A novel and sturdy MPPT architecture for grid-tied EV charging stations using Ali Baba and forty thieves optimization
Abstract In recent years, networks of power systems have increasingly implemented renewable energy sources. Due to the fast advancement of civilisation, the incidence of global warming and certain catastrophic climatic changes is increasing, along with cultural modernisation. Electric vehicles (EVs)...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-06-01
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| Series: | Discover Sustainability |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s43621-025-01089-w |
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| Summary: | Abstract In recent years, networks of power systems have increasingly implemented renewable energy sources. Due to the fast advancement of civilisation, the incidence of global warming and certain catastrophic climatic changes is increasing, along with cultural modernisation. Electric vehicles (EVs) are being promoted in practically every country to combat this environmental problem related to vehicles transmission. Nevertheless, using traditional fossil fuels to charge these EVs is not technically or economically feasible. A review of the literature indicates that PV module-based EV charging stations need an effective MPPT controller. It must be able to monitor Global Maximum Power Point (GMPP) as quickly as feasible in the grid integration. Standby battery (SBB) is also crucial since it ensures a steady supply of power for the vehicles. Thus, this manuscript suggests an EV charging station powered by renewable energy that combines solar power, standby battery systems, advanced control methods like neural network-integrated grids, the PID controller, and the improved Ali Baba and forty thief’s optimizations (ABFTO) for Maximum Power Point Tracking. This concept outperforms existing approaches and offers a workable strategy to advance the EV revolution while reducing environmental impact. Even in unpredictable conditions, it ensures a consistent power supply and optimises energy management. The power output of the proposed approach is compared with the two well-known soft computing based MPPT approaches, i.e., Cuckoo Search Algorithm and Grey Wolf Optimization. The comparison result ensures maximizing power output of the developed method. The reliability of power supply at charging stations is guaranteed via grid integration. This approach aims to optimize modelling for all EV fleets. The developed method performs exceptionally well in comparison to other algorithms that have been studied in the literature. In addition to the backup battery, grid integration is necessary to guarantee the charging station has a steady power source, even in erratic weather. |
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| ISSN: | 2662-9984 |