| Autor: |
Syafii Syafii, Krismadinata Krismadinata, Muladi Muladi, Thoriq Kurnia Agung, Devianda Ananta Sandri |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Journal of Sustainable Development of Energy, Water and Environment Systems, Vol 12, Iss 1, Pp 1-12 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1848-9257 |
| DOI: |
10.13044/j.sdewes.d11.0476 |
| Popis: |
Solar electric vehicle charging can substantially reduce carbon emissions compared to conventional utility grid-based electric vehicle charging. In the future, the need for the use of electric vehicle charging will continue to increase so that an energy charging management system that is simple and has ubiquitous components is needed. This paper presented a simple charging management system. The current solution is full of complexity with various algorithms, deep learning and machine learning solutions, and artificial intelligence, which can lead to errors for which no known solution exists. The main novelty in the proposed strategy is to compare the components used to get a simple but reliable system. The component that will compare is Raspberry Pi and ESP32. The ESP32 can offset the advantages of the Raspberry Pi with the help of Blynk, so for a simple and cheaper but reliable system, the ESP32 system is better for an energy charging management system. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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