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Title: Scenario-Based Uncertainty Modeling for Power Management in Islanded Microgrid Using the Mixed-Integer Distributed Ant Colony Optimization
Authors: Kreishan, MZ
Zobaa, AF
Keywords: ant colony optimization;droop control;dump load;load flow;multi-objective optimization;islanded microgrid;scenario-based stochastic modeling;wind power uncertainty
Issue Date: 22-May-2023
Publisher: MDPI
Citation: Kreishan, M.Z. and Zobaa, A.F. (2023). 'Scenario-Based Uncertainty Modeling for Power Management in Islanded Microgrid Using the Mixed-Integer Distributed Ant Colony Optimization', Energies, 16(10), 4257, pp.1 - 30. doi: 10.3390/en16104257.
Abstract: Copyright: © 2023 by the authors. 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.
Description: Data Availability Statement: The data supporting the reported results are available in the manuscript.
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

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