Decentralized Energy Consumption Analysis Framework for Coordinated EVs Charging

With the modernization of the transportation system, EVs penetration has been promoted significantly and holds great potential by maintaining energy sustainability for the greener environment. Nevertheless, owing to the vast number of EVs arriving at the CS, there is a high possibility of imbalanced energy exchange between EV and CS, which also disrupts the working of the smart grid. Moreover, security and privacy issues during EV energy transactions are not handled by the researchers to that extent. Thus, we propose a blockchain-based EV energy consumption analysis framework for predicting Evs' SoC in the smart grid environment. We have applied a sequential model to predict EVs SoC based on the various effecting parameters using optimizers such as Adam, Adadelta, and RMSprop. The incorporated IPFS protocol is combined with the blockchain to ensure the reliability and availability of the proposed framework during the EV energy consumption prediction. Finally, the proposed framework is analyzed and evaluated considering various standard performance metrics such as loss using MSE, MAE, and SoC error prediction in which the sequential model with Adam outperforms other optimizers in terms of minimum error and loss.