An Innovative Approach to Radiality Representation in Electrical Distribution System Reconfiguration: Enhanced Efficiency and Computational Performance

The reconfiguration problem (DPSR) in electrical distribution systems is a critical area of research, aimed at optimizing the operational efficiency of these networks. Historically, this problem has been approached through a variety of optimization methods. Regarding mathematical models, a key chall...

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Bibliographic Details
Published in:Energies (Basel) 2024-06, Vol.17 (11), p.2633
Main Authors: Cortés Sanabria, Pablo José, Tabares Pozos, Alejandra, Álvarez-Martínez, David, Noriega Barbosa, Diego Alejandro
Format: Article
Language:English
Subjects:
Artificial intelligence
computational efficiency
Efficiency
Integer programming
Linear programming
linearization techniques
mathematical modeling
Mathematical programming
Optimization techniques
power distribution system reconfiguration
radial operation
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Summary:The reconfiguration problem (DPSR) in electrical distribution systems is a critical area of research, aimed at optimizing the operational efficiency of these networks. Historically, this problem has been approached through a variety of optimization methods. Regarding mathematical models, a key challenge identified in these models is the formulation of equations that ensure the radial operation of the system, along with the nonlinear equations representing Kirchhoff’s laws, the last often necessitating complex relaxations for practical application. This paper introduces an alternative representation of system radiality, which potentially surpasses or matches the existing methods in the literature. Our approach utilizes a more intuitive and compact set of equations, simplifying the representation process. Additionally, we propose a linearization of the current calculation in the power flow model typically used to solve DPSR. This linearization significantly accelerates the process of obtaining feasible solutions and optimal reconfiguration profiles. To validate our approach, we conducted rigorous computational comparisons with the results reported in the existing literature, using a variety of test cases to ensure robustness. Our computational results demonstrate a considerable improvement in computational time. The objective functions used are competitive and, in many instances, outperform the best reported results in the literature. In some cases, our method even identifies superior solutions.
ISSN:1996-1073
1996-1073
DOI:10.3390/en17112633