skip to main content

Title: Robust Reconfiguration of A Distribution System

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.
 [1] ;  [1]
  1. University of Tennessee, Knoxville (UTK)
Publication Date:
OSTI Identifier:
DOE Contract Number:
Resource Type:
Resource Relation:
Conference: The 50th Huwaii International Conference on System Science, Waikoloa, HI, USA, 20170104, 20170107
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
Country of Publication:
United States
Distribution System Reconfiguration (DSR); Depth-First Search (DFS); Fuzzy Mixed Integer Programming (FMIP); Stochastic Mixed Integer Programming