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Physics Maths Engineering

A multi-agent-based symbiotic organism search algorithm for DG coordination in electrical distribution networks

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Shamte Kawambwa,

Shamte Kawambwa


Daudi Mnyanghwalo

Daudi Mnyanghwalo


  Peer Reviewed

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© attribution CC-BY

  • 0

rating
479 Views

Added on

2024-12-25

Doi: https://doi.org/10.1186/s43067-023-00072-7

Related Subjects
Physics
Math
Chemistry
Computer science
Engineering
Earth science
Biology

Abstract

AbstractMetaheuristic algorithms have become popular in solving engineering optimization problems due to their advantages of simple implementation and the ability to find near-optimal solutions for complex and large-scale problems. However, most applications of metaheuristic algorithms consider centralized design, assuming that all possible solutions are available in one machine or controller. In some applications, such as power systems, especially DG coordination, centralized design may not be efficient. This work integrates a multi-agent system (MAS) into a metaheuristic algorithm for enhanced performance. In a proposed multi-agent framework, the agent implements a metaheuristic algorithm and uses shared information with neighbours as input to optimize the solutions. In this study, a new distributed Symbiotic Organism Search (SOS) algorithm has been proposed and tested in the proposed multi-agent framework. The proposed algorithm is termed a multi-agent-based symbiotic organism search algorithm (MASOS). The MASOS has been tested and compared with other proficient algorithms through statistical analysis using benchmark functions. The results show that the proposed MASOS solves the considered benchmark functions efficiently. Then MASOS was tested for DGs coordination considering load variations in the Tanzanian electrical distribution network. The results show that the coordination of DG using the proposed algorithm reduces power loss and improves the voltage profiles of the power system.

Key Questions

What is the purpose of this study?

The study introduces a multi-agent-based Symbiotic Organism Search (MASOS) algorithm for distributed coordination of Distributed Generations (DGs) in electrical distribution networks.

How does the proposed MASOS algorithm improve DG coordination?

MASOS optimizes DG coordination by reducing power losses and improving voltage profiles in distribution systems, particularly under dynamic load variations.

What are the benefits of a multi-agent system (MAS) in this context?

MAS allows for distributed control of DGs, enabling more efficient problem-solving by agents that work cooperatively and independently, optimizing large-scale systems.

How does the proposed algorithm compare to other methods?

MASOS is tested and found to perform efficiently when compared with other algorithms, demonstrating better results in terms of power loss reduction and voltage improvement.

What are the challenges with centralized control in DG coordination?

Centralized control can lead to computational and communication bottlenecks, making it less effective for large-scale, dynamic power distribution systems.

Why is the Symbiotic Organism Search (SOS) algorithm used in this study?

SOS is used for its simplicity, good convergence properties, and ability to perform well on a range of optimization problems in power system coordination.

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ARTICLE USAGE


Article usage: Dec-2024 to May-2025
Show by month Manuscript Video Summary
2025 May 123 123
2025 April 69 69
2025 March 79 79
2025 February 109 109
2025 January 80 80
2024 December 19 19
Total 479 479
Show by month Manuscript Video Summary
2025 May 123 123
2025 April 69 69
2025 March 79 79
2025 February 109 109
2025 January 80 80
2024 December 19 19
Total 479 479
Related Subjects
Physics
Math
Chemistry
Computer science
Engineering
Earth science
Biology
copyright icon

© attribution CC-BY

  • 0

rating
479 Views

Added on

2024-12-25

Doi: https://doi.org/10.1186/s43067-023-00072-7

Related Subjects
Physics
Math
Chemistry
Computer science
Engineering
Earth science
Biology

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