当电力系统遭受某种较大扰动时,其安全稳定将受到威胁.为实现对整个系统受扰后机电暂态过程的完整跟踪,提出一种新的融合同步发电机动态状态估计(dynamic state estimation of synchronous generator,DSE-SG)的电力系统状态估计(state estimation of power system,SE-PS),研究该如何将DSE-SG的结果进一步应用于系统侧SE-PS中去,以实现全系统动、静态状态量的统一估计.首先,围绕全电力系统机电暂态DSE的求解方式,论述了完全联立的不可行性、解耦估计的实现条件以及复耦估计的必要性与意义;其次,在梳理DSE-SG与SE-PS概念、数学模型的基础上,厘清了所涉变量、方程组的地位、作用、关系及数据流程,为复耦媒介量的选取及接口方式的确定奠定了理论基础,形成了复耦估计的实现构思;进一步,提出两种不同的接口方式,详细给出其各自具体的实现方法及流程;最后,将所提方法在IEEE9节点系统中予以实现,结果表明该方法可良好跟踪全电力系统机电暂态过程,实现动、静态状态量的统一估计,较未融合DSE-SG结果的传统SE-PS精度更高,滤波效果更显著.
A New Power System State Estimation Based on Synchronous Generator Dynamic State Estimation
When a power system suffers from some big disturbance,its security and stability will be threatened.To completely track the electro-mechanical transient process after disturbance,a new power system state estimation(SE-PS)based on dynamic state estimation of synchronous generator(DSE-SG)is proposed,and how to further apply the results of DSE-SG to system-side SE-PS is studied to achieve the unified estimation of the dynamic and static state variables of the entire system.Firstly,focusing on the solution of electro-mechanical transient DSE of the whole power system,the infeasibility of complete synchronization,the realization conditions of decoupling estimation,and the necessity and significance of re-coupling estimation are discussed.Secondly,based on the concepts and mathematical models of DSE-SG and SE-PS,the status,roles,relationships,and data flows of the variables and equations involved are clarified,which lays a theoretical foundation for the selection of re-coupling media and the determination of interface mode and forms the realization framework and idea of re-coupling estimation.Furthermore,two different interface modes are proposed,and their specific implementation methods and processes are given in detail.Finally,the proposed method is implemented in an IEEE9-bus system.The simulation results show that the method can track the electro-mechanical transient process of the whole power system well and realize the unified estimation of dynamic and static state variables.Compared with the traditional SE-PS without DSE-SG,the proposed method has higher accuracy and a more remarkable filtering effect.
power system state estimationsynchronous generator dynamic state estimationPMUKalman filteringelectro-mechanical transient
万方数据
维普
