Distributed Renewable Energy Network for Electric Vehicle with Battery Ferry Supply CHain Management, Battery Swapping

Abstract

This thesis presents a widespread adoption of renewable energy, e.g., solar farms, to charge electric vehicle (EV) batteries. A sustainable decentralized network of battery ferrying and swapping technique is proposed. Batteries are charged by solar power at the solar farm, transported to local distributors, and further distributed to consumers’ EVs through delivery vans. The scenario focuses on building off-grid decentralized so- lar farms for communities (dependent on fossil fuel) overburdened with limited space not to use renewable energy. The model constructs a network that provides charged batteries at any time, at the doorstep to mitigate the range anxiety aligned with EVs. It is a cyber-physical framework (using the Internet of Things (IoT)) enabling machine- to-machine communication (i.e., battery-to-battery or battery-to-EV) in real-time in- formation (inclusion of EV user). A simulated scenario assesses the successful battery deliveries/supplies considering driving locations, traveling paths, demand for charging requests, etc. The results use a 4-layer neural network to forecast/predict the battery demand with an explained variance of 0.99289 for 72 hours, enabling batteries to be delivered within the shortest time and adequate number of batteries to be stored at the solar farm for supply. Besides, a system with a first-come, first-served (FCFS) queuing strategy is simulated where local distributors are placed at an optimum position near consumers through k-means clustering which provides efficiency of 82.524%. This thesis focuses on battery ferrying and swapping techniques and considers a human- centered practical approach of a green decentralized battery network that adopts the vision of Society 5.0.