大学控制与计算机工程学院,河北省保定市 071003

动力与电气工程

永磁同步风力发电系统两电平双PWM全功率换流器模糊分数阶控制器最大功率跟踪发电稳定

permanent magnet synchronous wind power gen-eration systemtwo-level dual PWM full rated converterfuzzy fractional-order controllerMPPTstable power gener-ation

《现代电力》 2024 (002)

230-239 / 10

河北省自然科学基金项目(E2018502111);河北省省级科技计划资助(22567643H).Project Supported by Natural Science Foundation of Hebei(E2018502111);S&T Program of Hebei(22567643H).

10.19725/j.cnki.1007-2322.2022.0248

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