Abstract: 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.

Abstract: 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.

Abstract: 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.