IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i7p2452-d780580.html
   My bibliography  Save this article

Optimal Placement of Capacitors in Radial Distribution Grids via Enhanced Modified Particle Swarm Optimization

Author

Listed:
  • Muhammad Junaid Tahir

    (Renewable Energy Research Labortary (RENERAL) Electrical Engineering Section, British Malaysian Institute, Universiti Kuala Lumpur, Gombak 53100, Selangor, Malaysia
    Electrical Technology Section, The University of Lahore, Lahore 53700, Pakistan)

  • Muhammad Babar Rasheed

    (Escuela Politécnica Superior, ISG, Universidad de Alcalá, 28800 Alcalá de Henares, Spain)

  • Mohd Khairil Rahmat

    (Renewable Energy Research Labortary (RENERAL) Electrical Engineering Section, British Malaysian Institute, Universiti Kuala Lumpur, Gombak 53100, Selangor, Malaysia)

Abstract

This paper presents the integration of shunt capacitors in the radial distribution grids (RDG) with constant and time-varying load consideration for the reduction of power losses and total annual cost, which turns to enhance the voltage profile and annual net savings. To gather the stated goals, three objective functions are formulated with system constraints. To solve this identified problem, a novel optimization technique based on the modification of particle swarm optimization is proposed. The solution methodology is divided into two phases. In phase one, potential candidate buses are nominated using the loss sensitivity factor method and in phase two the proposed technique first selects the optimal buses for the capacitor placement among the potential buses then it decides the optimal sizing of the capacitors as well. To demonstrate the performance in terms of efficiency and strength, the proposed technique is tested on IEEE 15, 33, and 69 bus system for the optimal placement and sizing of capacitors (OPSC) problem. The results are achieved in terms of annual net savings for 15 bus (47.66 % c a s e − 1 , 32.76 % c a s e − 2 , 26.46 % c a s e − 3 ) , 33 bus (33.09% c a s e − 1 , 27.06 % c a s e − 2 , 24.15 % c a s e − 3 ), and 69 bus (34.51% c a s e − 1 , 29.43 % c a s e − 2 , 25.83 % c a s e − 3 ) which are comparable to other state of the art methods, and it also indicates the success of the proposed technique.

Suggested Citation

  • Muhammad Junaid Tahir & Muhammad Babar Rasheed & Mohd Khairil Rahmat, 2022. "Optimal Placement of Capacitors in Radial Distribution Grids via Enhanced Modified Particle Swarm Optimization," Energies, MDPI, vol. 15(7), pages 1-27, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2452-:d:780580
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/7/2452/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/7/2452/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Diego José da Silva & Edmarcio Antonio Belati & Eduardo Werley Silva dos Angelos, 2020. "FPAES: A Hybrid Approach for the Optimal Placement and Sizing of Reactive Compensation in Distribution Grids," Energies, MDPI, vol. 13(23), pages 1-18, December.
    2. Chandan Kishore & Smarajit Ghosh & Vinod Karar, 2018. "Symmetric Fuzzy Logic and IBFOA Solutions for Optimal Position and Rating of Capacitors Allocated to Radial Distribution Networks," Energies, MDPI, vol. 11(4), pages 1-14, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chengjun Xia & Xia Hua & Zhen Wang & Zhenlin Huang, 2018. "Analytical Calculation for Multi-Infeed Interaction Factors Considering Control Modes of High Voltage Direct Current Links," Energies, MDPI, vol. 11(6), pages 1-19, June.
    2. Ovidiu Ivanov & Bogdan-Constantin Neagu & Gheorghe Grigoras & Mihai Gavrilas, 2019. "Optimal Capacitor Bank Allocation in Electricity Distribution Networks Using Metaheuristic Algorithms," Energies, MDPI, vol. 12(22), pages 1-36, November.
    3. Kyu-Hyung Jo & Mun-Kyeom Kim, 2018. "Improved Genetic Algorithm-Based Unit Commitment Considering Uncertainty Integration Method," Energies, MDPI, vol. 11(6), pages 1-18, May.
    4. Thuan Thanh Nguyen & Bach Hoang Dinh & Thai Dinh Pham & Thang Trung Nguyen, 2020. "Active Power Loss Reduction for Radial Distribution Systems by Placing Capacitors and PV Systems with Geography Location Constraints," Sustainability, MDPI, vol. 12(18), pages 1-30, September.
    5. Diego Jose da Silva & Edmarcio Antonio Belati & Jesús M. López-Lezama, 2023. "A Mathematical Programming Approach for the Optimal Operation of Storage Systems, Photovoltaic and Wind Power Generation," Energies, MDPI, vol. 16(3), pages 1-24, January.
    6. Cícero Augusto de Souza & Diego Jose da Silva & Priscila Rossoni & Edmarcio Antonio Belati & Ademir Pelizari & Jesús M. López-Lezama & Nicolás Muñoz-Galeano, 2023. "Multi-Period Optimal Power Flow with Photovoltaic Generation Considering Optimized Power Factor Control," Sustainability, MDPI, vol. 15(19), pages 1-20, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2452-:d:780580. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.