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

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.

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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.

Item Type: Article
Uncontrolled Keywords: distributed generators, radial distribution systems, real power losses, gray wolf optimizer, metaheuristic optimization, salp swarm algorithm, IEEE standard case
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Depositing User: Mr. Mohamad Zulkhibri Rahmad
Date Deposited: 13 Sep 2023 03:52
Last Modified: 13 Sep 2023 03:52

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