Unified dispatch of grid-connected and islanded microgrids
This work develops microgrid dispatch algorithms with a unified approach to model predictive control (MPC) to (a) operate in grid-connected mode to minimize total operational cost, (b) operate in islanded mode to maximize resilience during a utility outage, and (c) utilize weighting factors in the g...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-01-01
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| Series: | Frontiers in Energy Research |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2023.1257050/full |
| _version_ | 1797362370779021312 |
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| author | Mackenzie Robert Wodicker James Nelson Nathan Gregory Johnson |
| author_facet | Mackenzie Robert Wodicker James Nelson Nathan Gregory Johnson |
| author_sort | Mackenzie Robert Wodicker |
| collection | DOAJ |
| description | This work develops microgrid dispatch algorithms with a unified approach to model predictive control (MPC) to (a) operate in grid-connected mode to minimize total operational cost, (b) operate in islanded mode to maximize resilience during a utility outage, and (c) utilize weighting factors in the grid-connected objective function to preserve islanded capability (on-site fuel reserves, battery state of charge) to enhance resilience in the potential event of an unplanned grid outage. Resilience is defined using microgrid survivability (probability to serve 100% of critical load), autonomy (duration of time to serve 100% of critical load), and unserved energy (curtailed critical load) for a target of 7 days during a grid outage. The developed methods are applied to a military microgrid with 2,250 kW of diesel generation, 3,450 kW/13,800 kWh battery storage, and 16,479 kW of solar photovoltaics. Sensitivity analysis is conducted to determine the selection of weighting factors to have the best impact on three developed objectives: grid-connected economics, islanded resilience, and carbon intensity. Optimal weighting factors reduce operating costs by 0.1%, increase survivability by 3.9%, increase autonomy by 16.7%, reduce unserved energy by 94.1%, and increase carbon intensity by 2.5%. |
| first_indexed | 2024-03-08T16:06:06Z |
| format | Article |
| id | doaj.art-112c7cd905a8460193d6a7853d23351a |
| institution | Directory Open Access Journal |
| issn | 2296-598X |
| language | English |
| last_indexed | 2024-03-08T16:06:06Z |
| publishDate | 2024-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj.art-112c7cd905a8460193d6a7853d23351a2024-01-08T05:23:33ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2024-01-011110.3389/fenrg.2023.12570501257050Unified dispatch of grid-connected and islanded microgridsMackenzie Robert WodickerJames NelsonNathan Gregory JohnsonThis work develops microgrid dispatch algorithms with a unified approach to model predictive control (MPC) to (a) operate in grid-connected mode to minimize total operational cost, (b) operate in islanded mode to maximize resilience during a utility outage, and (c) utilize weighting factors in the grid-connected objective function to preserve islanded capability (on-site fuel reserves, battery state of charge) to enhance resilience in the potential event of an unplanned grid outage. Resilience is defined using microgrid survivability (probability to serve 100% of critical load), autonomy (duration of time to serve 100% of critical load), and unserved energy (curtailed critical load) for a target of 7 days during a grid outage. The developed methods are applied to a military microgrid with 2,250 kW of diesel generation, 3,450 kW/13,800 kWh battery storage, and 16,479 kW of solar photovoltaics. Sensitivity analysis is conducted to determine the selection of weighting factors to have the best impact on three developed objectives: grid-connected economics, islanded resilience, and carbon intensity. Optimal weighting factors reduce operating costs by 0.1%, increase survivability by 3.9%, increase autonomy by 16.7%, reduce unserved energy by 94.1%, and increase carbon intensity by 2.5%.https://www.frontiersin.org/articles/10.3389/fenrg.2023.1257050/fullmicrogridclimate resiliencemicrogrid islandingoptimizationmicrogrid dispatchenergy economics |
| spellingShingle | Mackenzie Robert Wodicker James Nelson Nathan Gregory Johnson Unified dispatch of grid-connected and islanded microgrids Frontiers in Energy Research microgrid climate resilience microgrid islanding optimization microgrid dispatch energy economics |
| title | Unified dispatch of grid-connected and islanded microgrids |
| title_full | Unified dispatch of grid-connected and islanded microgrids |
| title_fullStr | Unified dispatch of grid-connected and islanded microgrids |
| title_full_unstemmed | Unified dispatch of grid-connected and islanded microgrids |
| title_short | Unified dispatch of grid-connected and islanded microgrids |
| title_sort | unified dispatch of grid connected and islanded microgrids |
| topic | microgrid climate resilience microgrid islanding optimization microgrid dispatch energy economics |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2023.1257050/full |
| work_keys_str_mv | AT mackenzierobertwodicker unifieddispatchofgridconnectedandislandedmicrogrids AT jamesnelson unifieddispatchofgridconnectedandislandedmicrogrids AT nathangregoryjohnson unifieddispatchofgridconnectedandislandedmicrogrids |