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Implementation of a Real-Time Microgrid Simulation Platform Based on Centralized and Distributed Management

Author

Listed:
  • Omid Abrishambaf

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, Porto 4200-072, Portugal)

  • Pedro Faria

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, Porto 4200-072, Portugal)

  • Luis Gomes

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, Porto 4200-072, Portugal)

  • João Spínola

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, Porto 4200-072, Portugal)

  • Zita Vale

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, Porto 4200-072, Portugal)

  • Juan M. Corchado

    (BISITE—Bioinformatics, Intelligent Systems and Educational Technology Research Center, University of Salamanca, Salamanca 37008, Spain)

Abstract

Demand response and distributed generation are key components of power systems. Several challenges are raised at both technical and business model levels for integration of those resources in smart grids and microgrids. The implementation of a distribution network as a test bed can be difficult and not cost-effective; using computational modeling is not sufficient for producing realistic results. Real-time simulation allows us to validate the business model’s impact at the technical level. This paper comprises a platform supporting the real-time simulation of a microgrid connected to a larger distribution network. The implemented platform allows us to use both centralized and distributed energy resource management. Using an optimization model for the energy resource operation, a virtual power player manages all the available resources. Then, the simulation platform allows us to technically validate the actual implementation of the requested demand reduction in the scope of demand response programs. The case study has 33 buses, 220 consumers, and 68 distributed generators. It demonstrates the impact of demand response events, also performing resource management in the presence of an energy shortage.

Suggested Citation

  • Omid Abrishambaf & Pedro Faria & Luis Gomes & João Spínola & Zita Vale & Juan M. Corchado, 2017. "Implementation of a Real-Time Microgrid Simulation Platform Based on Centralized and Distributed Management," Energies, MDPI, vol. 10(6), pages 1-14, June.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:6:p:806-:d:101424
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    References listed on IDEAS

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    1. Ahmadali Khatibzadeh & Mohammadreza Besmi & Aminollah Mahabadi & Mahmoud Reza Haghifam, 2017. "Multi-Agent-Based Controller for Voltage Enhancement in AC/DC Hybrid Microgrid Using Energy Storages," Energies, MDPI, vol. 10(2), pages 1-17, February.
    2. Pedro Faria & Zita Vale & José Baptista, 2015. "Demand Response Programs Design and Use Considering Intensive Penetration of Distributed Generation," Energies, MDPI, vol. 8(6), pages 1-17, June.
    3. Faria, P. & Vale, Z., 2011. "Demand response in electrical energy supply: An optimal real time pricing approach," Energy, Elsevier, vol. 36(8), pages 5374-5384.
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    Cited by:

    1. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu & Liu, Junyao, 2023. "A review on integration of surging plug-in electric vehicles charging in energy-flexible buildings: Impacts analysis, collaborative management technologies, and future perspective," Applied Energy, Elsevier, vol. 331(C).
    2. Pedro Faria & Zita Vale, 2022. "Realistic Load Modeling for Efficient Consumption Management Using Real-Time Simulation and Power Hardware-in-the-Loop," Energies, MDPI, vol. 16(1), pages 1-15, December.
    3. Omid Abrishambaf & Pedro Faria & Zita Vale & Juan M. Corchado, 2019. "Energy Scheduling Using Decision Trees and Emulation: Agriculture Irrigation with Run-of-the-River Hydroelectricity and a PV Case Study," Energies, MDPI, vol. 12(20), pages 1-21, October.
    4. Omid Abrishambaf & Pedro Faria & Zita Vale, 2020. "Ramping of Demand Response Event with Deploying Distinct Programs by an Aggregator," Energies, MDPI, vol. 13(6), pages 1-18, March.
    5. Igual, R. & Medrano, C., 2020. "Research challenges in real-time classification of power quality disturbances applicable to microgrids: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    6. Pedro Faria, 2019. "Distributed Energy Resources Management," Energies, MDPI, vol. 12(3), pages 1-3, February.
    7. Muhammad Babar & Jakub Grela & Andrzej Ożadowicz & Phuong H. Nguyen & Zbigniew Hanzelka & I. G. Kamphuis, 2018. "Energy Flexometer: Transactive Energy-Based Internet of Things Technology," Energies, MDPI, vol. 11(3), pages 1-20, March.
    8. Zita Vale & Pedro Faria & Omid Abrishambaf & Luis Gomes & Tiago Pinto, 2021. "MARTINE—A Platform for Real-Time Energy Management in Smart Grids," Energies, MDPI, vol. 14(7), pages 1-18, March.
    9. Younes Zahraoui & Ibrahim Alhamrouni & Saad Mekhilef & M. Reyasudin Basir Khan & Mehdi Seyedmahmoudian & Alex Stojcevski & Ben Horan, 2021. "Energy Management System in Microgrids: A Comprehensive Review," Sustainability, MDPI, vol. 13(19), pages 1-33, September.
    10. Andrzej Ożadowicz, 2017. "A New Concept of Active Demand Side Management for Energy Efficient Prosumer Microgrids with Smart Building Technologies," Energies, MDPI, vol. 10(11), pages 1-22, November.
    11. Ibrahim Ahmad & Ghaeth Fandi & Zdenek Muller & Josef Tlusty, 2019. "Voltage Quality and Power Factor Improvement in Smart Grids Using Controlled DG Units," Energies, MDPI, vol. 12(18), pages 1-18, September.
    12. Giuseppe Barone & Giovanni Brusco & Alessandro Burgio & Daniele Menniti & Anna Pinnarelli & Michele Motta & Nicola Sorrentino & Pasquale Vizza, 2018. "A Real-Life Application of a Smart User Network," Energies, MDPI, vol. 11(12), pages 1-23, December.

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