Redirigiendo al acceso original de articulo en 19 segundos...
ARTÍCULO
TITULO

A Spatial Analytics Framework to Investigate Electric Power-Failure Events and Their Causes

Vivian Sultan and Brian Hilton    

Resumen

The U.S. electric-power infrastructure urgently needs renovation. Recent major power outages in California, New York, Texas, and Florida have highlighted U.S. electric-power unreliability. The media have discussed the U.S. aging power infrastructure and the Public Utilities Commission has demanded a comprehensive review of the causes of recent power outages. This paper explores geographic information systems (GIS) and a spatially enhanced predictive power-outage model to address: How may spatial analytics enhance our understanding of power outages? To answer this research question, we developed a spatial analysis framework that utilities can use to investigate power-failure events and their causes. Analysis revealed areas of statistically significant power outages due to multiple causes. This study?s GIS model can help to advance smart-grid reliability by, for example, elucidating power-failure root causes, defining a data-responsive blackout solution, or implementing a continuous monitoring and management solution. We unveil a novel use of spatial analytics to enhance power-outage understanding. Future work may involve connecting to virtually any type of streaming-data feed and transforming GIS applications into frontline decision applications, showing power-outage incidents as they occur. GIS can be a major resource for electronic-inspection systems to lower the duration of customer outages, improve crew response time, as well as reduce labor and overtime costs.

Palabras claves

 Artículos similares

       
 
Aynaz Lotfata, Stefanos Georganos, Stamatis Kalogirou and Marco Helbich    
Some studies have established relationships between neighborhood conditions and health. However, they neither evaluate the relative importance of neighborhood components in increasing obesity nor, more crucially, how these neighborhood factors vary geogr... ver más

 
Miguel Saraiva, Irina Matijo?aitiene, Saloni Mishra and Ana Amante    
Crimes are a common societal concern impacting quality of life and economic growth. Despite the global decrease in crime statistics, specific types of crime and feelings of insecurity, have often increased, leading safety and security agencies with the n... ver más

 
Guiming Zhang    
Volunteer-contributed geographic data (VGI) is an important source of geospatial big data that support research and applications. A major concern on VGI data quality is that the underlying observation processes are inherently biased. Detecting observatio... ver más

 
Ming Zhang and Bolin Lan    
Urban science research and the research on megaregions share a common interest in the system of cities and its implications for world urbanization and sustainability. The two lines of inquiry currently remain largely separate efforts. This study aims to ... ver más
Revista: Urban Science

 
Stefanos Georganos and Stamatis Kalogirou    
The aim of this paper is to present developments of an advanced geospatial analytics algorithm that improves the prediction power of a random forest regression model while addressing the issue of spatial dependence commonly found in geographical data. We... ver más