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Single and multi-objectives based on an improved golden jackal optimization algorithm for simultaneous integration of multiple capacitors and multi-type DGs in distribution systems

Author

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  • Elseify, Mohamed A.
  • Hashim, Fatma A.
  • Hussien, Abdelazim G.
  • Kamel, Salah

Abstract

This paper proposes a novel placement technique based on the improved golden jackal optimization (IGJO) algorithm for multiple capacitor banks (CBs) and multi-type DGs in a distribution network considering single and multi-objective problems. The proposed algorithm incorporates memory-based equations and random walk strategy to enhance the performance of the recent golden jackal optimization in terms of accuracy and convergence speed. The optimization problem is formulated as a weighted multi-objective that seeks to enhance the voltage profiles, boost stability, and minimize the total active power loss. An index named reactive loss sensitivity (QLSI) is also employed with the developed IGJO to identify the candidate nodes for the DGs and CBs installation to reduce the search space of the optimization algorithm. The robustness of the developed IGJO algorithm is evaluated through the CEC 2020 benchmark functions, and a comparison study is conducted with the original GJO and the other nine fresh competitors using various statistical tests to confirm its dominance and superiority. Then, the proposed IGJO is implemented in single and multi-objectives for the optimal deployment of multiple CBs individually and simultaneously with multiple DGs with different operating modes to enhance the performance of the IEEE 69-bus radial distribution system (RDS). The fetched outcomes are compared with the original GJO, weevil optimizer algorithm (WeevilOA), skill optimization algorithm (SOA), and Tasmanian devil optimization (TDO) to further measure its efficacy using different statistical tests. The IGJO algorithm is also applied to deploy multiple DGs for the IEEE 118-bus RDS with the aim of minimizing active loss. The simulation findings affirmed that the proposed IGJO technique beats the other rivals in all investigated situations, qualifying for the optimal inclusion of DGs in the presence of generation and demand uncertainties. Specifically, the integration of three units of CBs synchronously with three DGs Type-I and DG Type-III reduces the active power loss to 4.2664 kW and 3.4178 kW, respectively. The lowest power loss, approximately 2.7989 kW, is achieved with the simultaneous integration of three DG Type-I and DG Type-III using the developed IGJO algorithm.

Suggested Citation

  • Elseify, Mohamed A. & Hashim, Fatma A. & Hussien, Abdelazim G. & Kamel, Salah, 2024. "Single and multi-objectives based on an improved golden jackal optimization algorithm for simultaneous integration of multiple capacitors and multi-type DGs in distribution systems," Applied Energy, Elsevier, vol. 353(PA).
    • Handle: RePEc:eee:appene:v:353:y:2024:i:pa:s0306261923014186
    DOI: 10.1016/j.apenergy.2023.122054
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    References listed on IDEAS

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    1. Ayman Awad & Hussein Abdel-Mawgoud & Salah Kamel & Abdalla A. Ibrahim & Francisco Jurado, 2021. "Developing a Hybrid Optimization Algorithm for Optimal Allocation of Renewable DGs in Distribution Network," Clean Technol., MDPI, vol. 3(2), pages 1-15, May.
    2. Mohammed Hamouda Ali & Ahmed Tijani Salawudeen & Salah Kamel & Habeeb Bello Salau & Monier Habil & Mokhtar Shouran, 2022. "Single- and Multi-Objective Modified Aquila Optimizer for Optimal Multiple Renewable Energy Resources in Distribution Network," Mathematics, MDPI, vol. 10(12), pages 1-39, June.
    3. Chandrasekaran Venkatesan & Raju Kannadasan & Mohammed H. Alsharif & Mun-Kyeom Kim & Jamel Nebhen, 2021. "A Novel Multiobjective Hybrid Technique for Siting and Sizing of Distributed Generation and Capacitor Banks in Radial Distribution Systems," Sustainability, MDPI, vol. 13(6), pages 1-34, March.
    4. Mohamed A. Elseify & Salah Kamel & Hussein Abdel-Mawgoud & Ehab E. Elattar, 2022. "A Novel Approach Based on Honey Badger Algorithm for Optimal Allocation of Multiple DG and Capacitor in Radial Distribution Networks Considering Power Loss Sensitivity," Mathematics, MDPI, vol. 10(12), pages 1-26, June.
    5. Zeeshan Memon Anjum & Dalila Mat Said & Mohammad Yusri Hassan & Zohaib Hussain Leghari & Gul Sahar, 2022. "Parallel operated hybrid Arithmetic-Salp swarm optimizer for optimal allocation of multiple distributed generation units in distribution networks," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-38, April.
    6. Hassan Haes Alhelou & Mohamad Esmail Hamedani-Golshan & Takawira Cuthbert Njenda & Pierluigi Siano, 2019. "A Survey on Power System Blackout and Cascading Events: Research Motivations and Challenges," Energies, MDPI, vol. 12(4), pages 1-28, February.
    7. Ali Selim & Salah Kamel & Amal A. Mohamed & Ehab E. Elattar, 2021. "Optimal Allocation of Multiple Types of Distributed Generations in Radial Distribution Systems Using a Hybrid Technique," Sustainability, MDPI, vol. 13(12), pages 1-31, June.
    8. Thuan Thanh Nguyen & Thanh-Quyen Ngo & Thanh Long Duong & Thang Trung Nguyen & Alex Alexandridis, 2021. "Finding Radial Network Configuration of Distribution System Based on Modified Symbiotic Organisms Search," Complexity, Hindawi, vol. 2021, pages 1-23, February.
    9. Akanit Kwangkaew & Saher Javaid & Chalie Charoenlarpnopparut & Mineo Kaneko, 2022. "Optimal Location and Sizing of Renewable Distributed Generators for Improving Voltage Stability and Security Considering Reactive Power Compensation," Energies, MDPI, vol. 15(6), pages 1-23, March.
    10. Subrat Kumar Dash & Sivkumar Mishra & Almoataz Y. Abdelaziz & Mamdouh L. Alghaythi & Ahmed Allehyani, 2022. "Optimal Allocation of Distributed Generators in Active Distribution Networks Using a New Oppositional Hybrid Sine Cosine Muted Differential Evolution Algorithm," Energies, MDPI, vol. 15(6), pages 1-35, March.
    11. Fathy, Ahmed, 2022. "A novel artificial hummingbird algorithm for integrating renewable based biomass distributed generators in radial distribution systems," Applied Energy, Elsevier, vol. 323(C).
    12. Abdurrahman Shuaibu Hassan & Yanxia Sun & Zenghui Wang, 2022. "Water, Energy and Food Algorithm with Optimal Allocation and Sizing of Renewable Distributed Generation for Power Loss Minimization in Distribution Systems (WEF)," Energies, MDPI, vol. 15(6), pages 1-19, March.
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