Optimal Placement of Wireless Smart Concentrators in Power Distribution Networks Using a Metaheuristic Approach

The optimal allocation of Wireless Smart Concentrators (WSCs) in low-voltage (LV) distribution networks poses significant challenges due to signal attenuation caused by varying building densities and vegetation. This paper proposes a Variable Neighborhood Search (VNS) algorithm to optimize the placement of WSCs in LV distribution networks. To comprehensively assess the proposed approach, both linear and nonlinear mathematical formulations are considered, depending on whether the distance between meters and concentrators is treated as a fixed parameter or as a decision variable. The performance of the proposed VNS algorithm is benchmarked against both exact solvers and metaheuristics such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Tabu Search (TS). In the linear formulation, VNS achieved the exact optimal solution with execution times up to 75% faster than competing methods. For the more complex nonlinear model, VNS consistently identified superior solutions while requiring less computational effort. These results underscore the algorithm’s ability to balance solution quality and efficiency, making it particularly well-suited for large-scale, resource-constrained utility planning.

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Publication Details

Journal
Energies
Published
2025-08-30
DOI
https://doi.org/10.3390/en18174604
Citations
1
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
Field-Weighted Citation Impact
0.73

Funders

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article

Optimal Placement of Wireless Smart Concentrators in Power Distribution Networks Using a Metaheuristic Approach

Nicolás Muñóz-Galeano, Jesús M. López‐Lezama, Richard Wilcamango-Salas, Cristoercio A. Silva et al.
1 citations
Energies
Energy Harvesting in Wireless Networks
0.73
article

Optimal Placement of Wireless Smart Concentrators in Power Distribution Networks Using a Metaheuristic Approach

Nicolás Muñóz-Galeano, Jesús M. López‐Lezama, Richard Wilcamango-Salas, Cristoercio A. Silva, Joel D. Melo
article en
1 citations

Abstract

The optimal allocation of Wireless Smart Concentrators (WSCs) in low-voltage (LV) distribution networks poses significant challenges due to signal attenuation caused by varying building densities and vegetation. This paper proposes a Variable Neighborhood Search (VNS) algorithm to optimize the placement of WSCs in LV distribution networks. To comprehensively assess the proposed approach, both linear and nonlinear mathematical formulations are considered, depending on whether the distance between meters and concentrators is treated as a fixed parameter or as a decision variable. The performance of the proposed VNS algorithm is benchmarked against both exact solvers and metaheuristics such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Tabu Search (TS). In the linear formulation, VNS achieved the exact optimal solution with execution times up to 75% faster than competing methods. For the more complex nonlinear model, VNS consistently identified superior solutions while requiring less computational effort. These results underscore the algorithm’s ability to balance solution quality and efficiency, making it particularly well-suited for large-scale, resource-constrained utility planning.

EnergiesVol. 18(17)
Universidad de Antioquia (CO), Universidade Federal do ABC (BR)
Universidade Federal do ABC, Fundação de Amparo à Pesquisa do Estado de São Paulo, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Instituto Nacional de Energia Elétrica
Openalex Percentile: Top 24%
Energy Harvesting in Wireless Networks
0.73
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