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Scenario-Based Uncertainty Modeling for Power Management in Islanded Microgrid Using the Mixed-Integer Distributed Ant Colony Optimization

Author

Listed:
  • Maen Z. Kreishan

    (Electronic and Electrical Engineering Department, Brunel University London, Uxbridge UB8 3PH, UK)

  • Ahmed F. Zobaa

    (Electronic and Electrical Engineering Department, Brunel University London, Uxbridge UB8 3PH, UK)

Abstract

Reliable droop-controlled islanded microgrids are necessary to expand coverage and maximize renewables potential. Nonetheless, due to uncertainties surrounding renewable generation and load forecast, substantial power mismatch is expected at off-peak hours. Existing energy management systems such as storage and demand response are not equipped to handle a large power mismatch. Hence, utilizing dump loads to consume excess power is a promising solution to keep frequency and voltage within permissible limits during low-load hours. Considering the uncertainty in wind generation and demand forecast during off-peak hours, the dump load allocation problem was modeled within a scenario-based stochastic framework. The multi-objective optimization with uncertainty was formulated to minimize total microgrid cost, maximum voltage error, frequency deviation, and total energy loss. The mixed-integer distributed ant colony optimization was utilized in a massive parallelization framework for the first time in microgrids to solve the decomposed deterministic problem of the most probable scenarios. Moreover, a flexible and robust load-flow method called general backward/forward sweep was used to obtain the load-flow solution. The optimization problem was applied to the IEEE 69-bus and 118-bus systems. Furthermore, a cost benefit analysis was provided to highlight the proposed method’s advantage over battery-based power management solutions. Lastly, the obtained results further demonstrate the fundamental role of dump load as power management solution while minimizing costs and energy losses.

Suggested Citation

  • Maen Z. Kreishan & Ahmed F. Zobaa, 2023. "Scenario-Based Uncertainty Modeling for Power Management in Islanded Microgrid Using the Mixed-Integer Distributed Ant Colony Optimization," Energies, MDPI, vol. 16(10), pages 1-30, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:10:p:4257-:d:1153079
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    References listed on IDEAS

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    1. Fontenot, Hannah & Dong, Bing, 2019. "Modeling and control of building-integrated microgrids for optimal energy management – A review," Applied Energy, Elsevier, vol. 254(C).
    2. El-Bidairi, Kutaiba S. & Nguyen, Hung Duc & Mahmoud, Thair S. & Jayasinghe, S.D.G. & Guerrero, Josep M., 2020. "Optimal sizing of Battery Energy Storage Systems for dynamic frequency control in an islanded microgrid: A case study of Flinders Island, Australia," Energy, Elsevier, vol. 195(C).
    3. Maen Z. Kreishan & Ahmed F. Zobaa, 2021. "Optimal Allocation and Operation of Droop-Controlled Islanded Microgrids: A Review," Energies, MDPI, vol. 14(15), pages 1-45, July.
    4. Martin Schlüter & Matthias Gerdts, 2010. "The oracle penalty method," Journal of Global Optimization, Springer, vol. 47(2), pages 293-325, June.
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