DocumentCode
30628
Title
Self-Healing Resilient Distribution Systems Based on Sectionalization Into Microgrids
Author
Zhaoyu Wang ; Jianhui Wang
Author_Institution
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Volume
30
Issue
6
fYear
2015
fDate
Nov. 2015
Firstpage
3139
Lastpage
3149
Abstract
This paper proposes a novel comprehensive operation and self-healing strategy for a distribution system with both dispatchable and nondispatchable distributed generators (DGs). In the normal operation mode, the control objective of the system is to minimize the operation costs and maximize the revenues. A rolling-horizon optimization method is used to schedule the outputs of dispatchable DGs based on forecasts. In the self-healing mode, the on-outage portion of the distribution system will be optimally sectionalized into networked self-supplied microgrids (MGs) so as to provide reliable power supply to the maximum loads continuously. The outputs of the dispatchable DGs will be rescheduled accordingly too. In order to take into account the uncertainties of DG outputs and load consumptions, we formulate the problems as a stochastic program. A scenario reduction method is applied to achieve a tradeoff between the accuracy of the solution and the computational burden. A modified IEEE 123-node distribution system is used as a test system. The results of case studies demonstrate the effectiveness of the proposed methodology.
Keywords
distributed power generation; power generation dispatch; stochastic programming; dispatchable distributed generators; modified IEEE 123-node distribution system; networked self-supplied microgrids; nondispatchable distributed generators; rolling-horizon optimization method; scenario reduction method; sectionalization; self-healing resilient distribution system; stochastic program; Distributed power generation; Microgrids; Optimization; Power distribution faults; Power system reliability; Stochastic processes; Uncertainty; Distributed power generation; microgrid (MG); power distribution; power distribution faults; self-healing; stochastic optimization;
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/TPWRS.2015.2389753
Filename
7017458
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