Optimal Economic-Emission Scheduling of Coupled Transportation and Power Distribution Networks With Multi-Objective Optimization

The growing penetration of electric vehicles (EVs) strengthens the interaction between the transportation network (TN) and the power distribution network (PDN). Such interaction brings opportunities for reducing consumption and emissions, while creating challenges for collaborative scheduling. This paper presents a multi-objective optimization strategy, which is formulated to optimize the economy and emissions of the coupled networks in a way that the optimal operations of TN and PDN are guaranteed simultaneously. Specifically, the detailed models of TN comprised of EVs and gasoline vehicles (GVs), and PDN, respectively, are formulated; thus, the coupling relationship can be clarified. Since two objectives compete with each other, an economic and low-carbon scheduling problem (ELCP) is proposed based on the Pareto efficiency theory. To facilitate the model's tractability, several approximation and relaxation methods are exploited to derive a mixed-integer quadratic problem (MIQP). Furthermore, a co-optimization method that combines the epsilon-constraint algorithm is developed to transform the multi-objective problem into its equivalent single-objective problem for obtaining scheduling results. Finally, two test systems are examined to evaluate the effectiveness of the proposed method, and numerical results demonstrate that the economic cost and emissions are effectively balanced.