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Identifiability Analysis of Load Model Parameter Identification with Likelihood Profile Method

机译:似然曲线法的负荷模型参数辨识可识别性分析

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Load model parameter identification from practical measured data has become an essential method to build load models for power system simulation, analysis and control. With different power system practical measurement and operation conditions, which may include disturbance magnitudes, measurement errors and data lengths, the difficulty to identify load model parameters is also different, which would lead to the problem of practical identifiability. In this paper, a likelihood profile based parameter practical identifiability analysis method for load model identification is proposed. The load model structure and parameters used for identification and the method to identify parameters based on ambient signal are introduced first. The definition of identifiability together with the likelihood profile analysis method are then proposed, after which the procedures of load model parameter identifiability are given. Simulation is conducted in WSCC 9 bus system to show the effectiveness of the proposed method. Impact factors of load model parameter identifiability are also analyzed and simulated.
机译:从实际测量数据中识别负载模型参数已成为构建用于电力系统仿真,分析和控制的负载模型的重要方法。在不同的电力系统实际测量和操作条件下,可能包括扰动幅度,测量误差和数据长度,识别负载模型参数的难度也有所不同,这将导致实际可识别性问题。提出了一种基于似然分布的负荷模型辨识参数实用可识别性分析方法。首先介绍了用于识别的负荷模型结构和参数,以及基于环境信号识别参数的方法。提出了可识别性的定义以及似然分布分析方法,给出了负荷模型参数可识别性的过程。在WSCC 9总线系统中进行了仿真,以证明该方法的有效性。对载荷模型参数可识别性的影响因素也进行了分析和仿真。

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