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虚拟同步发电机参数自适应控制策略 被引量:14

Parameter adaptive control strategy of virtual synchronous generator
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摘要 微电网具有低惯性和弱阻尼的特点,虚拟同步发电机技术可以改善其稳定性和动态响应性能,但传统虚拟同步发电机中的固定转动惯量和阻尼系数,不利于系统在不同工况下运行。文章提出一种基于模糊控制的虚拟同步发电机参数自适应控制策略,该策略借助虚拟同步发电机的数学模型,分析了转动惯量和阻尼系数对系统输出特性的影响;利用角频率偏差及其变化率确定模糊规则,根据不同工况实时调节转动惯量和阻尼系数的大小,确保微电网频率的稳定。仿真和试验结果表明,文章所提控制策略可有效抑制系统暂态振荡,进而提高微电网的运行性能。 Microgrid has the characteristics of low inertia and weak damping.Its stability and dynamic response performance can be improved by the virtual synchronous generator technology.However,the fixed moment of inertia and damping coefficient in the traditional virtual syn-chronous generator are not favorable for the system to operate under different operating conditions.Therefore,a parameter adaptive control strategy for virtual synchronous generator based on fuzzy control is proposed.By means of the mathematical model of the virtual syn-chronous generator,the influences of the moment of inertia and the damping coefficient on the output characteristics of the system are analyzed.The angular frequency deviation and its rate of change are used to determine the fuzzy rule,and the moment of inertia and damping coefficient are adjusted in real time according to different working conditions to ensure the stability of the microgrid’s frequency.Simulation and experimental results show that the proposed control strategy can effectively suppress the transient oscillation of the system and improve the operation performance of the microgrid.
作者 程国栋 邵宣 王贵峰 Cheng Guodong;Shao Xuan;Wang Guifeng(Xuhai College,China University of Mining and Technology,Xuzhou 221008,China;School of Electrical and Power Engineering,China University of Mining and Technology,Xuzhou 221008,China;School of Electrical Engineering&Automation,Jiangsu Normal University,Xuzhou 221008,China)
出处 《可再生能源》 CAS CSCD 北大核心 2021年第12期1655-1661,共7页 Renewable Energy Resources
基金 国家自然科学基金资助项目(51707086) 江苏省高等学校自然科学研究面上项目(18KJD470007)。
关键词 虚拟同步发电机 转动惯量 阻尼系数 模糊控制 自适应控制 virtual synchronous generator moment of inertia damping coefficient fuzzy control adaptive control
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