Multi-objective Charging and Discharging Optimization of Electric Vehicles in Time-divided period Based on SOC Evolution

Title:Multi-objective Charging and Discharging Optimization of Electric Vehicles in Time-divided period Based on SOC Evolution

Volume: 13 Issue: 4

Author(s): Ying Wang, Gang Ma*, Yixi Chen, Jian Zhang and Jiashu Wang

Affiliation:

• School of NARI Electric and Automation Engineering, Nanjing Normal University, Nanjing,China

Keywords: Electric vehicle, charge and discharge optimization, SOC evolution, time-divided, MPSO, EV technology.

Abstract:

Background: With the increase of Electric Vehicle (EV), their disordered charging behaviour will put great pressure on the stable operation of the distribution network.

Methods: In order to study the charging and discharging optimization scheme of EVs, firstly the EV charging and discharging load model is founded based on the Vehicle-to-Grid (V2G) technology.

Results: According to the electricity price mechanism of Shanxi Province, the paper proposes a multi-target charging and discharging optimization for EVs based on the evolution of EV State of Charge (SOC) using the Modified Particle Swarm Optimization (MPSO).

Conclusion: Compared with the disordered charging mode, the method proposed in this paper can simultaneously reduce the network loss of the distribution network and the cost of EV users.

Cite this article as:

Wang Ying , Ma Gang *, Chen Yixi , Zhang Jian and Wang Jiashu, Multi-objective Charging and Discharging Optimization of Electric Vehicles in Time-divided period Based on SOC Evolution, Recent Advances in Electrical & Electronic Engineering 2020; 13 (4) . https://dx.doi.org/10.2174/2352096512666190911144557

DOI https://dx.doi.org/10.2174/2352096512666190911144557	Print ISSN 2352-0965
Publisher Name Bentham Science Publisher	Online ISSN 2352-0973