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Optimal Siting and Sizing of Distributed Generators by Strawberry Plant Propagation Algorithm

Author

Listed:
  • Mohsin Shahzad

    (Department of Electrical and Computer Engineering, Abbottabad Campus, COMSATS University Islamabad, Abbottabad 22060, Pakistan
    These authors contributed equally to this work.)

  • Waseem Akram

    (Department of Electrical and Computer Engineering, Abbottabad Campus, COMSATS University Islamabad, Abbottabad 22060, Pakistan
    These authors contributed equally to this work.)

  • Muhammad Arif

    (Department of Electrical and Computer Engineering, Abbottabad Campus, COMSATS University Islamabad, Abbottabad 22060, Pakistan
    These authors contributed equally to this work.)

  • Uzair Khan

    (Department of Electrical and Computer Engineering, Abbottabad Campus, COMSATS University Islamabad, Abbottabad 22060, Pakistan
    These authors contributed equally to this work.)

  • Barkat Ullah

    (Department of Mechanical Engineering, Wah Campus, COMSATS University Islamabad, Wah 47040, Pakistan
    These authors contributed equally to this work.)

Abstract

Increasing the unplanned penetration of Distributed Generators (DGs) has spurred active and reactive power losses in the distribution system. This article suggests using a novel Strawberry Plant Propagation Algorithm (SPPA) for planning the placement of the DGs with the aim of reducing the network (active) power losses and improving the overall voltage profile. The proposed method (SPPA) has been tested on 33 and 69 node radial systems in MATLAB. A cost analysis was also performed and compared with other contemporary methods. The results for the considered variables show the significance of the proposed method in comparison to various other counterparts, including the Mine Blast Algorithm and Particle Swarm Optimization.

Suggested Citation

  • Mohsin Shahzad & Waseem Akram & Muhammad Arif & Uzair Khan & Barkat Ullah, 2021. "Optimal Siting and Sizing of Distributed Generators by Strawberry Plant Propagation Algorithm," Energies, MDPI, vol. 14(6), pages 1-13, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:6:p:1744-:d:521401
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    References listed on IDEAS

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    Cited by:

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    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. Emad M. Ahmed & Rajarajeswari Rathinam & Suchitra Dayalan & George S. Fernandez & Ziad M. Ali & Shady H. E. Abdel Aleem & Ahmed I. Omar, 2021. "A Comprehensive Analysis of Demand Response Pricing Strategies in a Smart Grid Environment Using Particle Swarm Optimization and the Strawberry Optimization Algorithm," Mathematics, MDPI, vol. 9(18), pages 1-24, September.
    7. Adewale Zakariyahu Obaro & Josiah Lange Munda & Adedayo Adedamola YUSUFF, 2023. "Modelling and Energy Management of an Off-Grid Distributed Energy System: A Typical Community Scenario in South Africa," Energies, MDPI, vol. 16(2), pages 1-30, January.
    8. Habib Ur Rehman & Arif Hussain & Waseem Haider & Sayyed Ahmad Ali & Syed Ali Abbas Kazmi & Muhammad Huzaifa, 2023. "Optimal Planning of Solar Photovoltaic (PV) and Wind-Based DGs for Achieving Techno-Economic Objectives across Various Load Models," Energies, MDPI, vol. 16(5), pages 1-38, March.
    9. Dariusz Tarnapowicz & Sergey German-Galkin & Arkadiusz Nerc & Marek Jaskiewicz, 2023. "Improving the Energy Efficiency of a Ship’s Power Plant by Using an Autonomous Hybrid System with a PMSG," Energies, MDPI, vol. 16(7), pages 1-19, March.
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