Expansion Planning of Urban Electrified Transportation Networks: A Mixed-Integer Convex Programming Approach

Abstract

Electric vehicles (EVs) have been widely acknowledged as one effective solution to alleviate the fossil fuel shortage and environmental pressure in modern metropolises. To foster the large-scale integration of EVs, transportation electrification is becoming an emerging trend. This paper proposes a comprehensive model for the expansion planning of urban electrified transportation networks (ETNs), which determines the best investment strategies for the TN and the power distribution network (PDN) simultaneously, including the sites and sizes of new lanes, charging facilities, distribution lines, and local generators. The steady-state distribution of traffic flow in the TN is characterized by the Nesterov user equilibrium (NUE). The operating condition of the PDN is described by linearized branch power flow equations. To consider the interdependency between the TN and PDN created by the charging behavior of EVs, the power demand of on-road charging facility is assumed to be proportional to the traffic flow it carries. The expansion planning model is formulated as a mixed-integer nonlinear program with NUE constraints. In order to retrieve a global optimal solution, it is further transformed into an equivalent mixed-integer convex program through duality theory and techniques of integer algebra; no approximation error is involved. Case studies on a test ETN corroborate the proposed model and method.