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Optimal DG Placement in Power Systems Using a Modified Flower Pollination Algorithm

Author

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  • Abinands Ramshanker

    (School of Electrical Engineering, Vellore Institute Technology, Vellore 632014, India)

  • Jacob Raglend Isaac

    (School of Electrical Engineering, Vellore Institute Technology, Vellore 632014, India)

  • Belwin Edward Jeyeraj

    (School of Electrical Engineering, Vellore Institute Technology, Vellore 632014, India)

  • Jose Swaminathan

    (School of Mechanical Engineering, Vellore Institute Technology, Vellore 632014, India)

  • Ravi Kuppan

    (School of Electrical Engineering, Vellore Institute Technology, Vellore 632014, India)

Abstract

There is a huge requirement for power systems to reduce power losses. Adding distributed generators (DGs) is the most common approach to achieving lower power losses. However, several challenges arise, such as determining the ideal size as well as location of the utilized distributed generators. Most of the existing methods do not consider the variety of load types, the variety and size of the utilized DGs besides reducing the convergence time and enhancing the optimization results. The paper performed an optimization algorithm that integrated a golden search-based flower pollination algorithm and fitness-distance balance (FDB) to find out the optimal size as well as the location of the distributed generators. It was then compared with different optimization methods to determine the best optimization technique, and it was determined to be the best technique. In addition, different types of DGs are considered, including solar energy, wind energy, and biogas, along with optimizing the size of the utilized DGs to reduce the system cost. Testing with different types of bus systems, and different types of DGs in a radial distribution system was done to reveal that the modified flower pollination with golden section search was superior in comparison to others with regards to convergence and power loss reduction.

Suggested Citation

  • Abinands Ramshanker & Jacob Raglend Isaac & Belwin Edward Jeyeraj & Jose Swaminathan & Ravi Kuppan, 2022. "Optimal DG Placement in Power Systems Using a Modified Flower Pollination Algorithm," Energies, MDPI, vol. 15(22), pages 1-17, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8516-:d:972586
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    References listed on IDEAS

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    1. Dalia Yousri & Thanikanti Sudhakar Babu & Dalia Allam & Vigna. K. Ramachandaramurthy & Eman Beshr & Magdy. B. Eteiba, 2019. "Fractional Chaos Maps with Flower Pollination Algorithm for Partial Shading Mitigation of Photovoltaic Systems," Energies, MDPI, vol. 12(18), pages 1-27, September.
    2. Haizhu Yang & Xiangyang Liu & Yiming Guo & Peng Zhang, 2020. "Fault Location of Active Distribution Networks Based on the Golden Section Method," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-9, February.
    3. Esmaili, Masoud & Firozjaee, Esmail Chaktan & Shayanfar, Heidar Ali, 2014. "Optimal placement of distributed generations considering voltage stability and power losses with observing voltage-related constraints," Applied Energy, Elsevier, vol. 113(C), pages 1252-1260.
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    1. Ardiaty Arief & Muhammad Bachtiar Nappu, 2023. "Novel Hybrid Modified Modal Analysis and Continuation Power Flow Method for Unity Power Factor DER Placement," Energies, MDPI, vol. 16(4), pages 1-18, February.
    2. 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.

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