Systematic Framework for Integration of Weather Data into Prediction Models for the Electric Grid Outage and Asset Management Applications
Systematic Framework for Integration of Weather Data into Prediction Models for the Electric Grid Outage and Asset Management Applications
复制标题
将天气数据集成到电网停电和资产管理应用的预测模型中的系统框架
DOI：
10.24251/hicss.2018.346
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发表时间：
2018
期刊：
影响因子：
3.9
通讯作者：
S. Roychoudhury
中科院分区：
文献类型：
--
作者：
M. Kezunovic;Z. Obradovic;Tatjana Djokic;S. Roychoudhury
本文描述了一个天气影响模型（WIM），该模型能够服务于各种预测应用，从实时运行和提前一天的运行计划，到资产和停电管理。所提出的模型能够将各种天气参数组合成特定应用感兴趣的不同天气影响特征。本研究的重点是开发一个基于地理信息系统（GIS）中嵌入的逻辑回归的通用天气影响模型。它能够将从历史停电和天气数据到实时天气预报和网络监测测量的大量数据集合并为一个称为天气灾害概率的功能。停机和资产管理应用程序的示例用于说明模型功能。
This paper describes a Weather Impact Model (WIM) capable of serving a variety of predictive applications ranging from real-time operation and day-ahead operation planning, to asset and outage management. The proposed model is capable of combining various weather parameters into different weather impact features of interest to a specific application. This work focuses on the development of a universal weather impacts model based on the logistic regression embedded in a Geographic Information System (GIS). It is capable of merging massive data sets from historical outage and weather data, to real-time weather forecast and network monitoring measurements, into a feature known as weather hazard probability. The examples of the outage and asset management applications are used to illustrate the model capabilities.