Adaptive charging management for electric and fuel cell vehicles in smart distribution networks: a multi-objective optimization framework

This research paper provides an all-encompassing charging scheme of fuel cells and electric cars (FCEVs/ EVs) that are utilized in renewable smart grids. The framework uses a multi-objective optimization process, which aligns charging policies through the intention of reducing peak load requirements and at the same time maximizing the exploitation of renewable sources of energy. The hybrid model combines the use of Distributed Energy Resource Management Systems and the vehicle-to-grid (V2G) technologies producing a decrease in the operational expenses by 27.3% compared to the uncoordinated charging systems. The simulation research undertaken on three urban distribution systems shows that the adaptive algorithm is able to handle penetration rate of 35 per cent EVs without the need to upgrade the infrastructure to realize a levelized reduction of 19.8 per cent EVs levelized charging costs. The sensitivity studies verify the stability of the model in a variety of renewable generation plans and electric vehicle adoption conditions, and thus create a technical basis of the sustainable electrification of transport in combination with renewable smart grids.