Measurement data from smart meters installed at customers' load points are transferred from multiple data aggregation points (DAPs) to a local hub. This device serves as a master gateway for a neighborhood area network (NAN). Thus, the unavailability of a DAP will result in loss of data related to energy usage and measurement for all smart meters associated with the failed DAP. As a result, various DMS functions that use these data may be compromised, for example, energy billing and state estimation (SE). This paper proposes a hybrid method for assessing state estimation accuracy (SEA) in smart grids considering failures in smart meters and DAP. This method overcomes some disadvantages of conventional state selection and analytical approaches applied in SEA assessment. The tests demonstrated that the proposed method is as accurate as the crude Monte Carlo Simulation (MCS), but its computational cost is four times lower than the crude MCS.

中文翻译：

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智能电网状态估计器精度评估中的测量概率建模的混合概率方法

来自安装在客户负载点的智能电表的测量数据从多个数据聚合点（DAP）传输到本地集线器。此设备用作邻域网（NAN）的主网关。因此，DAP的不可用性将导致与与故障DAP相关的所有智能电表的能源使用和测量相关的数据丢失。结果，使用这些数据的各种DMS功能可能会受到影响，例如，能源账单和状态估计（SE）。本文提出了一种考虑智能电表和DAP故障的评估智能电网状态估计精度（SEA）的混合方法。该方法克服了常规状态选择和SEA评估中应用的分析方法的一些缺点。