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双馈异步风机控制模态交互与内部谐振问题研究

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随着国家能源结构的转型以及实施"双碳"战略,大规模风电持续接入电力系统,对系统带来了交互谐振以及变流器驱动稳定性等问题.通过研究双馈异步风机机侧变流器以及网侧变流器控制外环的控制参数对稳定性的影响,发现机侧变流器控制外环的参数稳定区均位于左下平面,网侧变流器外环控制参数稳定区位于右下平面,参数稳定区与不稳定区之间存在着带状的参数风险区.当增大网侧变流器控制器的比例系数与积分系数时,系统阻尼将增强,但在某个区间会产生强烈的交互作用进而发生内部谐振,导致系统失去稳定.针对网侧变流器控制器之间的强烈交互作用,引入粒子群算法对网侧变流器的PI控制器进行参数优化,优化后直流电压恢复速度缩短半个周期,超调量减少40%.
A Study of Control Modal Interaction and Internal Resonance of DFIG
With the transformation of the national energy structure and the implementation of the"dual-carbon"strategy,large-scale wind power continues to be connected to the power system,which brings problems such as interactive resonance and converter drive stability to the system.By studying the influence of the control parameters of the machine-side converter and the outer ring of the grid-side converter control on the stability of doubly-fed asynchronous wind turbines,it is found that the parameter stabilization zones of the outer ring of the machine-side converter control are located in the lower left plane,and that the parameter stabilization zones of the outer ring of the grid-side converter control are located in the lower right plane,and that there exists a band of parameter risk areas between the parameter stabilization zones and the instability zones.When increasing the proportional and integral coefficients of the grid-side converter controllers,the system damping will be enhanced,but in a certain interval,a strong interaction and thus internal resonance will occur,leading to system destabilization.For the strong interaction between the controllers of the grid-side converter,Particle Swarm Optimization(PSO)is introduced to optimize the parameters of the PI controllers of the grid-side converter,and the optimization shortens the DC voltage recovery speed by half a cycle and reduces the overshooting amount by 40%.

doubly fed induction generatormodal interactioninternal resonancecontrol parametersparameter optimization

罗坚强、黎浩贤、杨苓

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广东工业大学 自动化学院,广东 广州 510006

广东电网有限责任公司 江门供电局,广东 江门 529000

双馈异步风机 模态交互 内部谐振 参数设计 参数优化

广东省自然科学基金资助项目广东省自然科学基金资助项目广州市基础与应用基础研究基金资助项目

2023A15152400102024A15150110182024A04J4673

2024

广东工业大学学报
广东工业大学

广东工业大学学报

影响因子:0.628
ISSN:1007-7162
年,卷(期):2024.41(5)