Integration of electric vehicle charging stations with distributed generation using multi-objective metaheuristic optimization
The growing adoption of Electric Vehicles will lead to an increase in the number of charging stations, which can introduce several problems to power distribution networks. Research on incorporating Distributed Generators (DGs) and Electric Vehicle Charging Stations (EVCS) into radial distribution sy...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
|
| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025026374 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849762167843192832 |
|---|---|
| author | Aya Desoky Gaber E.M. Abdallah M.I. Elsayed Ahmed Abdelbaset |
| author_facet | Aya Desoky Gaber E.M. Abdallah M.I. Elsayed Ahmed Abdelbaset |
| author_sort | Aya Desoky Gaber |
| collection | DOAJ |
| description | The growing adoption of Electric Vehicles will lead to an increase in the number of charging stations, which can introduce several problems to power distribution networks. Research on incorporating Distributed Generators (DGs) and Electric Vehicle Charging Stations (EVCS) into radial distribution systems (RDS) is expanding to enhance voltage profiles, reduce losses, meet growing power demands, and raise the voltage stability index (VSI). This paper uses a multi-objective optimization approach metaheuristic algorithm, specifically the Whale Optimization Algorithm (WOA), Zebra Optimization Algorithm (ZOA), and Puma Optimization Algorithm (POA), to determine the optimal size and placement of DG units in the presence of EVCS. The objectives include reducing the average voltage deviation index (AVDI) and raising VSI. The proposed methodology is tested on IEEE 33-bus and 69-bus systems under six scenarios: a base case without EVCS or DG (Case 1), non-optimized EVCS (Case 2), optimized EVCS alone (Case 3), and EVCS combined with three DG operation modes in Cases 4, 5, and 6. Case 6 shows the most favorable results, where POA reduces losses by 85.46% and 96.27% and raises voltage levels to 0.9888 p.u. and 0.9942 p.u. for the IEEE 33- and 69-bus systems, respectively. Although WOA and ZOA slightly outperform POA in certain indicators like AVDI and VSI, Overall POA consistently achieves the most balanced and robust improvements, confirming its capability to enhance distribution system efficiency and voltage stability. |
| format | Article |
| id | doaj-art-20a98a15fd51463d8174c635ca45d0bd |
| institution | DOAJ |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-20a98a15fd51463d8174c635ca45d0bd2025-08-20T03:05:49ZengElsevierResults in Engineering2590-12302025-09-012710656810.1016/j.rineng.2025.106568Integration of electric vehicle charging stations with distributed generation using multi-objective metaheuristic optimizationAya Desoky Gaber0E.M. Abdallah1M.I. Elsayed2Ahmed Abdelbaset3Department of Electric Power and Machines Engineering, Higher Institute of Engineering, El-Shorouk Academy, Cairo, Egypt; Corresponding author.Department of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Cairo, EgyptDepartment of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Cairo, EgyptDepartment of Electric Power and Machines Engineering, Higher Institute of Engineering, El-Shorouk Academy, Cairo, EgyptThe growing adoption of Electric Vehicles will lead to an increase in the number of charging stations, which can introduce several problems to power distribution networks. Research on incorporating Distributed Generators (DGs) and Electric Vehicle Charging Stations (EVCS) into radial distribution systems (RDS) is expanding to enhance voltage profiles, reduce losses, meet growing power demands, and raise the voltage stability index (VSI). This paper uses a multi-objective optimization approach metaheuristic algorithm, specifically the Whale Optimization Algorithm (WOA), Zebra Optimization Algorithm (ZOA), and Puma Optimization Algorithm (POA), to determine the optimal size and placement of DG units in the presence of EVCS. The objectives include reducing the average voltage deviation index (AVDI) and raising VSI. The proposed methodology is tested on IEEE 33-bus and 69-bus systems under six scenarios: a base case without EVCS or DG (Case 1), non-optimized EVCS (Case 2), optimized EVCS alone (Case 3), and EVCS combined with three DG operation modes in Cases 4, 5, and 6. Case 6 shows the most favorable results, where POA reduces losses by 85.46% and 96.27% and raises voltage levels to 0.9888 p.u. and 0.9942 p.u. for the IEEE 33- and 69-bus systems, respectively. Although WOA and ZOA slightly outperform POA in certain indicators like AVDI and VSI, Overall POA consistently achieves the most balanced and robust improvements, confirming its capability to enhance distribution system efficiency and voltage stability.http://www.sciencedirect.com/science/article/pii/S2590123025026374Optimal placementCharging stationDistribution generationLoss reductionWhale optimization algorithm (WOA)Zebra optimization algorithm (ZOA) |
| spellingShingle | Aya Desoky Gaber E.M. Abdallah M.I. Elsayed Ahmed Abdelbaset Integration of electric vehicle charging stations with distributed generation using multi-objective metaheuristic optimization Results in Engineering Optimal placement Charging station Distribution generation Loss reduction Whale optimization algorithm (WOA) Zebra optimization algorithm (ZOA) |
| title | Integration of electric vehicle charging stations with distributed generation using multi-objective metaheuristic optimization |
| title_full | Integration of electric vehicle charging stations with distributed generation using multi-objective metaheuristic optimization |
| title_fullStr | Integration of electric vehicle charging stations with distributed generation using multi-objective metaheuristic optimization |
| title_full_unstemmed | Integration of electric vehicle charging stations with distributed generation using multi-objective metaheuristic optimization |
| title_short | Integration of electric vehicle charging stations with distributed generation using multi-objective metaheuristic optimization |
| title_sort | integration of electric vehicle charging stations with distributed generation using multi objective metaheuristic optimization |
| topic | Optimal placement Charging station Distribution generation Loss reduction Whale optimization algorithm (WOA) Zebra optimization algorithm (ZOA) |
| url | http://www.sciencedirect.com/science/article/pii/S2590123025026374 |
| work_keys_str_mv | AT ayadesokygaber integrationofelectricvehiclechargingstationswithdistributedgenerationusingmultiobjectivemetaheuristicoptimization AT emabdallah integrationofelectricvehiclechargingstationswithdistributedgenerationusingmultiobjectivemetaheuristicoptimization AT mielsayed integrationofelectricvehiclechargingstationswithdistributedgenerationusingmultiobjectivemetaheuristicoptimization AT ahmedabdelbaset integrationofelectricvehiclechargingstationswithdistributedgenerationusingmultiobjectivemetaheuristicoptimization |