Coupling Neighboring Microgrids for Overload Management Based on Dynamic Multicriteria Decision-Making
A microgrid (MG) is expected to supply its local loads independently; however, due to intermittency of wind and solar-based energy resources as well as the load uncertainty, it is probable that the MG experiences power deficiency (overloading). This problem can be mitigated by coupling the overloade...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
2017
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| Online Access: | http://hdl.handle.net/20.500.11937/41463 |
| _version_ | 1848756152886624256 |
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| author | Shahnia, Farhad Bourbour, S. Ghosh, Arindam |
| author_facet | Shahnia, Farhad Bourbour, S. Ghosh, Arindam |
| author_sort | Shahnia, Farhad |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | A microgrid (MG) is expected to supply its local loads independently; however, due to intermittency of wind and solar-based energy resources as well as the load uncertainty, it is probable that the MG experiences power deficiency (overloading). This problem can be mitigated by coupling the overloaded MG to another neighboring MG that has surplus power. Considering a distribution network composed of several islanded MGs, defining the suitable MGs (alternative) to be coupled with the overloaded MG is a challenge. An MG overload management technique is developed in this paper, which first identifies the overloaded MG(s) and then selects the most suitable alternative. The alternative selection is based on different criteria, such as available surplus power, reliability, supply security, power loss, electricity cost, and CO2 emissions in the alternative MGs. Moreover, the frequency and voltage deviation in the system of coupled MGs are considered in the selection. A dynamic multicriteria decision-making algorithm is developed for this purpose. To contemplate the uncertainties in the considered distribution network, a cloud theory-based probabilistic analysis is deployed as the research framework and the performance of the developed technique is evaluated in MATLAB. |
| first_indexed | 2025-11-14T09:07:40Z |
| format | Journal Article |
| id | curtin-20.500.11937-41463 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:07:40Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-414632017-09-13T15:39:43Z Coupling Neighboring Microgrids for Overload Management Based on Dynamic Multicriteria Decision-Making Shahnia, Farhad Bourbour, S. Ghosh, Arindam A microgrid (MG) is expected to supply its local loads independently; however, due to intermittency of wind and solar-based energy resources as well as the load uncertainty, it is probable that the MG experiences power deficiency (overloading). This problem can be mitigated by coupling the overloaded MG to another neighboring MG that has surplus power. Considering a distribution network composed of several islanded MGs, defining the suitable MGs (alternative) to be coupled with the overloaded MG is a challenge. An MG overload management technique is developed in this paper, which first identifies the overloaded MG(s) and then selects the most suitable alternative. The alternative selection is based on different criteria, such as available surplus power, reliability, supply security, power loss, electricity cost, and CO2 emissions in the alternative MGs. Moreover, the frequency and voltage deviation in the system of coupled MGs are considered in the selection. A dynamic multicriteria decision-making algorithm is developed for this purpose. To contemplate the uncertainties in the considered distribution network, a cloud theory-based probabilistic analysis is deployed as the research framework and the performance of the developed technique is evaluated in MATLAB. 2017 Journal Article http://hdl.handle.net/20.500.11937/41463 10.1109/TSG.2015.2477845 restricted |
| spellingShingle | Shahnia, Farhad Bourbour, S. Ghosh, Arindam Coupling Neighboring Microgrids for Overload Management Based on Dynamic Multicriteria Decision-Making |
| title | Coupling Neighboring Microgrids for Overload Management Based on Dynamic Multicriteria Decision-Making |
| title_full | Coupling Neighboring Microgrids for Overload Management Based on Dynamic Multicriteria Decision-Making |
| title_fullStr | Coupling Neighboring Microgrids for Overload Management Based on Dynamic Multicriteria Decision-Making |
| title_full_unstemmed | Coupling Neighboring Microgrids for Overload Management Based on Dynamic Multicriteria Decision-Making |
| title_short | Coupling Neighboring Microgrids for Overload Management Based on Dynamic Multicriteria Decision-Making |
| title_sort | coupling neighboring microgrids for overload management based on dynamic multicriteria decision-making |
| url | http://hdl.handle.net/20.500.11937/41463 |