A mixed-integer nonlinear programming model for optimal reconfiguration of DC distribution feeders
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Date
2020-08-27
Authors
Montoya, O.D.
Gil-González, Walter
Hernández, Jesus C.
Giral-Ramírez, Diego Armando
Medina-Quesada, A.
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Abstract
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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Montoya, O.D.; Gil-González, W.; Hernández, J.C.; Giral-Ramírez, D.A.; Medina-Quesada, A. A Mixed-Integer Nonlinear Programming Model for Optimal Reconfiguration of DC Distribution Feeders. Energies 2020, 13, 4440.