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Optimal Operational Scheduling of Reconfigurable Multi-Microgrids Considering Energy Storage Systems

Author

Listed:
  • Saeid Esmaeili

    (Department of Electrical Engineering, Iran University of Science and Technology, 16846-13114 Tehran, Iran)

  • Amjad Anvari-Moghaddam

    (Department of Energy Technology, Aalborg University, 9220 Aalborg East, Denmark)

  • Shahram Jadid

    (Department of Electrical Engineering, Iran University of Science and Technology, 16846-13114 Tehran, Iran)

Abstract

This paper proposes an optimal operational scheduling of a reconfigurable multi-microgrid (MG) distribution system complemented by demand response programs and Energy Storage Systems (ESSs) in an uncertain environment. Since there is a set of competing players with inherently conflicting objectives in the system under study such as the Distribution System Operator (DSO) and MG owners, a one-leader multi-follower-type bi-level optimization model is proposed. In this framework, the upper-level player as a leader minimizes the total cost from DSO’s point of view, while the lower-level players as multi-followers maximize the profit of MG owners. Since the resulting model is a non-linear bi-level optimization problem, it is transformed into a single-level mixed-integer second-order cone programming problem through Karush–Kuhn–Tucker conditions. The satisfactory performance of the proposed model is investigated on a real-test system under different scenarios and working conditions.

Suggested Citation

  • Saeid Esmaeili & Amjad Anvari-Moghaddam & Shahram Jadid, 2019. "Optimal Operational Scheduling of Reconfigurable Multi-Microgrids Considering Energy Storage Systems," Energies, MDPI, vol. 12(9), pages 1-23, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1766-:d:229786
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    References listed on IDEAS

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    Cited by:

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    3. Ricardo Echeverri Mart nez & Eduardo Caicedo Bravo & Wilfredo Alfonso Morales & Juan David Garcia-Racines, 2020. "A Bi-level Multi-objective Optimization Model for the Planning, Design and Operation of Smart Grid Projects. Case Study: An Islanded Microgrid," International Journal of Energy Economics and Policy, Econjournals, vol. 10(4), pages 325-341.
    4. Mingyue He & Zahra Soltani & Mojdeh Khorsand & Aaron Dock & Patrick Malaty & Masoud Esmaili, 2022. "Behavior-Aware Aggregation of Distributed Energy Resources for Risk-Aware Operational Scheduling of Distribution Systems," Energies, MDPI, vol. 15(24), pages 1-18, December.
    5. Matamala, Yolanda & Feijoo, Felipe, 2021. "A two-stage stochastic Stackelberg model for microgrid operation with chance constraints for renewable energy generation uncertainty," Applied Energy, Elsevier, vol. 303(C).
    6. Xiaohong Yin & Lin Li & Qiang Liu, 2022. "A Study on the Vulnerability Cascade Propagation of Integrated Energy Systems in the Transportation Industry Based on the Petri Network," Energies, MDPI, vol. 15(12), pages 1-12, June.
    7. Nevena Srećković & Miran Rošer & Gorazd Štumberger, 2021. "Utilization of Active Distribution Network Elements for Optimization of a Distribution Network Operation," Energies, MDPI, vol. 14(12), pages 1-17, June.

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