A Hybrid MBO-VND algorithm to solve distribution network reconfiguration problem

The use of bio-inspired meta-heuristics in electrical engineering optimization problems is subject of a considerable number of studies, specially in distribution network reconfiguration (DNR). Such approaches shows to be of easy implementation and understanding, presenting, majorly, good results. As...

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Published in2021 14th IEEE International Conference on Industry Applications (INDUSCON) pp. 110 - 117
Main Authors Gerez, Cassio, Costa, Eduardo C. M., Sguarezi Filho, Alfeu J.
Format Conference Proceeding
LanguageEnglish
Published IEEE 15.08.2021
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DOI10.1109/INDUSCON51756.2021.9529542

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Abstract The use of bio-inspired meta-heuristics in electrical engineering optimization problems is subject of a considerable number of studies, specially in distribution network reconfiguration (DNR). Such approaches shows to be of easy implementation and understanding, presenting, majorly, good results. As systems grows in scale, the difficulty to find the best solution also increases, thus needing modifications in the original structure of such algorithms to improve the search. One way of doing that is through the use of a local search procedure using a second technique such as greedy adaptive search procedure (GRASP) and variable neighborhood search (VNS). These latter meta-heuristics normally needs a good starting point to reach the best result for the majority of systems. As bio-inspired meta-heuristics usually presents better results in comparison with auxiliary algorithms (e.g. Prim) normally used to find the starting points, such techniques can be used in replacement of it. In this context, this paper proposes a hybrid approach to solve DNR aiming losses reduction. The approach, named hybrid monarch butterfly optimizer variable neighborhood descent (HYMBOV), is based in the monarch butterfly optimization (MBO) and variable neighborhood descent (VND). In HYMBOV, MBO is used to search the best solution using a small number of iteration and, after that, VND seek for improvements in the solution with the MBO solution serving as the starting point. All the electrical analysis is performed through OpenDSS. The algorithm was fully discussed when tested in two well known systems of the literature: 33- and 84-bus.
AbstractList The use of bio-inspired meta-heuristics in electrical engineering optimization problems is subject of a considerable number of studies, specially in distribution network reconfiguration (DNR). Such approaches shows to be of easy implementation and understanding, presenting, majorly, good results. As systems grows in scale, the difficulty to find the best solution also increases, thus needing modifications in the original structure of such algorithms to improve the search. One way of doing that is through the use of a local search procedure using a second technique such as greedy adaptive search procedure (GRASP) and variable neighborhood search (VNS). These latter meta-heuristics normally needs a good starting point to reach the best result for the majority of systems. As bio-inspired meta-heuristics usually presents better results in comparison with auxiliary algorithms (e.g. Prim) normally used to find the starting points, such techniques can be used in replacement of it. In this context, this paper proposes a hybrid approach to solve DNR aiming losses reduction. The approach, named hybrid monarch butterfly optimizer variable neighborhood descent (HYMBOV), is based in the monarch butterfly optimization (MBO) and variable neighborhood descent (VND). In HYMBOV, MBO is used to search the best solution using a small number of iteration and, after that, VND seek for improvements in the solution with the MBO solution serving as the starting point. All the electrical analysis is performed through OpenDSS. The algorithm was fully discussed when tested in two well known systems of the literature: 33- and 84-bus.
Author Gerez, Cassio
Sguarezi Filho, Alfeu J.
Costa, Eduardo C. M.
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  organization: University of São Paulo,Dept of Energy and Electr. Eng.,São Paulo,Brazil
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  givenname: Eduardo C. M.
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  givenname: Alfeu J.
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  email: alfeu.sguarezi@ufabc.edu.br
  organization: Federal University of ABC,Center of Eng., Modell. and Appld. Sciences,Santo André-SP,Brazil
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Snippet The use of bio-inspired meta-heuristics in electrical engineering optimization problems is subject of a considerable number of studies, specially in...
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StartPage 110
SubjectTerms Conferences
distribution network reconfiguration
Distribution networks
Electrical engineering
hybrid algorithm
Industry applications
Linear programming
losses minimization
monarch butterfly optimization
Search problems
Sensitivity
variable neighborhood descent
Title A Hybrid MBO-VND algorithm to solve distribution network reconfiguration problem
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