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Optimal Power Flow in Islanded Microgrids Using a Simple Distributed Algorithm

Author

Listed:
  • Eleonora Riva Sanseverino

    (Department of Energy, Information Engineering and Mathematical Models (DEIM), University of Palermo, Viale delle Scienze, Edificio 9, Palermo 90128, Italy
    These authors contributed equally to this work.)

  • Maria Luisa Di Silvestre

    (Department of Energy, Information Engineering and Mathematical Models (DEIM), University of Palermo, Viale delle Scienze, Edificio 9, Palermo 90128, Italy
    These authors contributed equally to this work.)

  • Romina Badalamenti

    (Department of Energy, Information Engineering and Mathematical Models (DEIM), University of Palermo, Viale delle Scienze, Edificio 9, Palermo 90128, Italy
    These authors contributed equally to this work.)

  • Ninh Quang Nguyen

    (Department of Energy, Information Engineering and Mathematical Models (DEIM), University of Palermo, Viale delle Scienze, Edificio 9, Palermo 90128, Italy
    These authors contributed equally to this work.)

  • Josep Maria Guerrero

    (Department of Energy Technology, Aalborg University, Pontoppi-danstræde, Aalborg 9220, Denmark
    These authors contributed equally to this work.)

  • Lexuan Meng

    (Department of Energy Technology, Aalborg University, Pontoppi-danstræde, Aalborg 9220, Denmark
    These authors contributed equally to this work.)

Abstract

In this paper, the problem of distributed power losses minimization in islanded distribution systems is dealt with. The problem is formulated in a very simple manner and a solution is reached after a few iterations. The considered distribution system, a microgrid, will not need large bandwidth communication channels, since only closeby nodes will exchange information. The correction of generated active powers is possible by means of the active power losses partition concept that attributes a portion of the overall power losses in each branch to each generator. The experimental part shows the first results of the proposed method on an islanded microgrid. Simulation results of the distributed algorithm are compared to a centralized Optimal Power Flow approach and very small errors can be observed.

Suggested Citation

  • Eleonora Riva Sanseverino & Maria Luisa Di Silvestre & Romina Badalamenti & Ninh Quang Nguyen & Josep Maria Guerrero & Lexuan Meng, 2015. "Optimal Power Flow in Islanded Microgrids Using a Simple Distributed Algorithm," Energies, MDPI, vol. 8(10), pages 1-22, October.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:10:p:11493-11514:d:57145
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    References listed on IDEAS

    as
    1. Sanseverino, Eleonora Riva & Di Silvestre, Maria Luisa & Ippolito, Mariano Giuseppe & De Paola, Alessandra & Lo Re, Giuseppe, 2011. "An execution, monitoring and replanning approach for optimal energy management in microgrids," Energy, Elsevier, vol. 36(5), pages 3429-3436.
    2. Eleonora Riva Sanseverino & Maria Luisa Di Silvestre & Gaetano Zizzo & Roberto Gallea & Ninh Nguyen Quang, 2013. "A Self-Adapting Approach for Forecast-Less Scheduling of Electrical Energy Storage Systems in a Liberalized Energy Market," Energies, MDPI, vol. 6(11), pages 1-22, November.
    3. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
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    Cited by:

    1. M. Rambabu & G. V. Nagesh Kumar & S. Sivanagaraju, 2019. "Optimal Power Flow of Integrated Renewable Energy System using a Thyristor Controlled SeriesCompensator and a Grey-Wolf Algorithm," Energies, MDPI, vol. 12(11), pages 1-18, June.
    2. Abdullah Khan & Hashim Hizam & Noor Izzri bin Abdul Wahab & Mohammad Lutfi Othman, 2020. "Optimal power flow using hybrid firefly and particle swarm optimization algorithm," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-21, August.
    3. Warid Warid & Hashim Hizam & Norman Mariun & Noor Izzri Abdul-Wahab, 2016. "Optimal Power Flow Using the Jaya Algorithm," Energies, MDPI, vol. 9(9), pages 1-18, August.
    4. Igyso Zafeiratou & Ionela Prodan & Laurent Lefévre, 2021. "A Hierarchical Control Approach for Power Loss Minimization and Optimal Power Flow within a Meshed DC Microgrid," Energies, MDPI, vol. 14(16), pages 1-27, August.
    5. Yongming Zhang & Zhe Yan & Feng Yuan & Jiawei Yao & Bao Ding, 2018. "A Novel Reconstruction Approach to Elevator Energy Conservation Based on a DC Micro-Grid in High-Rise Buildings," Energies, MDPI, vol. 12(1), pages 1-17, December.
    6. Sowmmiya, U. & Uma, G., 2017. "Effective performance and power transfer operation of a current controlled WRIG based WES in a hybrid grid," Renewable Energy, Elsevier, vol. 101(C), pages 1052-1066.
    7. Hatem Diab & Mahmoud Abdelsalam & Alaa Abdelbary, 2021. "A Multi-Objective Optimal Power Flow Control of Electrical Transmission Networks Using Intelligent Meta-Heuristic Optimization Techniques," Sustainability, MDPI, vol. 13(9), pages 1-25, April.
    8. Abdi, Hamdi & Beigvand, Soheil Derafshi & Scala, Massimo La, 2017. "A review of optimal power flow studies applied to smart grids and microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 742-766.
    9. Gonggui Chen & Zhengmei Lu & Zhizhong Zhang, 2018. "Improved Krill Herd Algorithm with Novel Constraint Handling Method for Solving Optimal Power Flow Problems," Energies, MDPI, vol. 11(1), pages 1-27, January.

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