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, the authors 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, the authors formulate an integrated optimization problem to determine the optimal feasible total load profile and the respective optimal load profiles of PREVs and ETs. This study formulates two 0-1 optimization problems in the second stage, with the goal of selecting the most in need of charge PREVs and ETs to monitor the reference load fed from the first stage. This research proposes a generic algorithm to solve the two problems that is quick to convergence and needs little communication data. Finally, the simulation results show that the proposed algorithm is successful. Moreover, this study demonstrates that proposed integrated scheduling strategy performs better than the separated scheduling strategies.