Two-Layer Iterative Sizing for Logistics Centers Equipped With Fast Charging Stations

The rapid transportation electrification requires efficient integration of fast charging stations (FCSs) in logistic centers to support the electric vehicles (EVs) demand. Energy storage and solar PV should be further integrated to reduce the stress on the grid. This paper proposes a two-layer iterative sizing method for logistic centers integrated with FCSs, energy storage systems (ESSs), and solar PV considering the participation in the Nordic electricity and balancing market. First, a two-layer iterative method is proposed where the operation layer aims to minimize the operation cost, the planning layer aims to minimize the investment cost of ESS, solar PV, fast chargers, and waiting spaces. A natural aggregation algorithm is deployed to address the nonlinear constraints posed by the M/M/s/N queue model, which characterizes the charging behaviors of EVs. The stochastic weighted robust optimization (SWRO) method is employed to deal with the uncertainties of EV demand, PV generation, and the basic loads of logistics centers, considering the interaction between sizing and scheduling. Case studies for a logistic center in Stockholm are conducted to demonstrate the effectiveness of the proposed solution.