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Short-Term Operation Scheduling of a Microgrid under Variability Contracts to Preserve Grid Flexibility

Author

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  • Sunwoong Kim

    (Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Korea)

  • Dam Kim

    (Department of Statistics, Institute of Engineering Research, Seoul National University, Seoul 08826, Korea)

  • Yong Tae Yoon

    (Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Korea)

Abstract

The conventional microgrid (MG) price-based operation scheme with respect to the hourly market price considers only profit maximization from energy transactions and disregards variability. This causes flexibility burdens on the main grid system operator (SO), which must then utilize its ramping capability to cover the net load variability. As the proportion of renewable energy sources (RESs) involving intermittency in MGs continues to increase owing to global energy policies, net load variability within shorter time intervals has also increased, making proper management guidelines necessary. Thus, this paper proposes an MG-SO variability contract on intra-hour and inter-hour time intervals for regulating variability such that the SO can support and distribute its relevant costs between the MG and the SO. To prove the effectiveness of the proposed contract, an MG variability contract-based scheduling model is also proposed, and the results were compared with those of the price-based model. A case study demonstrates that the introduction of RESs increases the variability in shorter intervals and that the suggested contract is effective in terms of decreasing the variability with increased MG operating costs. A sensitivity analysis between the reduced variability and additional operating costs was also conducted in the case study.

Suggested Citation

  • Sunwoong Kim & Dam Kim & Yong Tae Yoon, 2019. "Short-Term Operation Scheduling of a Microgrid under Variability Contracts to Preserve Grid Flexibility," Energies, MDPI, vol. 12(18), pages 1-16, September.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:18:p:3587-:d:268844
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    References listed on IDEAS

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    1. Hernández, Luis & Baladrón, Carlos & Aguiar, Javier M. & Carro, Belén & Sánchez-Esguevillas, Antonio & Lloret, Jaime, 2014. "Artificial neural networks for short-term load forecasting in microgrids environment," Energy, Elsevier, vol. 75(C), pages 252-264.
    2. Majzoobi, Alireza & Khodaei, Amin, 2017. "Application of microgrids in providing ancillary services to the utility grid," Energy, Elsevier, vol. 123(C), pages 555-563.
    3. Dam Kim & Hungyu Kwon & Mun-Kyeom Kim & Jong-Keun Park & Hyeongon Park, 2017. "Determining the Flexible Ramping Capacity of Electric Vehicles to Enhance Locational Flexibility," Energies, MDPI, vol. 10(12), pages 1-18, December.
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    Cited by:

    1. Matthew Gough & Sérgio F. Santos & Mohammed Javadi & Rui Castro & João P. S. Catalão, 2020. "Prosumer Flexibility: A Comprehensive State-of-the-Art Review and Scientometric Analysis," Energies, MDPI, vol. 13(11), pages 1-32, May.

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