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.
Highlights
Rapid advances in power electronics, i.e., conversion technologies, have transformed the classical distribution networks, where power comes from large scale generators interconnected through transmission grids to the substations, into modern electrical networks where interactions between generators and end-consumers have a place in the same voltage level [1,2,3]
The problem of the optimal reconfiguration in direct current networks can be represented as a mixed-integer nonlinear programming model based on the following facts: (i) the presence of binary variables regarding the selection of the branch l, i.e., xl, and (ii) the nonlinear relation between voltage and currents related to the power balance at each node of the network when constant power consumption is presented
This test feeder corresponds to a medium voltage DC grid projected to be operated at the nominal voltage of the distribution network in Bogotá city (This is a fictitious network employed in this paper to validate the use of the mixed-integer nonlinear programming (MINLP) proposed model for optimal reconfiguration of medium voltage DC networks), i.e., 11.40 kV which is composed by 12 nodes connected to the conversion station connected at node 1
Summary
Rapid advances in power electronics, i.e., conversion technologies, have transformed the classical distribution networks, where power comes from large scale generators interconnected through transmission grids to the substations, into modern electrical networks where interactions between generators and end-consumers have a place in the same voltage level (e.g., medium- or low-voltage distribution) [1,2,3]. An improved version has been proposed of the classical genetic algorithm, and all the numerical validations were made in the 33-node test feeder where the optimal reconfiguration plan optimises the grid operation (i.e., energy losses minimisation) when a shortage in renewables or electric vehicles are redispatched. This research is framed within the active distribution network analysis, in the DC distribution area, which presents a new MINLP model that represents the optimal reconfiguration problem in DC grids In this sense, we concentrate our efforts on the representation of the technical operative aspects of the network, i.e., operational variables such as currents in lines, voltages at nodes and power losses.
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