DocumentCode
41704
Title
Security Enhancement With Nodal Criticality-Based Integration of Strategic Micro Grids
Author
Jayaweera, Dilan
Author_Institution
Dept. of Electr. & Comput. Eng., Curtin Univ., Perth, WA, Australia
Volume
30
Issue
1
fYear
2015
fDate
Jan. 2015
Firstpage
337
Lastpage
345
Abstract
Security enhancement of distribution networks are constrained with multiple causes including limited availability of network resources and high penetration of intermittent distributed generation. In that context, this paper proposes a new methodology to enhance the security of power supply in a distribution network by strategically integrating plug-in hybrid electric vehicle (PHEV) micro grids based on the nodal criticality. The nodal criticality is assessed by integrating operational uncertainties of events into samples of Monte Carlo simulation and then classifying load interruptions on the basis of their magnitudes and frequencies. The load shedding due to criticality of system stress is classified into arrays of clusters on the basis of magnitudes of interrupted loads. The critical clusters that provide the largest disturbances to nodal loads are used as the reference capacities of PHEV micro grids to mitigate impacts. Case studies are performed by applying the methodology into a realistic model of a distribution network. Results depict that the proposed methodology can improve the system-wide security of supply. There are some nodes of which the security of supply can be improved significantly. The levels of improvement in security of supply of nodes are not consistent and some nodes can also receive marginal improvements.
Keywords
Monte Carlo methods; distributed power generation; hybrid electric vehicles; power distribution reliability; Monte Carlo simulation; distribution network; interruption classification; nodal criticality based integration; plug-in hybrid electric vehicle; power supply security; security enhancement; strategic microgrids; system wide supply security; Convergence; Distributed power generation; Generators; Load modeling; Monte Carlo methods; Security; Time series analysis; Distribution network planning; Monte Carlo simulation; grid integration of renewables; security of power supply;
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/TPWRS.2014.2327120
Filename
6827248
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