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Real-Time Dynamic Parameter Estimation for an Exponential Dynamic Load Model

机译:指数动态负荷模型的实时动态参数估计

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摘要

This paper is concerned about real-time modeling and identification of dynamically changing loads in power systems. An exponential dynamic load model was proposed earlier and was well accepted by several investigators who worked on this paper. This paper considers this model and identifies its parameters in real-time based on synchronously sampled measurements. An unscented Kalman filter is used to track the unknown parameters of the exponential dynamic load model. This paper first implements and tests the proposed method using simulated measurements. The method is then applied to actual recorded utility measurements to identify and track the bus load of the utility. The results are found to be promising, suggesting viability of tracking dynamic load models for online applications.
机译:本文关注电力系统中动态变化负载的实时建模和识别。较早提出了指数动态载荷模型,该模型已为从事本文工作的一些研究人员所接受。本文考虑了该模型,并基于同步采样的测量结果实时识别其参数。无味卡尔曼滤波器用于跟踪指数动态负载模型的未知参数。本文首先使用模拟测量来实施和测试该方法。然后将该方法应用于实际记录的公用事业测量,以识别和跟踪公用事业的总线负载。发现结果很有希望,表明跟踪在线应用程序的动态负载模型的可行性。

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