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Economic Operation of Utility-Connected Microgrids in a Fast and Flexible Framework Considering Non-Dispatchable Energy Sources

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  • Rasoul Akbari

    (Energy Systems and Power Electronics Lab, Purdue School of Engineering and Technology, Indianapolis, IN 46202, USA)

  • Seyede Zahra Tajalli

    (Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 71557-13876, Iran)

  • Abdollah Kavousi-Fard

    (Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 71557-13876, Iran)

  • Afshin Izadian

    (Energy Systems and Power Electronics Lab, Purdue School of Engineering and Technology, Indianapolis, IN 46202, USA)

Abstract

This paper introduces a modified consensus-based real-time optimization framework for utility-connected and islanded microgrids scheduling in normal conditions and under cyberattacks. The exchange of power with the utility is modeled, and the operation of the microgrid energy resources is optimized to minimize the total energy cost. This framework tracks both generation and load variations to decide optimal power generations and the exchange of power with the utility. A linear cost function is defined for the utility where the rates are updated at every time interval. In addition, a realistic approach is taken to limit the power generation from renewable energy sources, including photovoltaics (PVs), wind turbines (WTs), and dispatchable distributed generators (DDGs). The maximum output power of DDGs is limited to their ramp rates. Besides this, a specific cloud-fog architecture is suggested to make the real-time operation and monitoring of the proposed method feasible for utility-connected and islanded microgrids. The cloud-fog-based framework is flexible in applying demand response (DR) programs for more efficiency of the power operation. The algorithm’s performance is examined on the 14 bus IEEE network and is compared with optimal results. Three operating scenarios are considered to model the load as light and heavy, and after denial of service (DoS) attack to indicate the algorithm’s feasibility, robustness, and proficiency. In addition, the uncertainty of the system is analyzed using the unscented transformation (UT) method. The simulation results demonstrate a robust, rapid converging rate and the capability to track the load variations due to the probable responsive loads (considering DR programs) or natural alters of load demand.

Suggested Citation

  • Rasoul Akbari & Seyede Zahra Tajalli & Abdollah Kavousi-Fard & Afshin Izadian, 2022. "Economic Operation of Utility-Connected Microgrids in a Fast and Flexible Framework Considering Non-Dispatchable Energy Sources," Energies, MDPI, vol. 15(8), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:8:p:2894-:d:794194
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    References listed on IDEAS

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    1. Janssen, Hans, 2013. "Monte-Carlo based uncertainty analysis: Sampling efficiency and sampling convergence," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 123-132.
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    Cited by:

    1. Jing Yu & Jicheng Liu & Yajing Wen & Xue Yu, 2023. "Economic Optimal Coordinated Dispatch of Power for Community Users Considering Shared Energy Storage and Demand Response under Blockchain," Sustainability, MDPI, vol. 15(8), pages 1-26, April.
    2. Hui Zhou & Jian Ding & Yinlong Hu & Zisong Ye & Shang Shi & Yonghui Sun & Qiyu Zhang, 2022. "Economic Dispatch of Power Retailers: A Bi-Level Programming Approach via Market Clearing Price," Energies, MDPI, vol. 15(19), pages 1-17, September.
    3. Zejun Tong & Chun Zhang & Xiaotai Wu & Pengcheng Gao & Shuang Wu & Haoyu Li, 2023. "Economic Optimization Control Method of Grid-Connected Microgrid Based on Improved Pinning Consensus," Energies, MDPI, vol. 16(3), pages 1-31, January.

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