DocumentCode :
3387185
Title :
High performance computing platform for advanced distributed network operations
Author :
Wallom, David C. H. ; Salvini, Stef ; Lopatka, Piotr
Author_Institution :
Oxford e-Res. Centre, Univ. of Oxford, Oxford, UK
fYear :
2012
fDate :
14-17 Oct. 2012
Firstpage :
1
Lastpage :
5
Abstract :
The HiPerDNO project is a three-year EU-funded research project which studies novel applications for Distribution Network Operations (DNOs) and the platforms required to run these. These applications (distributed state estimation, power restoration, monitoring of assets) emerge from the large-scale deployment of sensors and instrumentation devices, responsive loads and embedded generation. Their introduction requires HPC strategy. A HiPerDNO HPC platform, which takes into account DNOs´ and applications requirements, has been built and several applications were developed and tested on it. In this paper we report on the results achieved.
Keywords :
condition monitoring; data mining; distributed power generation; distribution networks; load (electric); power engineering computing; power system measurement; power system restoration; power system state estimation; sensor placement; HiPerDNO HPC platform; HiPerDNO project; advanced distributed network operations; assets monitoring; distributed state estimation; embedded generation; high performance computing platform; instrumentation device; large-scale sensor deployment; power restoration; responsive loads; three-year EU-funded research project; Algorithm design and analysis; Condition monitoring; Engines; Monitoring; Pipelines; Security; State estimation; HPC; condition monitoring; distribution state estimation; power restoration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Smart Grid Technologies (ISGT Europe), 2012 3rd IEEE PES International Conference and Exhibition on
Conference_Location :
Berlin
ISSN :
2165-4816
Print_ISBN :
978-1-4673-2595-0
Electronic_ISBN :
2165-4816
Type :
conf
DOI :
10.1109/ISGTEurope.2012.6465832
Filename :
6465832
Link To Document :
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