伍珀苇, 王子涵, 李庚银, 蔡德福, 孙冠群. 基于模型预测控制的光伏并网系统次同步振荡抑制策略研究[J]. 太阳能学报, 2024, 45(8): 349-357. DOI: 10.19912/j.0254-0096.tynxb.2023-0571
引用本文: 伍珀苇, 王子涵, 李庚银, 蔡德福, 孙冠群. 基于模型预测控制的光伏并网系统次同步振荡抑制策略研究[J]. 太阳能学报, 2024, 45(8): 349-357. DOI: 10.19912/j.0254-0096.tynxb.2023-0571
Wu Powei, Wang Zihan, Li Gengyin, Cai Defu, Sun Guanqun. RESEARCH ON SUB-SYNCHRONOUS OSCILLATION SUPPRESSION STRATEGY OF PHOTOVOLTAIC GRID-CONNECTED SYSTEM BASED ON MODEL PREDICTIVE CONTROL[J]. Acta Energiae Solaris Sinica, 2024, 45(8): 349-357. DOI: 10.19912/j.0254-0096.tynxb.2023-0571
Citation: Wu Powei, Wang Zihan, Li Gengyin, Cai Defu, Sun Guanqun. RESEARCH ON SUB-SYNCHRONOUS OSCILLATION SUPPRESSION STRATEGY OF PHOTOVOLTAIC GRID-CONNECTED SYSTEM BASED ON MODEL PREDICTIVE CONTROL[J]. Acta Energiae Solaris Sinica, 2024, 45(8): 349-357. DOI: 10.19912/j.0254-0096.tynxb.2023-0571

基于模型预测控制的光伏并网系统次同步振荡抑制策略研究

RESEARCH ON SUB-SYNCHRONOUS OSCILLATION SUPPRESSION STRATEGY OF PHOTOVOLTAIC GRID-CONNECTED SYSTEM BASED ON MODEL PREDICTIVE CONTROL

  • 摘要: 随着中国光伏装机容量的不断增加,规模化光伏并网会引入大量电力电子设备,光伏并网系统存在发生次同步振荡的风险。为解决其潜在的次同步振荡问题,提出基于模型预测控制的光伏并网系统次同步振荡抑制策略。首先,建立考虑逆变器控制延时的光伏并网系统小信号分析模型,采用参与因子分析法选取具有良好可观性和可控性的模型预测控制信号。其次,建立合适的目标函数及约束条件,通过模型预测控制器求解光伏并网系统的最优输入序列,使系统输出达到期望值,从而抑制系统振荡。最后,通过仿真验证该抑制策略的有效性和鲁棒性。

     

    Abstract: With the continuous increase of photovoltaic(PV) power in China, large-scale photovoltaic grid connection introduces a lot of power electronic devices, and there is a risk of sub-synchronous oscillation(SSO) in photovoltaic grid-connected systems. In order to solve the potential sub-synchronous oscillation problem of photovoltaic grid-connected system, a model predictive control method based SSO suppression strategy for PV grid-connected system is proposed. Firstly, establish a small signal analysis model for PV gridconnected system considering the inverter control delay, and use the participation factor analysis method to select model with good observability and controllability to predict control signal. Secondly, establish appropriate objective function and constraints, and solve the optimal input sequence of the system through model predictive controller to make the system output reach the expected value, thereby suppressing the system oscillation. Finally, the effectiveness and robustness of the SSO suppression strategy are verified through simulation.

     

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