Optimal Allocation of Plug-in Electric Vehicle Parking Lots for Maximum Serviceability and Profit in the coupled distribution and transportation networks

Abstract

Optimal planning and management of electric vehicle parking lots (EVPLs) can be an effective approach for improving the operation of both the distribution system and traffic networks. However, the limited land areas of cities can be an obstacle for constructing a large number of parking lots (PLs). This paper proposed a model for optimal siting and sizing of EVPLs as well as their charging schedule to maximize the total profit of their owners, while maximum parking demand of plug-in electric vehicles (PEVs) can be satisfied. In the proposed model, the purpose of trips, number of PEVs, plus their arrival and departure time in different urban areas are considered. Distribution network constraints are also taken into account using linearized load flow equations. The proposed model is implemented in a 37-bus distribution system coupled with a 25-node transportation network which includes four different areas in terms of PEV travel type. The simulation results show the effectiveness of the proposed model to cover the parking demand of PEVs with a limited number of PLs.

New optimal planning strategy for plug‐in electric vehicles charging stations in a coupled power and transportation network

“…Also, the variable cost and the maximum number of chargers that need to be installed at any point in the transportation network are in accordance with Table 3. We have used some values and information of reference [50] for this table as the case study.…”

“…The selected case study for this research is the IEEE standard 37-bus distribution networks, which are coupled with the 25-node transportation network [50]. The information of the standard IEEE 37-bus network is given in [51].…”

“…Also, the variable cost and the maximum number of chargers that need to be installed at any point in the transportation network are in accordance with Table 3. We have used some values and information of reference [50] for this table as the case study. According to the transportation network data, using the Floyd-Warshall algorithm, which is mentioned in Table 1, it is possible to calculate the shortest distance between two nodes in the transportation network.…”