Litcius/Paper detail

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

Oscar Danilo Montoya, Walter Gil-González, Jesús C. Hernández, D. Ramı́rez, A. Medina

2020Energies27 citationsDOIOpen Access PDF

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.

Topics & Concepts

Control reconfigurationIncidence matrixMathematical optimizationPower flowPower (physics)Nonlinear programmingInteger programmingInteger (computer science)Nonlinear systemPower BalanceMathematicsComputer scienceNode (physics)Electric power systemEngineeringEmbedded systemStructural engineeringPhysicsProgramming languageQuantum mechanicsOptimal Power Flow DistributionMicrogrid Control and OptimizationPower System Optimization and Stability