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An Augmented Social Network Search Algorithm for Optimal Reactive Power Dispatch Problem

Author

Listed:
  • Shahenda Sarhan

    (Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Abdullah Shaheen

    (Department of Electrical Engineering, Faculty of Engineering, Suez University, Suez 43533, Egypt)

  • Ragab El-Sehiemy

    (Department of Electrical Engineering, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh 33516, Egypt)

  • Mona Gafar

    (Department of Computer Science, College of Science and Humanities in Al-Sulail, Prince Sattam bin Abdulaziz University, Kharj 16273, Saudi Arabia
    Machine Learning and Information Retrieval Department, Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh 33516, Egypt)

Abstract

Optimal Reactive Power Dispatch (ORPD) is one of the main challenges in power system operations. ORPD is a non-linear optimization task that aims to reduce the active power losses in the transmission grid, minimize voltage variations, and improve the system voltage stability. This paper proposes an intelligent augmented social network search (ASNS) algorithm for meeting the previous aims compared with the social network search (SNS) algorithm. The social network users’ dialogue, imitation, creativity, and disputation moods drive the core of the SNS algorithm. The proposed ASNS enhances SNS performance by boosting the search capability surrounding the best possible solution, with the goal of improving its globally searched possibilities while attempting to avoid getting locked in a locally optimal one. The performance of ASNS is evaluated compared with SNS on three IEEE standard grids, IEEE 30-, 57-, and 118-bus test systems, for enhanced results. Diverse comparisons and statistical analyses are applied to validate the performance. Results indicated that ASNS supports the diversity of populations in addition to achieving superiority in reducing power losses up to 22% and improving voltage profiles up to 90.3% for the tested power grids.

Suggested Citation

  • Shahenda Sarhan & Abdullah Shaheen & Ragab El-Sehiemy & Mona Gafar, 2023. "An Augmented Social Network Search Algorithm for Optimal Reactive Power Dispatch Problem," Mathematics, MDPI, vol. 11(5), pages 1-42, March.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:5:p:1236-:d:1087014
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    References listed on IDEAS

    as
    1. Ragab El-Sehiemy & Abdallah Elsayed & Abdullah Shaheen & Ehab Elattar & Ahmed Ginidi, 2021. "Scheduling of Generation Stations, OLTC Substation Transformers and VAR Sources for Sustainable Power System Operation Using SNS Optimizer," Sustainability, MDPI, vol. 13(21), pages 1-24, October.
    2. Zelan Li & Yijia Cao & Le Van Dai & Xiaoliang Yang & Thang Trung Nguyen, 2019. "Finding Solutions for Optimal Reactive Power Dispatch Problem by a Novel Improved Antlion Optimization Algorithm," Energies, MDPI, vol. 12(15), pages 1-31, August.
    3. Mohamed Ebeed & Ayman Alhejji & Salah Kamel & Francisco Jurado, 2020. "Solving the Optimal Reactive Power Dispatch Using Marine Predators Algorithm Considering the Uncertainties in Load and Wind-Solar Generation Systems," Energies, MDPI, vol. 13(17), pages 1-19, August.
    4. Ahmed M. Abd-El Wahab & Salah Kamel & Mohamed H. Hassan & Mohamed I. Mosaad & Tarek A. AbdulFattah, 2022. "Optimal Reactive Power Dispatch Using a Chaotic Turbulent Flow of Water-Based Optimization Algorithm," Mathematics, MDPI, vol. 10(3), pages 1-26, January.
    5. Shaheen, Abdullah M. & El-Sehiemy, Ragab A. & Alharthi, Mosleh M. & Ghoneim, Sherif S.M. & Ginidi, Ahmed R., 2021. "Multi-objective jellyfish search optimizer for efficient power system operation based on multi-dimensional OPF framework," Energy, Elsevier, vol. 237(C).
    6. Abdullah Shaheen & Ahmed Ginidi & Ragab El-Sehiemy & Abdallah Elsayed & Ehab Elattar & Hassen T. Dorrah, 2022. "Developed Gorilla Troops Technique for Optimal Power Flow Problem in Electrical Power Systems," Mathematics, MDPI, vol. 10(10), pages 1-29, May.
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