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Salp swarm and gray wolf optimizer for improving the efficiency of power supply network in radial distribution systems

The efficiency of distribution networks is hugely affected by active and reactive power flows in distribution electric power systems. Currently, distributed generators (DGs) of energy are extensively applied to minimize power loss and improve voltage deviancies on power distribution systems. The bes...

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Main Authors: Ihsan Salman, Ihsan Salman, Khalid Mohammed Saffer, Khalid Mohammed Saffer, Hayder H. Saf, Hayder H. Saf, Salama A. Mostafa, Salama A. Mostafa, Bashar Ahmad Khalaf, Bashar Ahmad Khalaf
Format: Article
Language:English
Published: De Gruyter 2023
Subjects:
T Technology (General)
Online Access:http://eprints.uthm.edu.my/10223/1/J15749_6866315792a4b3a48cab143d532100d7.pdf
http://eprints.uthm.edu.my/10223/
https://doi.org/10.1515/jisys-2022-0221
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spelling my.uthm.eprints.102232023-10-18T07:18:56Z http://eprints.uthm.edu.my/10223/ Salp swarm and gray wolf optimizer for improving the efficiency of power supply network in radial distribution systems Ihsan Salman, Ihsan Salman Khalid Mohammed Saffer, Khalid Mohammed Saffer Hayder H. Saf, Hayder H. Saf Salama A. Mostafa, Salama A. Mostafa Bashar Ahmad Khalaf, Bashar Ahmad Khalaf T Technology (General) The efficiency of distribution networks is hugely affected by active and reactive power flows in distribution electric power systems. Currently, distributed generators (DGs) of energy are extensively applied to minimize power loss and improve voltage deviancies on power distribution systems. The best position and volume of DGs produce better power outcomes. This work prepares a new hybrid SSA–GWO metaheuristic optimization algorithm that combines the salp swarm algorithm (SSA) and the gray wolf optimizer (GWO) algorithm. The SSA–GWO algorithm ensures generating the best size and site of one and multi-DGs on the radial distribution network to decrease real power losses (RPL) (kW) on lines and resolve voltage deviancies. Our novel algorithm is executed on IEEE 123-bus radial distribution test systems. The results confirm the success of the suggested hybrid SSA–GWO algorithm compared with implementing the SSA and GWO individually. Through the proposed SSA–GWO algorithm, the study decreases the RPL and improves the voltage profile on distribution networks with multiple DGs units. De Gruyter 2023 Article PeerReviewed text en http://eprints.uthm.edu.my/10223/1/J15749_6866315792a4b3a48cab143d532100d7.pdf Ihsan Salman, Ihsan Salman and Khalid Mohammed Saffer, Khalid Mohammed Saffer and Hayder H. Saf, Hayder H. Saf and Salama A. Mostafa, Salama A. Mostafa and Bashar Ahmad Khalaf, Bashar Ahmad Khalaf (2023) Salp swarm and gray wolf optimizer for improving the efficiency of power supply network in radial distribution systems. Journal of Intelligent Systems. pp. 1-12. https://doi.org/10.1515/jisys-2022-0221
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Ihsan Salman, Ihsan Salman
Khalid Mohammed Saffer, Khalid Mohammed Saffer
Hayder H. Saf, Hayder H. Saf
Salama A. Mostafa, Salama A. Mostafa
Bashar Ahmad Khalaf, Bashar Ahmad Khalaf
Salp swarm and gray wolf optimizer for improving the efficiency of power supply network in radial distribution systems
description The efficiency of distribution networks is hugely affected by active and reactive power flows in distribution electric power systems. Currently, distributed generators (DGs) of energy are extensively applied to minimize power loss and improve voltage deviancies on power distribution systems. The best position and volume of DGs produce better power outcomes. This work prepares a new hybrid SSA–GWO metaheuristic optimization algorithm that combines the salp swarm algorithm (SSA) and the gray wolf optimizer (GWO) algorithm. The SSA–GWO algorithm ensures generating the best size and site of one and multi-DGs on the radial distribution network to decrease real power losses (RPL) (kW) on lines and resolve voltage deviancies. Our novel algorithm is executed on IEEE 123-bus radial distribution test systems. The results confirm the success of the suggested hybrid SSA–GWO algorithm compared with implementing the SSA and GWO individually. Through the proposed SSA–GWO algorithm, the study decreases the RPL and improves the voltage profile on distribution networks with multiple DGs units.
format Article
author Ihsan Salman, Ihsan Salman
Khalid Mohammed Saffer, Khalid Mohammed Saffer
Hayder H. Saf, Hayder H. Saf
Salama A. Mostafa, Salama A. Mostafa
Bashar Ahmad Khalaf, Bashar Ahmad Khalaf
author_facet Ihsan Salman, Ihsan Salman
Khalid Mohammed Saffer, Khalid Mohammed Saffer
Hayder H. Saf, Hayder H. Saf
Salama A. Mostafa, Salama A. Mostafa
Bashar Ahmad Khalaf, Bashar Ahmad Khalaf
author_sort Ihsan Salman, Ihsan Salman
title Salp swarm and gray wolf optimizer for improving the efficiency of power supply network in radial distribution systems
title_short Salp swarm and gray wolf optimizer for improving the efficiency of power supply network in radial distribution systems
title_full Salp swarm and gray wolf optimizer for improving the efficiency of power supply network in radial distribution systems
title_fullStr Salp swarm and gray wolf optimizer for improving the efficiency of power supply network in radial distribution systems
title_full_unstemmed Salp swarm and gray wolf optimizer for improving the efficiency of power supply network in radial distribution systems
title_sort salp swarm and gray wolf optimizer for improving the efficiency of power supply network in radial distribution systems
publisher De Gruyter
publishDate 2023
url http://eprints.uthm.edu.my/10223/1/J15749_6866315792a4b3a48cab143d532100d7.pdf
http://eprints.uthm.edu.my/10223/
https://doi.org/10.1515/jisys-2022-0221
_version_ 1781707451967471616
score 13.211869

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