Exploration of Artifical Intelligence Approaches for the Integration of E-Mobility Energy Storage Systems into Virtual Power Plants

As a side effect to the mobility aspect, the steadily increasing proportion of electric vehicles provides a decentralized electrical storage network which can be used as an alternative to traditional central storage systems for buffering fluctuations in power generation and balancing the stability 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. To validate the developed methodology, the results of two metaheuristics are explored: Simulated Annealing (SA) and Particle Swarm optimization (PSO).