Electric Boats and Electric Vehicles Data-Driven Approach for Enhanced Resilience in Power Distribution Networks
This paper proposes a novel hierarchical optimization framework to enhance power distribution network resilience against extreme events by incorporating electric boats (E-Boats) as complementary assets to electric vehicles (EVs). Unlike EVs reliant on potentially compromised roadways, E-Boats naviga...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10949145/ |
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| author | Abdullah Ali M. Alghamdi Dilan Jayaweera |
| author_facet | Abdullah Ali M. Alghamdi Dilan Jayaweera |
| author_sort | Abdullah Ali M. Alghamdi |
| collection | DOAJ |
| description | This paper proposes a novel hierarchical optimization framework to enhance power distribution network resilience against extreme events by incorporating electric boats (E-Boats) as complementary assets to electric vehicles (EVs). Unlike EVs reliant on potentially compromised roadways, E-Boats navigate unaffected waterways, offering superior resilience during disaster response in regions with rivers and canals. The approach employs a two-phase methodology evaluated on a modified IEEE 123-node test feeder with actual infrastructure data, enabling large-scale integration of non-pre-determined EVs/E-Boats. Phase-I emphasizes proactive planning and anticipatory optimization, leveraging extensive data integration and a developed exchange architecture enabling efficient EV/E-Boat distribution through novel selection and pairing algorithms. Phase-II focuses on adaptive restoration and coordination optimization by employing sophisticated model layers. These include advanced EV and E-Boat dispatch models that use changing geospatial data to approximate motion conditions and charging/discharging requirements, enabling energy-efficient and optimized dispatch. Detailed simulations with comprehensive performance analysis demonstrate the proposed algorithm’s superiority in achieving optimal solutions within shorter computational times. This work presents an effective solution for enhancing power network resilience using a combined EV/E-Boat network with geospatial data for EV and E-Boat locations, state-of-charge updates, and adaptive path optimization algorithms. Results highlight faster restoration, minimized costs, and reduced energy consumption. |
| format | Article |
| id | doaj-art-1f94fa4739aa4c318b7cbbebf4cb9cef |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-1f94fa4739aa4c318b7cbbebf4cb9cef2025-08-20T03:06:30ZengIEEEIEEE Access2169-35362025-01-0113604706049110.1109/ACCESS.2025.355809510949145Electric Boats and Electric Vehicles Data-Driven Approach for Enhanced Resilience in Power Distribution NetworksAbdullah Ali M. Alghamdi0https://orcid.org/0000-0003-4024-8951Dilan Jayaweera1https://orcid.org/0000-0002-1009-9089Department of Electronic, Electrical and Systems Engineering, School of Engineering, University of Birmingham, Birmingham, U.K.Department of Electronic, Electrical and Systems Engineering, School of Engineering, University of Birmingham, Birmingham, U.K.This paper proposes a novel hierarchical optimization framework to enhance power distribution network resilience against extreme events by incorporating electric boats (E-Boats) as complementary assets to electric vehicles (EVs). Unlike EVs reliant on potentially compromised roadways, E-Boats navigate unaffected waterways, offering superior resilience during disaster response in regions with rivers and canals. The approach employs a two-phase methodology evaluated on a modified IEEE 123-node test feeder with actual infrastructure data, enabling large-scale integration of non-pre-determined EVs/E-Boats. Phase-I emphasizes proactive planning and anticipatory optimization, leveraging extensive data integration and a developed exchange architecture enabling efficient EV/E-Boat distribution through novel selection and pairing algorithms. Phase-II focuses on adaptive restoration and coordination optimization by employing sophisticated model layers. These include advanced EV and E-Boat dispatch models that use changing geospatial data to approximate motion conditions and charging/discharging requirements, enabling energy-efficient and optimized dispatch. Detailed simulations with comprehensive performance analysis demonstrate the proposed algorithm’s superiority in achieving optimal solutions within shorter computational times. This work presents an effective solution for enhancing power network resilience using a combined EV/E-Boat network with geospatial data for EV and E-Boat locations, state-of-charge updates, and adaptive path optimization algorithms. Results highlight faster restoration, minimized costs, and reduced energy consumption.https://ieeexplore.ieee.org/document/10949145/Electric boatselectric vehiclespost-disaster restoration strategiespower distribution network resilience |
| spellingShingle | Abdullah Ali M. Alghamdi Dilan Jayaweera Electric Boats and Electric Vehicles Data-Driven Approach for Enhanced Resilience in Power Distribution Networks IEEE Access Electric boats electric vehicles post-disaster restoration strategies power distribution network resilience |
| title | Electric Boats and Electric Vehicles Data-Driven Approach for Enhanced Resilience in Power Distribution Networks |
| title_full | Electric Boats and Electric Vehicles Data-Driven Approach for Enhanced Resilience in Power Distribution Networks |
| title_fullStr | Electric Boats and Electric Vehicles Data-Driven Approach for Enhanced Resilience in Power Distribution Networks |
| title_full_unstemmed | Electric Boats and Electric Vehicles Data-Driven Approach for Enhanced Resilience in Power Distribution Networks |
| title_short | Electric Boats and Electric Vehicles Data-Driven Approach for Enhanced Resilience in Power Distribution Networks |
| title_sort | electric boats and electric vehicles data driven approach for enhanced resilience in power distribution networks |
| topic | Electric boats electric vehicles post-disaster restoration strategies power distribution network resilience |
| url | https://ieeexplore.ieee.org/document/10949145/ |
| work_keys_str_mv | AT abdullahalimalghamdi electricboatsandelectricvehiclesdatadrivenapproachforenhancedresilienceinpowerdistributionnetworks AT dilanjayaweera electricboatsandelectricvehiclesdatadrivenapproachforenhancedresilienceinpowerdistributionnetworks |