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Optimizing Operation Indices Considering Different Types of Distributed Generation in Microgrid Applications

Author

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  • Niloofar Ghanbari

    (Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27695, USA)

  • Hossein Mokhtari

    (Department of Electrical Engineering, Sharif University of Technology, P.O. Box 11365-11155 Tehran, Iran)

  • Subhashish Bhattacharya

    (Department of Electrical Engineering, Sharif University of Technology, P.O. Box 11365-11155 Tehran, Iran)

Abstract

The need for independent power generation has increased in recent years, especially with the growing demand in microgrid systems. In a microgrid with several generations of different types and with all kinds of loads of variable nature, an optimal power balance in the system has to be achieved. This optimal objective, which results in minimal energy losses over a specific period of time, requires an optimal location and sizing of the distributed generations (DGs) in a microgrid. This paper proposes a new optimization method in which both optimal location of the DGs and their generation profile according to the load demand profile as well as the type of DG are determined during the life time of the DGs. The types of DGs that are considered in this paper are diesel generators and wind turbine. The method is based on simultaneously minimizing the cost of the investment and operation of the DGs, the cost of power delivered by the the external grid as well as the cost of power losses in the network. The proposed method is tested on the IEEE standard radial distribution network considering time-varying loads and the wind speed every hour of a day.

Suggested Citation

  • Niloofar Ghanbari & Hossein Mokhtari & Subhashish Bhattacharya, 2018. "Optimizing Operation Indices Considering Different Types of Distributed Generation in Microgrid Applications," Energies, MDPI, vol. 11(4), pages 1-12, April.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:894-:d:140587
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    References listed on IDEAS

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    1. Soares, João & Fotouhi Ghazvini, Mohammad Ali & Vale, Zita & de Moura Oliveira, P.B., 2016. "A multi-objective model for the day-ahead energy resource scheduling of a smart grid with high penetration of sensitive loads," Applied Energy, Elsevier, vol. 162(C), pages 1074-1088.
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    Cited by:

    1. Ghaeth Fandi & Ibrahim Ahmad & Famous O. Igbinovia & Zdenek Muller & Josef Tlusty & Vladimir Krepl, 2018. "Voltage Regulation and Power Loss Minimization in Radial Distribution Systems via Reactive Power Injection and Distributed Generation Unit Placement," Energies, MDPI, vol. 11(6), pages 1-17, May.
    2. Dolatiary, Soheil & Rahmani, Javad & Khalilzad, Zahra, 2018. "Optimum location of DG units considering operation conditions," MPRA Paper 94194, University Library of Munich, Germany, revised 2018.
    3. Farzaneh Pourahmadi & Payman Dehghanian, 2018. "A Game-Theoretic Loss Allocation Approach in Power Distribution Systems with High Penetration of Distributed Generations," Mathematics, MDPI, vol. 6(9), pages 1-14, September.
    4. Rahmani, Fatemeh, 2018. "Electric Vehicle Charger Based on DC/DC Converter Topology," MPRA Paper 108310, University Library of Munich, Germany, revised 01 Jul 2018.
    5. Kaitlyn J. Bunker & Wayne W. Weaver, 2018. "Optimal Multidimensional Droop Control for Wind Resources in DC Microgrids," Energies, MDPI, vol. 11(7), pages 1-20, July.
    6. Fatemeh Ghalavand & Behzad Asle Mohammadi Alizade & Hossam Gaber & Hadis Karimipour, 2018. "Microgrid Islanding Detection Based on Mathematical Morphology," Energies, MDPI, vol. 11(10), pages 1-18, October.

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