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A novel model for tight radiality constraints incorporating dynamic parent–child selection and single commodity flow: An application of microgrid formation.

Authors :
Alizadeh, Ali
Kamwa, Innocent
Cao, Bo
Xu, Minghui
Source :
Electric Power Systems Research. Jun2024, Vol. 231, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

Maintaining radiality within distribution systems is crucial for reasons of control ease and financial efficiency. However, the extraction of a radial network from existing meshes poses significant challenges. Consequently, various approaches have been proposed by scholars to address the issue of maintaining radiality in distribution systems. Nevertheless, the practical application of these methods is limited due to their high tightness or compactness, leading to substantial computational burdens when dealing with real networks. In this paper, we present a novel model for radiality constraints that strikes a balance between tightness and compactness, aiming to enhance scalability and tractability. Furthermore, main feeders are discriminated from laterals in the proposed radiality model to further improve compactness. This idea significantly reduces the computational burden associated with real networks. Moreover, a microgrid (MG) formation problem is developed in which controllable and uncontrollable loads are considered. To evaluate the effectiveness of the proposed radiality constraints, they are tested in the developed MG formation problem. Meanwhile, the results are compared against other existing models. The comparisons demonstrate the superior performance and efficiency of the proposed radiality constraints and MG formation problem. • A compact and tight linear radiality constraints. • A dynamic parent–child selection equipped with single commodity flow • Creating a balance between tightness and compactness. • Discriminating main feeder sections and laterals in radiality constraints. • Microgrid formation considering controllable and uncontrollable loads. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
*MICROGRIDS
*LINEAR programming

Details

Language :
English
ISSN :
03787796
Volume :
231
Database :
Academic Search Index
Journal :
Electric Power Systems Research
Publication Type :
Academic Journal
Accession number :
176547316
Full Text :
https://doi.org/10.1016/j.epsr.2024.110332