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DC Field | Value | Language |
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dc.contributor.author | Kreishan, MZ | - |
dc.contributor.author | Zobaa, AF | - |
dc.date.accessioned | 2023-05-25T10:59:09Z | - |
dc.date.available | 2023-05-25T10:59:09Z | - |
dc.date.issued | 2023-05-22 | - |
dc.identifier.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. | en_US |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/26524 | - |
dc.description | Data Availability Statement: The data supporting the reported results are available in the manuscript. | - |
dc.description.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. | en_US |
dc.description.sponsorship | This research received no external funding. | - |
dc.format.medium | Electronic | - |
dc.publisher | MDPI | en_US |
dc.rights | Copyright © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | ant colony optimization | en_US |
dc.subject | droop control | en_US |
dc.subject | dump load | en_US |
dc.subject | load flow | en_US |
dc.subject | multi-objective optimization | en_US |
dc.subject | islanded microgrid | en_US |
dc.subject | scenario-based stochastic modeling | en_US |
dc.subject | wind power uncertainty | en_US |
dc.title | Scenario-Based Uncertainty Modeling for Power Management in Islanded Microgrid Using the Mixed-Integer Distributed Ant Colony Optimization | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.3390/en16104257 | - |
dc.relation.isPartOf | Energies | - |
pubs.issue | 10 | - |
pubs.publication-status | Published | - |
pubs.volume | 16 | - |
dc.identifier.eissn | 1996-1073 | - |
Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers |
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FullText.pdf | Copyright © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | 9.15 MB | Adobe PDF | View/Open |
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