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Data driven transfer functions and transmission network parameters for GIC modelling

机译:数据驱动传递函数和GIC建模传输网络参数

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Typical geomagnetically induced current (GIC) modelling assumes the induced quasi-DC current at a node in the transmission network is linearly related to the local geoelectric field by a pair of network parameters. Given a limited time-series of measured geomagnetic and GIC data, an empirical method is presented that results in a statistically significant generalised ensemble of parameter estimates with the error in the estimates identified. The method is showcased for different transmission networks and geomagnetic storms and, where prior modelling exists, shows improved GIC estimation. Furthermore, modelled networks can be locally characterised and probed without any further network knowledge. Insights include network parameter variation, effective network directionality and response. Merging the network parameters and geoelectric field estimation, a transfer function is derived which offers an alternative approach to assessing transformer exposure to GICs.
机译:典型的地磁感应电流(GIC)建模假设传输网络中的节点处的诱导的准直流电流与一对网络参数与局部地质电场线性相关。给定有限的时间序列的测量的地磁和差异数据数据,提出了一种经验方法,其导致参数估计的统计学上显着的集合,其中识别的估计中的误差。该方法被展示用于不同的传输网络和地磁风暴,并且在存在先前建模的情况下,显示出改善的差异性估计。此外,没有任何进一步的网络知识,可以在本地表征和探测建模网络。洞察包括网络参数变化,有效的网络方向性和响应。合并网络参数和地质电场估计,导出传递函数,其提供了一种评估变压器暴露于GIC的替代方法。

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