Optimization Techniques in Electric Vehicle Charging Scheduling, Routing and Spatio-Temporal Demand Coordination: A Systematic Review
The growing penetration of electric vehicles (EVs) and the increasing EV energy demand pose several challenges to the power grid, the power distribution networks and the transportation networks. This growing demand drives the need for effective demand management and energy coordination strategies to...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Open Journal of Vehicular Technology |
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| Online Access: | https://ieeexplore.ieee.org/document/10577180/ |
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| author | Eiman Elghanam Akmal Abdelfatah Mohamed S. Hassan Ahmed H. Osman |
| author_facet | Eiman Elghanam Akmal Abdelfatah Mohamed S. Hassan Ahmed H. Osman |
| author_sort | Eiman Elghanam |
| collection | DOAJ |
| description | The growing penetration of electric vehicles (EVs) and the increasing EV energy demand pose several challenges to the power grid, the power distribution networks and the transportation networks. This growing demand drives the need for effective demand management and energy coordination strategies to maximize the demand covered by the EV charging stations, ensure EV users' satisfaction and prevent grid-side overload. As a result, several optimization problems are formulated and solved in the literature to provide optimal EV charging schedules (i.e. temporal coordination) as well as optimal EV-to-charging-station assignments and routing plans (i.e. spatial coordination). This paper presents a review of the state-of-the-art literature on the utilization of different deterministic optimization techniques to develop optimal EV charging coordination strategies. In particular, these works are reviewed according to their domains of operation (i.e. time-based scheduling, spatial coordination, and spatio-temporal charging coordination), their respective objectives (user-, grid- and operator-related objectives), and the solution algorithms adopted to provide the corresponding optimal coordination plans. This helps in identifying key research gaps and provide recommendations for future research directions to develop comprehensive and computationally efficient charging coordination models. |
| format | Article |
| id | doaj-art-aeffdec646cc4e36b065e82c54eb0b53 |
| institution | Kabale University |
| issn | 2644-1330 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Vehicular Technology |
| spelling | doaj-art-aeffdec646cc4e36b065e82c54eb0b532025-01-30T00:04:19ZengIEEEIEEE Open Journal of Vehicular Technology2644-13302024-01-0151294131310.1109/OJVT.2024.342024410577180Optimization Techniques in Electric Vehicle Charging Scheduling, Routing and Spatio-Temporal Demand Coordination: A Systematic ReviewEiman Elghanam0https://orcid.org/0000-0003-1342-2934Akmal Abdelfatah1https://orcid.org/0000-0001-7709-9932Mohamed S. Hassan2https://orcid.org/0000-0001-6318-0748Ahmed H. Osman3https://orcid.org/0000-0001-9302-8608Department of Industrial Engineering, American University of Sharjah, Sharjah, UAEDepartment of Civil Engineering, American University of Sharjah, Sharjah, UAEDepartment of Electrical Engineering, American University of Sharjah, Sharjah, UAEDepartment of Electrical Engineering, American University of Sharjah, Sharjah, UAEThe growing penetration of electric vehicles (EVs) and the increasing EV energy demand pose several challenges to the power grid, the power distribution networks and the transportation networks. This growing demand drives the need for effective demand management and energy coordination strategies to maximize the demand covered by the EV charging stations, ensure EV users' satisfaction and prevent grid-side overload. As a result, several optimization problems are formulated and solved in the literature to provide optimal EV charging schedules (i.e. temporal coordination) as well as optimal EV-to-charging-station assignments and routing plans (i.e. spatial coordination). This paper presents a review of the state-of-the-art literature on the utilization of different deterministic optimization techniques to develop optimal EV charging coordination strategies. In particular, these works are reviewed according to their domains of operation (i.e. time-based scheduling, spatial coordination, and spatio-temporal charging coordination), their respective objectives (user-, grid- and operator-related objectives), and the solution algorithms adopted to provide the corresponding optimal coordination plans. This helps in identifying key research gaps and provide recommendations for future research directions to develop comprehensive and computationally efficient charging coordination models.https://ieeexplore.ieee.org/document/10577180/Electric vehiclescharging coordinationdeterministic optimizationexact methodsheuristicsmetaheuristics |
| spellingShingle | Eiman Elghanam Akmal Abdelfatah Mohamed S. Hassan Ahmed H. Osman Optimization Techniques in Electric Vehicle Charging Scheduling, Routing and Spatio-Temporal Demand Coordination: A Systematic Review IEEE Open Journal of Vehicular Technology Electric vehicles charging coordination deterministic optimization exact methods heuristics metaheuristics |
| title | Optimization Techniques in Electric Vehicle Charging Scheduling, Routing and Spatio-Temporal Demand Coordination: A Systematic Review |
| title_full | Optimization Techniques in Electric Vehicle Charging Scheduling, Routing and Spatio-Temporal Demand Coordination: A Systematic Review |
| title_fullStr | Optimization Techniques in Electric Vehicle Charging Scheduling, Routing and Spatio-Temporal Demand Coordination: A Systematic Review |
| title_full_unstemmed | Optimization Techniques in Electric Vehicle Charging Scheduling, Routing and Spatio-Temporal Demand Coordination: A Systematic Review |
| title_short | Optimization Techniques in Electric Vehicle Charging Scheduling, Routing and Spatio-Temporal Demand Coordination: A Systematic Review |
| title_sort | optimization techniques in electric vehicle charging scheduling routing and spatio temporal demand coordination a systematic review |
| topic | Electric vehicles charging coordination deterministic optimization exact methods heuristics metaheuristics |
| url | https://ieeexplore.ieee.org/document/10577180/ |
| work_keys_str_mv | AT eimanelghanam optimizationtechniquesinelectricvehiclechargingschedulingroutingandspatiotemporaldemandcoordinationasystematicreview AT akmalabdelfatah optimizationtechniquesinelectricvehiclechargingschedulingroutingandspatiotemporaldemandcoordinationasystematicreview AT mohamedshassan optimizationtechniquesinelectricvehiclechargingschedulingroutingandspatiotemporaldemandcoordinationasystematicreview AT ahmedhosman optimizationtechniquesinelectricvehiclechargingschedulingroutingandspatiotemporaldemandcoordinationasystematicreview |