LAPSE:2023.9095
Published Article

LAPSE:2023.9095
Optimal Operational Reliability and Reconfiguration of Electrical Distribution Network Based on Jellyfish Search Algorithm
February 27, 2023
Abstract
In this paper, the electricity network automation based on Power Network Reconfiguration (PNR) is implemented to improve the operational reliability of distribution systems using jellyfish search algorithm. For this purpose, system average interruption frequency index (SAIFI), system average interruption unavailability index (SAIUI) and total energy not supplied (TENS) are critical measures. In this paper, a new optimization technique of jellyfish search (JFS) algorithm is employed for distribution network reconfiguration for reliability improvement. It is concerned with the moving patterns of jellyfish. They are divided into three categories. The jellyfish could flow towards the ocean current or between its own swarm. Meanwhile, whenever the food supply is adequate, the jellyfishes are attracted to its location. It is formulated considering the three reliability indices of SAIFI, SAIUI and TENS, simultaneously in a multi-objective model based on the weight factors. The proposed methodology based on the JFS optimizer is implemented on an IEEE 33-node distribution network. According to the numerical results, the SAIFI, SAIUI and TENS is improved by 36.44%, 34.11% and 33.35%, compared to the initial condition. For comparison purposes, tuna swarm optimizer and tunicate swarm algorithm, besides the JFS algorithm, are implemented as well. The simulation results declare the significant outperformance of the JFS algorithm compared to TUNA and TSA in terms of the obtained improvements and the regarding convergence properties.
In this paper, the electricity network automation based on Power Network Reconfiguration (PNR) is implemented to improve the operational reliability of distribution systems using jellyfish search algorithm. For this purpose, system average interruption frequency index (SAIFI), system average interruption unavailability index (SAIUI) and total energy not supplied (TENS) are critical measures. In this paper, a new optimization technique of jellyfish search (JFS) algorithm is employed for distribution network reconfiguration for reliability improvement. It is concerned with the moving patterns of jellyfish. They are divided into three categories. The jellyfish could flow towards the ocean current or between its own swarm. Meanwhile, whenever the food supply is adequate, the jellyfishes are attracted to its location. It is formulated considering the three reliability indices of SAIFI, SAIUI and TENS, simultaneously in a multi-objective model based on the weight factors. The proposed methodology based on the JFS optimizer is implemented on an IEEE 33-node distribution network. According to the numerical results, the SAIFI, SAIUI and TENS is improved by 36.44%, 34.11% and 33.35%, compared to the initial condition. For comparison purposes, tuna swarm optimizer and tunicate swarm algorithm, besides the JFS algorithm, are implemented as well. The simulation results declare the significant outperformance of the JFS algorithm compared to TUNA and TSA in terms of the obtained improvements and the regarding convergence properties.
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Keywords
distribution systems, jellyfish search algorithm, network reconfiguration, operational reliability
Subject
Suggested Citation
Shaheen A, El-Sehiemy R, Kamel S, Selim A. Optimal Operational Reliability and Reconfiguration of Electrical Distribution Network Based on Jellyfish Search Algorithm. (2023). LAPSE:2023.9095
Author Affiliations
Shaheen A: Department of Electrical Engineering, Faculty of Engineering, Suez University, Suez 43533, Egypt [ORCID]
El-Sehiemy R: Department of Electrical Engineering, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh 33516, Egypt [ORCID]
Kamel S: Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan 81542, Egypt [ORCID]
Selim A: Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan 81542, Egypt [ORCID]
El-Sehiemy R: Department of Electrical Engineering, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh 33516, Egypt [ORCID]
Kamel S: Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan 81542, Egypt [ORCID]
Selim A: Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan 81542, Egypt [ORCID]
Journal Name
Energies
Volume
15
Issue
19
First Page
6994
Year
2022
Publication Date
2022-09-23
ISSN
1996-1073
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Original Submission
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PII: en15196994, Publication Type: Journal Article
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LAPSE:2023.9095
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https://doi.org/10.3390/en15196994
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Feb 27, 2023
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