Abstract:

The growing proportion of electric vehicles, as a side effect of the mobility factor, provides a decentralized electric storage network that can be used as an alternative to traditional central storage systems for buffering fluctuations in power generation and balancing the reliability of the power grid. The systematic optimization of such energy-technical scenarios towards multiple objectives provides a complex optimization problem, which is addressed in this paper by using mechanisms of Artificial Intelligence (AI). A methodology for an optimized energy exchange between a network of e-mobility energy storages (ES) and a virtual power plant (VPP) will be presented, which improves the stability of the power grid and at the same time charges the storage systems of the electric vehicles for their further use. The results of two metaheuristics -- Simulated Annealing (SA) and Particle Swarm Optimization (PSO)--are examined in order to validate the established methodology.