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A Gradient-Based Optimizer with a Crossover Operator for Distribution Static VAR Compensator (D-SVC) Sizing and Placement in Electrical Systems

Author

Listed:
  • Ghareeb Moustafa

    (Electrical Engineering Department, Jazan University, Jazan 45142, Saudi Arabia
    Electrical Engineering Department, Suez Canal University, Ismailia 41522, Egypt)

  • Mostafa Elshahed

    (Electrical Engineering Department, Engineering and Information Technology College, Buraydah Private Colleges, Buraydah 51418, Saudi Arabia
    Electrical Power Engineering Department, Faculty of Engineering, Cairo University, Giza 12613, Egypt)

  • Ahmed R. Ginidi

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

  • Abdullah M. Shaheen

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

  • Hany S. E. Mansour

    (Electrical Engineering Department, Suez Canal University, Ismailia 41522, Egypt)

Abstract

A gradient-based optimizer (GBO) is a recently inspired meta-heuristic technique centered on Newton’s gradient-based approach. In this paper, an advanced developed version of the GBO is merged with a crossover operator (GBOC) to enhance the diversity of the created solutions. The merged crossover operator causes the solutions in the next generation to be more random. The proposed GBOC maintains the original Gradient Search Rule (GSR) and Local Escaping Operator (LEO). The GSR directs the search to potential areas and aids in its convergence to the optimal answer, while the LEO aids the searching process in avoiding local optima. The proposed GBOC technique is employed to optimally place and size the distribution static VAR compensator (D-SVC), one of the distribution flexible AC transmission devices (D-FACTS). It is developed to maximize the yearly energy savings via power losses concerning simultaneously different levels of the peak, average, and light loadings. Its relevance is tested on three distribution systems of IEEE 33, 69, and 118 nodes. Based on the proposed GBOC, the outputs of the D-SVCs are optimally varying with the loading level. Furthermore, their installed ratings are handled as an additional constraint relating to two compensation levels of 50% and 75% of the total reactive power load to reflect a financial installation limit. The simulation applications of the proposed GBOC declare great economic savings in yearly energy losses for the three distribution systems with increasing compensation levels and iterations compared to the initial case. In addition, the effectiveness of the proposed GBOC is demonstrated compared to several techniques, such as the original GBO, the salp swarm algorithm, the dwarf mongoose algorithm, differential evolution, and honey badger optimization.

Suggested Citation

  • Ghareeb Moustafa & Mostafa Elshahed & Ahmed R. Ginidi & Abdullah M. Shaheen & Hany S. E. Mansour, 2023. "A Gradient-Based Optimizer with a Crossover Operator for Distribution Static VAR Compensator (D-SVC) Sizing and Placement in Electrical Systems," Mathematics, MDPI, vol. 11(5), pages 1-30, February.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:5:p:1077-:d:1075832
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    References listed on IDEAS

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    1. Hashim, Fatma A. & Houssein, Essam H. & Hussain, Kashif & Mabrouk, Mai S. & Al-Atabany, Walid, 2022. "Honey Badger Algorithm: New metaheuristic algorithm for solving optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 192(C), pages 84-110.
    2. Gasperic, Samo & Mihalic, Rafael, 2019. "Estimation of the efficiency of FACTS devices for voltage-stability enhancement with PV area criteria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 144-156.
    3. Luis Fernando Grisales-Noreña & Oscar Danilo Montoya & Jesús C. Hernández & Carlos Andres Ramos-Paja & Alberto-Jesus Perea-Moreno, 2022. "A Discrete-Continuous PSO for the Optimal Integration of D-STATCOMs into Electrical Distribution Systems by Considering Annual Power Loss and Investment Costs," Mathematics, MDPI, vol. 10(14), pages 1-16, July.
    4. Amal Amin Mohamed & Salah Kamel & Mohamed H. Hassan & Mohamed I. Mosaad & Mansour Aljohani, 2022. "Optimal Power Flow Analysis Based on Hybrid Gradient-Based Optimizer with Moth–Flame Optimization Algorithm Considering Optimal Placement and Sizing of FACTS/Wind Power," Mathematics, MDPI, vol. 10(3), pages 1-31, January.
    5. Martin Ćalasan & Tatjana Konjić & Katarina Kecojević & Lazar Nikitović, 2020. "Optimal Allocation of Static Var Compensators in Electric Power Systems," Energies, MDPI, vol. 13(12), pages 1-24, June.
    6. Mostafa Elshahed & Mohamed A. Tolba & Ali M. El-Rifaie & Ahmed Ginidi & Abdullah Shaheen & Shazly A. Mohamed, 2023. "An Artificial Rabbits’ Optimization to Allocate PVSTATCOM for Ancillary Service Provision in Distribution Systems," Mathematics, MDPI, vol. 11(2), pages 1-19, January.
    7. Hana Merah & Abdelmalek Gacem & Djilani Ben Attous & Abderezak Lashab & Francisco Jurado & Mariam A. Sameh, 2022. "Sizing and Sitting of Static VAR Compensator (SVC) Using Hybrid Optimization of Combined Cuckoo Search (CS) and Antlion Optimization (ALO) Algorithms," Energies, MDPI, vol. 15(13), pages 1-20, July.
    8. Savić, Aleksandar & Đurišić, Željko, 2014. "Optimal sizing and location of SVC devices for improvement of voltage profile in distribution network with dispersed photovoltaic and wind power plants," Applied Energy, Elsevier, vol. 134(C), pages 114-124.
    9. Oscar Danilo Montoya & Luis Fernando Grisales-Noreña & Diego Armando Giral-Ramírez, 2022. "Optimal Placement and Sizing of PV Sources in Distribution Grids Using a Modified Gradient-Based Metaheuristic Optimizer," Sustainability, MDPI, vol. 14(6), pages 1-19, March.
    10. Xu, Xu & Li, Jiayong & Xu, Zhao & Zhao, Jian & Lai, Chun Sing, 2019. "Enhancing photovoltaic hosting capacity—A stochastic approach to optimal planning of static var compensator devices in distribution networks," Applied Energy, Elsevier, vol. 238(C), pages 952-962.
    11. Abdullah Shaheen & Ragab El-Sehiemy & Salah Kamel & Ali Selim, 2022. "Optimal Operational Reliability and Reconfiguration of Electrical Distribution Network Based on Jellyfish Search Algorithm," Energies, MDPI, vol. 15(19), pages 1-14, September.
    12. Rezk, Hegazy & Ferahtia, Seydali & Djeroui, Ali & Chouder, Aissa & Houari, Azeddine & Machmoum, Mohamed & Abdelkareem, Mohammad Ali, 2022. "Optimal parameter estimation strategy of PEM fuel cell using gradient-based optimizer," Energy, Elsevier, vol. 239(PC).
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