Assessment of predictive smart charging for electric trucks: a case study in fast private charging stations

Nowadays, the electrification of mobility and its charging by renewable energy sources has become a hot topic. In this regard, suitable solutions have been predicted for possible challenges in the presence of the high energy demand of passenger cars. Therefore, various charging algorithms with specific objective functions have been proposed for different applications. However, the emergence and growth of heavy electric vehicles such as trucks have a deeper impact on the local system, which reveals the need for more study in this field. In this paper, the impact of smart charging of electric truck as a flexible element in a fast-charging station of a factory is analyzed. The proposed predictive optimization charging algorithm for different uncontrolled, unidirectional and bidirectional scenarios tries to minimize the cost of energy exchanged with the grid. In this regard, considering the health of the battery, the best scenario from the factory owner's point of view is selected for a two-day interval including four different charge periods. Although it is obvious that the best scenario depends on the different parameters of each case study, the smart charging scenarios impose less cost on the local system in the desired case study.