Mixed-Integer Nonlinear Programming Formulation for Distribution Networks Reliability Optimization

2018 ◽  
Vol 14 (5) ◽  
pp. 1952-1961 ◽  
Author(s):  
Alireza Heidari ◽  
Zhao Yang Dong ◽  
Daming Zhang ◽  
Pierluigi Siano ◽  
Jamshid Aghaei
Keyword(s):  
Nonlinear Programming ◽  
Distribution Networks ◽  
Mixed Integer Nonlinear Programming ◽  
Mixed Integer ◽  
Reliability Optimization ◽  
Programming Formulation ◽  
Integer Nonlinear Programming

scholarly journals A Mixed-Integer Nonlinear Programming Model for Optimal Reconfiguration of DC Distribution Feeders

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4440 ◽  
Author(s):  
O. D. Montoya ◽  
W. Gil-González ◽  
J. C. Hernández ◽  
D. A. Giral-Ramírez ◽  
A. Medina-Quesada
Keyword(s):  
Nonlinear Programming ◽  
Power Flow ◽  
Distribution Networks ◽  
Mixed Integer Nonlinear Programming ◽  
Mixed Integer ◽  
Power Losses ◽  
Dc Distribution ◽  
Integer Nonlinear Programming ◽  
Minlp Model ◽  
Optimal Reconfiguration

This paper deals with the optimal reconfiguration problem of DC distribution networks by proposing a new mixed-integer nonlinear programming (MINLP) formulation. This MINLP model focuses on minimising the power losses in the distribution lines by reformulating the classical power balance equations through a branch-to-node incidence matrix. The general algebraic modelling system (GAMS) is chosen as a solution tool, showing in tutorial form the implementation of the proposed MINLP model in a 6-nodes test feeder with 10 candidate lines. The validation of the MINLP formulation is performed in two classical 10-nodes DC test feeders. These are typically used for power flow and optimal power flow analyses. Numerical results demonstrate that power losses are reduced by about 16% when the optimal reconfiguration plan is found. The numerical validations are made in the GAMS software licensed by Universidad Tecnológica de Bolívar.

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