Robust Reconfiguration of A Distribution System

dc.contributor.author Moradzadeh, Benyamin
dc.contributor.author Liu, Guodong
dc.contributor.author Tomsovic, Kevin
dc.date.accessioned 2016-12-29T01:14:56Z
dc.date.available 2016-12-29T01:14:56Z
dc.date.issued 2017-01-04
dc.description.abstract In this paper, a robust reconfiguration approach based on Mixed Integer Programming (MIP) is proposed to minimize loss in distribution systems. A Depth-First Search (DFS) algorithm to enumerate possible loops provides radiality constraint. This provides a general solution to the radiality constraint for distribution system reconfiguration/expansion problems. Still, imprecision and ambiguity in net loads, i.e., load minus renewable generation, due to lack of sufficient measurements and high utilization of demand response programs and renewable resources, creates challenges for effective reconfiguration. Deterministic optimization of reconfiguration may no lead to optimal/feasible results. Two methods to address these uncertainties are introduced in this paper: one, based on a stochastic MIP (SMIP) formulation and two, based on a fuzzy MIP (FMIP) formulation. Case studies demonstrate the robustness and efficiency of the proposed reconfiguration methods.
dc.format.extent 9 pages
dc.identifier.doi 10.24251/HICSS.2017.391
dc.identifier.isbn 978-0-9981331-0-2
dc.identifier.uri http://hdl.handle.net/10125/41547
dc.language.iso eng
dc.relation.ispartof Proceedings of the 50th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Distribution System Reconfiguration (DSR)
dc.subject Depth-First Search (DFS)
dc.subject Fuzzy Mixed Integer Programming (FMIP)
dc.subject Stochastic Mixed Integer Programming (SMIP).
dc.title Robust Reconfiguration of A Distribution System
dc.type Conference Paper
dc.type.dcmi Text
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