A New Mathematical Model for the Restoration Problem in Balanced Radial Distribution Systems

This paper presents a comprehensive mathematical model to solve the restoration problem in balanced radial distribution systems. The restoration problem, originally modeled as mixed integer nonlinear programming, is transformed into a mixed integer second-order cone programming problem, which can be...

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Bibliographic Details
Published in:IEEE transactions on power systems Vol. 31; no. 2; pp. 1259 - 1268
Main Authors: Romero, Ruben, Franco, John F., Leao, Fabio B., Rider, Marcos J., de Souza, Eliane S.
Format: Journal Article
Language:English
Published: New York IEEE 01.03.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Distribution system optimization
Linear programming
Load modeling
Manuals
Mathematical model
Mathematical models
Mixed integer
mixed integer second-order cone programming
Nonlinear programming
Optimization
Optimization techniques
Radial distribution
Restoration
restoration problem
Substations
Switches
Switching circuits
ISSN:0885-8950, 1558-0679
Online Access:Get full text
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Summary:This paper presents a comprehensive mathematical model to solve the restoration problem in balanced radial distribution systems. The restoration problem, originally modeled as mixed integer nonlinear programming, is transformed into a mixed integer second-order cone programming problem, which can be solved efficiently using several commercial solvers based on the efficient optimization technique family branch and bound. The proposed mathematical model considers several objectives in a single objective function, using parameters to preserve the hierarchy of the different objectives: 1) maximizing the satisfaction of the demand, 2) minimizing the number of switch operations, 3) prioritizing the automatic switch operation rather than a manual one, and 4) prioritizing especial loads. General and specialized tests were carried out on a 53-node test system, and the results were compared with other previously proposed algorithms. Results show that the mathematical model is robust, efficient, flexible, and presents excellent performance in finding optimal solutions.
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ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2015.2418160