Robust distribution network reconfiguration
- Argonne National Lab. (ANL), Argonne, IL (United States); Northwestern University
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Northwestern Univ., Evanston, IL (United States)
- Xi'an Jiaotong Univ., Xi'an (China)
We propose a two-stage robust optimization model for the distribution network reconfiguration problem with load uncertainty. The first-stage decision is to configure the radial distribution network and the second-stage decision is to find the optimal a/c power flow of the reconfigured network for given demand realization. We solve the two-stage robust model by using a column-and-constraint generation algorithm, where the master problem and subproblem are formulated as mixed-integer second-order cone programs. Computational results for 16, 33, 70, and 94-bus test cases are reported. As a result, we find that the configuration from the robust model does not compromise much the power loss under the nominal load scenario compared to the configuration from the deterministic model, yet it provides the reliability of the distribution system for all scenarios in the uncertainty set.
- Research Organization:
- Northwestern Univ., Evanston, IL (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
- Grant/Contract Number:
- SC0005102
- OSTI ID:
- 1321134
- Alternate ID(s):
- OSTI ID: 1392577
- Journal Information:
- IEEE Transactions on Smart Grid, Journal Name: IEEE Transactions on Smart Grid Journal Issue: 2 Vol. 6; ISSN 1949-3053
- Publisher:
- Institute of Electrical and Electronics Engineers (IEEE)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
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