Multi-agent framework for smart management of electric vehicle charging stations (EVCS) considering a smart charging scheduling, smart contracts and data validation by OCPP

Abstract

This paper presents a comprehensive model for electric vehicle chargers (EVC) focused on scheduling loads in electric vehicle charging stations (EVCS). It also applies practical information from data gathered by Open Charge Point Protocol (OCPP) for validation of results. The scheduling strategy applies an evolutionary particle swarm optimization (EPSO) metaheuristic to set the hours for charge of the EV. The battery charging model combines the Kinetic Battery Model (KiBaM) and a Voltage Model (VM). A practical validation for the battery model accuracy is made with real data gathered by OCPP. The results showed a good operation for the framework in the EVCS in terms of economic cost and grid impact.. The results also showed a good performance for the battery model. Finally, the OCPP confirmed the results of the model with low errors in terms of performance.