An Economic and Low-Carbon Co-optimization Method for Coupled Transportation and Power Distribution Networks

The growing penetration of electric vehicles (EVs) strengthens the interaction between the transportation network (TN) and power distribution network (PDN). The randomness of EV charging behavior brings both challenges and opportunities to the coupled network. The goals of cost reduction, efficiency enhancement, and low-carbon emission are expected to be achieved by optimizing the dispatch of traffic flow and power flow. The economy has been studied in the existing research, whereas, environmental protection is ignored. Thus, an economic and low-carbon scheduling problem (ELCP) is formulated to collaboratively optimize the economy and emissions. Specifically, the detailed models of the TN and PDN are formulated, respectively, then the coupling relationship can be clarified. Besides, a multi-objective optimization problem is proposed, whose objectives optimize the overall economy and emissions of the coupled network, respectively. Furthermore, a solution method that combines the epsilon-constraint algorithm with the extreme points of the feasible solution space is proposed to obtain various solutions. A fourteen-link/five-bus TN-PDN is applied to evaluate the proposed method. Simulation results show that the optimal traffic and power flow dispatch schemes can be obtained by solving the ELCP. At the compromise solution point, the economic cost can be reduced by 14.25%, while the corresponding carbon emission only increases by 4.02%.