Hierarchical planning of PEV charging facilities and DGs under transportation-power network couplings

Abstract

The increasing penetration level of plug-in electric vehicles (PEVs), as well as distributed generators (DGs), imposes significant challenges on power system planning. This work presents a coordinated approach for the planning of PEV charging facilities and DGs, including both the locations and the capacities, with the consideration of the transportation - power network couplings. First, the PEV charging demand is characterized by a temporal-SoC (State of Charge) analysis, and the DG generation uncertainties are modeled by K-means clustering using historical data. The M/M/s/N queuing model is used to formulate the dynamics of charging stations and then obtain the optimal station capacity, including the number of chargers and waiting spaces. Furthermore, the placement of charging stations is optimized by the Floyd Algorithm to minimize the total distance to obtain charging service. Finally, the sitting and sizing of DGs are optimized over multiple objectives, including active power losses, reactive power losses, and voltage deviation. The solution is evaluated through a case study of the IEEE 53-bus test feeder coupled with a 25-node transportation network. It is shown that the proposed solution enables the active and reactive power losses as well as the voltage deviation to be reduced by 37.6%, 44.3%, and 33.6%, respectively, after the optimal integration of PEV charging stations and DGs. The scalability and effectiveness of the solution are further validated in an IEEE 123-bus test feeder coupled with the same transportation network, and the result confirms the effectiveness and scalability of the proposed solution.