Integrated Scheduling Strategy for Private Electric Vehicles and Electric Taxis

Abstract

Private electric vehicles (PREVs) and electric taxis (ETs) are two of the most common electric vehicles (EVs) in the cities. It is important to regulate the charging load file of PREVs and ETs, which has a significant impact on the power grid. Most of the existing works optimize the charging load profiles of PREVs and ETs separately since their charging behaviors are different. However, the separated optimization methods may not find out the optimal profile of the total charging load. To address this problem, in this article, we propose a two-stage integrated scheduling strategy, which can achieve a desired load profile of PREVs and ETs. In the first stage, according to the charging models of PREVs and ETs, we formulate an integrated optimization problem to determine the optimal feasible total load profile and the respective optimal load profiles of PREVs and ETs. In the second stage, we formulate two 0–1 optimization problems, respectively, which aim to select PREVs and ETs in the most need of charge to track the reference load fed from the first stage. We propose a generic algorithm to solve the two problems, which has fast convergence speed and requires low data size of communication. Finally, the simulation results validate the effectiveness of the proposed algorithm. Moreover, we demonstrate that proposed integrated scheduling strategy performs better than the separated scheduling strategies.