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1. 发明授权

US10977593B1 Predictive models for electric power grid maintenance 有权
公开(公告)号：US10977593B1
公开(公告)日：2021-04-13
申请号：US16601519
申请日：2019-10-14
申请人： American Public Power Association Inc.
发明人： Alexander Hofmann , Michael John Hyland
IPC分类号： G06N20/00 , G06Q10/06 , G06Q50/06 , G06F11/34 , G06N3/08
摘要： Methods, systems, and apparatus, including computer-readable storage devices, for predictive models for electric power grid maintenance. In some implementations, one or more computers receive data indicating a maintenance action to be performed for a utility system. The one or more computers generate outcome scores for the maintenance action using a model generated from records for maintenance performed by multiple utilities. The one or more computers select one or more maintenance plan elements based on the outcome scores, provide an indication of the selected one or more maintenance plan elements for display, and store a record corresponding to the maintenance action. In some examples, the selected one or more maintenance plan elements can include recommended plan elements to improve the safety and efficiency of the maintenance action.

2. 发明授权

US09297723B1 Tracking and analyzing service outages 有权
标题翻译：跟踪和分析服务中断
公开(公告)号：US09297723B1
公开(公告)日：2016-03-29
申请号：US14541924
申请日：2014-11-14
申请人： American Public Power Association Inc.
发明人： Alexander Hofmann , Michael John Hyland
IPC分类号： G01W1/00 , G06Q10/00 , G01M99/00 , G06N99/00
CPC分类号： G01M99/00 , G01W1/00 , G01W2203/00 , G06N99/005 , Y02A90/14
摘要： Methods, systems, and apparatus, including computer-readable storage devices, for tracking and analyzing service outages. Weather data and outage data are accessed. Based on the weather data and the outage data, weather conditions corresponding to service outages are identified. A machine learning system is trained to estimate training a machine learning system to estimate effects of weather conditions on utility systems. Data for a particular utility system is provided to the trained machine learning system, and in response, output indicating estimated effects of future weather conditions on the particular utility system is received. The information that indicates the estimated effects of future weather conditions on the particular utility system is provided for display.
摘要翻译：用于跟踪和分析服务中断的方法，系统和装置，包括计算机可读存储装置。访问天气数据和中断数据。根据天气数据和中断数据，确定与服务中断对应的天气条件。训练机器学习系统来估计训练机器学习系统以估计天气条件对公用事业系统的影响。特定应用系统的数据被提供给训练有素的机器学习系统，并且作为响应，接收到指示未来天气状况对特定公用系统的估计影响的输出。提供了显示未来天气状况对特定公用事业系统的估计影响的信息。

3. 发明授权

US10445673B1 Predictive models for electric power grid maintenance 有权
公开(公告)号：US10445673B1
公开(公告)日：2019-10-15
申请号：US15921917
申请日：2018-03-15
申请人： American Public Power Association Inc.
发明人： Alexander Hofmann , Michael John Hyland
IPC分类号： G06N3/08 , G06Q10/06 , G06F11/34 , G06Q50/06 , G06N20/00
摘要： Methods, systems, and apparatus, including computer-readable storage devices, for predictive models for electric power grid maintenance. In some implementations, one or more computers receive data indicating a maintenance action to be performed for a utility system (e.g., an electric power delivery system, a water system, a gas distribution system), a location for the maintenance action, and environmental conditions at the location. In some examples, the one or more computers also receive data indicating a training level, incident history, or health status of a worker assigned to perform the maintenance action. The one or more computers generate outcome scores for the maintenance action using a model generated from records for maintenance performed by multiple utilities. The one or more computers access mapping data indicating a mapping of the multiple types of potential outcomes with a plurality of maintenance plan elements. The one or more computers select one or more maintenance plan elements based on the outcome scores, provide an indication of the selected one or more maintenance plan elements for display, and store a record corresponding to the maintenance action. In some examples, the selected one or more maintenance plan elements can include recommended plan elements to improve the safety and efficiency of the maintenance action.

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