DocumentCode :
1759591
Title :
Dynamic Partitioning of DC Microgrid in Resilient Clusters Using Event-Driven Approach
Author :
Simonov, Mikhail
Author_Institution :
Ist. Superiore Mario Boella, Turin, Italy
Volume :
5
Issue :
5
fYear :
2014
fDate :
Sept. 2014
Firstpage :
2618
Lastpage :
2625
Abstract :
An energy distribution network is a critical infrastructure that any compromise has an enormous impact on daily lives and the economy. The objective of this work is a computerized tool for distributed monitoring, dynamic re-configuration and control of DC distribution topology. This paper describes the double bar bus DC system exploiting the event-driven, service-oriented architecture, and real-time metering with nonuniform time sampling as an example of neighborhood optimization. We build a system with the capability to assess the resilience of and to rebuild better resilient grid partitions at run-time. The result is an intelligent system distributing loads between two buses dynamically in a way to keep self-sustainable and/or non-interruptible portion running at one bus by moving few other loads to the second bus. In standalone modality, the tool assesses the survivability of microgrid with high penetration of renewable energy. Running in cooperation with grid management tools, the same software can reconfigure optimally the local topology at run-time.
Keywords :
distributed power generation; power distribution control; power distribution reliability; power engineering computing; power system measurement; service-oriented architecture; DC distribution topology; DC microgrid; computerized tool; distributed monitoring; double bar bus DC system; dynamic partitioning; dynamic reconfiguration; energy distribution network; event-driven approach; grid management tools; microgrid survivability; nonuniform time sampling; real-time metering; resilient clusters; resilient grid partitions; service-oriented architecture; Microgrids; Optimization; Power system dynamics; Power system stability; Real-time systems; Resilience; Topology; Adaptive scheduling; energy management; intelligent control; microgrids; power system dynamics; power system reliability;
fLanguage :
English
Journal_Title :
Smart Grid, IEEE Transactions on
Publisher :
ieee
ISSN :
1949-3053
Type :
jour
DOI :
10.1109/TSG.2014.2302992
Filename :
6805667
Link To Document :
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