DocumentCode :
1985566
Title :
Geospatial visualization of Smart data for improved network management
Author :
Poursharif, Goudarz ; Brint, Andrew ; Holliday, John ; Black, Mary ; Marshall, Mark
Author_Institution :
Manage. Sch. & Inf. Sch., Univ. of Sheffield, Sheffield, UK
fYear :
2015
fDate :
June 29 2015-July 2 2015
Firstpage :
1
Lastpage :
6
Abstract :
As the penetration level of embedded generation in the electricity distribution network rises, network operators´ need for real time and geographically accurate information about the Low Voltage (LV) network increases. Smart meters and network monitors are the main providers of Smart data to the network operators. However, the Smart data need to be presented to the users in meaningful ways, that are helpful, relevant, and accurate. This paper proposes a model that identifies the granularity of data required by network operators and the best ways in which the Smart data need to be visualized in order to enhance network operation applications such as network planning, asset management, and fault management, leading to smarter grid operation.
Keywords :
distributed power generation; power distribution planning; power system faults; power system management; smart meters; asset management; data granularity; electricity distribution network; embedded generation; fault management; geospatial visualization; low voltage network; network management; network monitor; network planning; smart data; smart meters; Substations; Data Visualization; Embedded Generation; Smart Data; Smart Grid; Smart Meters;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PowerTech, 2015 IEEE Eindhoven
Conference_Location :
Eindhoven
Type :
conf
DOI :
10.1109/PTC.2015.7232445
Filename :
7232445
Link To Document :
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