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Probabilistic Load Flow–Based Optimal Placement and Sizing of Distributed Generators

Author

Listed:
  • Ferdous Al Hossain

    (School of Automation, Hangzhou Dianzi University, Hangzhou 310017, China)

  • Md. Rokonuzzaman

    (Institute of Sustainable Energy (ISE), Universiti Tenaga Nasional (@UNITEN, The National Energy University), Kajang 43000, Selangor, Malaysia
    College of Engineering (COE), Universiti Tenaga Nasional (@UNITEN, The National Energy University), Kajang 43000, Selangor, Malaysia
    School of Engineering and Advance Engineering Platform, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway, Subang Jaya 47500, Selangor, Malaysia)

  • Nowshad Amin

    (Institute of Sustainable Energy (ISE), Universiti Tenaga Nasional (@UNITEN, The National Energy University), Kajang 43000, Selangor, Malaysia
    College of Engineering (COE), Universiti Tenaga Nasional (@UNITEN, The National Energy University), Kajang 43000, Selangor, Malaysia)

  • Jianmin Zhang

    (School of Automation, Hangzhou Dianzi University, Hangzhou 310017, China)

  • Mahmuda Khatun Mishu

    (Institute of Sustainable Energy (ISE), Universiti Tenaga Nasional (@UNITEN, The National Energy University), Kajang 43000, Selangor, Malaysia
    College of Engineering (COE), Universiti Tenaga Nasional (@UNITEN, The National Energy University), Kajang 43000, Selangor, Malaysia)

  • Wen-Shan Tan

    (School of Engineering and Advance Engineering Platform, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway, Subang Jaya 47500, Selangor, Malaysia)

  • Md. Rabiul Islam

    (School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia)

  • Rajib Baran Roy

    (School of Engineering and Technology, Central Queensland University, Bryan Jordan Drive, Gladstone, QLD 4680, Australia)

Abstract

Distributed generation (DG) is gaining importance as electrical energy demand increases. DG is used to decrease power losses, operating costs, and improve voltage stability. Most DG resources have less environmental impact. In a particular region, the sizing and location of DG resources significantly affect the planned DG integrated distribution network (DN). The voltage profiles of the DN will change or even become excessively increased. An enormous DG active power, inserted into an improper node of the distribution network, may bring a larger current greater than the conductor’s maximum value, resulting in an overcurrent distribution network. Therefore, DG sizing and DG location optimization is required for a systematic DG operation to fully exploit distributed energy and achieve mutual energy harmony across existing distribution networks, which creates an economically viable, secure, stable, and dependable power distribution system. DG needs to access the location and capacity for rational planning. The objective function of this paper is to minimize the sum of investment cost, operation cost, and line loss cost utilizing DG access. The probabilistic power flow calculation technique based on the two-point estimation method is chosen for this paper’s load flow computation. The location and size of the DG distribution network are determined using a genetic algorithm in a MATLAB environment. For the optimum solution, the actual power load is estimated using historical data. The proposed system is based on the China distribution system, and the currency is used in Yuan. After DG access, active and reactive power losses are reduced by 53% and 26%, respectively. The line operating cost and the total annual cost are decreased by 53.7% and 12%, respectively.

Suggested Citation

  • Ferdous Al Hossain & Md. Rokonuzzaman & Nowshad Amin & Jianmin Zhang & Mahmuda Khatun Mishu & Wen-Shan Tan & Md. Rabiul Islam & Rajib Baran Roy, 2021. "Probabilistic Load Flow–Based Optimal Placement and Sizing of Distributed Generators," Energies, MDPI, vol. 14(23), pages 1-16, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:23:p:7857-:d:686136
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    References listed on IDEAS

    as
    1. Doagou-Mojarrad, Hasan & Gharehpetian, G.B. & Rastegar, H. & Olamaei, Javad, 2013. "Optimal placement and sizing of DG (distributed generation) units in distribution networks by novel hybrid evolutionary algorithm," Energy, Elsevier, vol. 54(C), pages 129-138.
    2. Shivarama Krishna, K. & Sathish Kumar, K., 2015. "A review on hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 907-916.
    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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