Multi-Objective Optimization and Reconstruction of Distribution Networks with Distributed Power Sources Based on an Improved BPSO Algorithm

The continuous integration of distributed power into the distribution network has increased the complexity of the distribution network and created challenges in distribution-network reconfiguration. In order to make the distribution network operate in the optimal mode, this paper establishes a multi-objective reconfiguration-optimization model that takes into account active network loss, voltage offset, number of switching actions and distributed power output. For a distribution network with a distributed power supply, it is easy for the traditional binary particle swarm optimization algorithm to fall into a local optimum. In order to improve the convergence speed of the algorithm and avoid premature convergence, this paper adopts an improved binary particle swarm optimization algorithm to solve the problem. The IEEE33 node system is used as an example for simulation verification. The experimental results show that the algorithm improves the convergence speed and global search ability, effectively reduces the system network loss, and greatly improves the voltage level of each node. It improves the stability and economy of distribution-network operation and can effectively solve the problem of multi-objective reconfiguration.

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Publication Details

Journal
Energies
Published
2024-09-28
DOI
https://doi.org/10.3390/en17194877
Citations
5
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
1.04

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article

Multi-Objective Optimization and Reconstruction of Distribution Networks with Distributed Power Sources Based on an Improved BPSO Algorithm

Qiang Fu, Linjuan Zhang, Wenfeng Li, Dan Lu et al.
5 citations
Energies
Optimal Power Flow Distribution
1.04
article

Multi-Objective Optimization and Reconstruction of Distribution Networks with Distributed Power Sources Based on an Improved BPSO Algorithm

Qiang Fu, Linjuan Zhang, Wenfeng Li, Dan Lu, Kai Wang, Q JIAO
article en
5 citations

Abstract

The continuous integration of distributed power into the distribution network has increased the complexity of the distribution network and created challenges in distribution-network reconfiguration. In order to make the distribution network operate in the optimal mode, this paper establishes a multi-objective reconfiguration-optimization model that takes into account active network loss, voltage offset, number of switching actions and distributed power output. For a distribution network with a distributed power supply, it is easy for the traditional binary particle swarm optimization algorithm to fall into a local optimum. In order to improve the convergence speed of the algorithm and avoid premature convergence, this paper adopts an improved binary particle swarm optimization algorithm to solve the problem. The IEEE33 node system is used as an example for simulation verification. The experimental results show that the algorithm improves the convergence speed and global search ability, effectively reduces the system network loss, and greatly improves the voltage level of each node. It improves the stability and economy of distribution-network operation and can effectively solve the problem of multi-objective reconfiguration.

EnergiesVol. 17(19)
NARI Group (China) (CN)
Economic Research Institute
Openalex Percentile: Top 23%
Optimal Power Flow Distribution
1.04
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