考虑储能SOC的RBF自适应VSG控制策略  

RBF Adaptive VSG Control Strategy Considering Energy Storage SOC

作　　者：袁涛 杜振东 YUAN Tao;DU Zhendong(Shanghai University of Electric Power,Shanghai 200090,China;Zhejiang Huayun Electric Power Engineering Design Consulting Co.,Ltd.,Hangzhou,Zhejiang 310014,China)

机构地区：[1]上海电力大学,上海200090 [2]浙江华云电力工程设计咨询有限公司,浙江杭州310002

出　　处：《上海电力大学学报》2023年第5期436-442,452,共8页Journal of Shanghai University of Electric Power

摘　　要：采用虚拟同步发电机(VSG)控制策略的并网逆变器可为分布式能源提供必要的惯性阻尼特性,以支撑电网频率。VSG的惯量和阻尼特性均受储能荷电状态(SOC)约束,因此有必要维持储能SOC水平,避免储能VSG失去惯量阻尼特性。设计了基于SOC的储能充放电系数,结合径向基函数(RBF)神经网络控制,提出了一种储能VSG参数自适应控制策略,并通过MATLAB/Simulink仿真,验证了所提策略的有效性和优越性。A grid-connected inverter using a virtual synchronous generator(VSG)control strategy can generate the necessary inertial damping characteristics for distributed energy to support the grid frequency.The inertia and damping characteristics of the VSG are both constrained by the energy storage SOC,so it is necessary to maintain the energy storage SOC level to prevent the energy storage VSG from losing its inertia damping characteristics.In this paper,an energy storage charge and discharge coefficient based on SOC is designed,and an adaptive control strategy for energy storage VSG parameters is proposed in combination with Radial Basis Function(RBF)neural network control.Finally,the effectiveness and superiority of the proposed strategy is verified by MATLAB/Simulink.

关 键 词：虚拟同步发电机 储能 惯性时间常数 阻尼系数 神经网络 

分 类 号：TM712[电气工程—电力系统及自动化]