GIS-Based Multi-Objective Particle Swarm Optimization of Charging Station of Electric Vehicles – Taking a District in Beijing as an Example

Zhang Yue (1) , Arash Farnoosh (2, 3) , Qi Zang (1) , Siyuan Chen (1)

1 China University of Petroleum
2 IFPEN - IFP Energies nouvelles
3 IFP School

The rapid development of electric vehicles can greatly alleviate the environmental problems and energy tension. However, the lack of public supporting facilities has become the biggest problem hinders its development. How to reasonably plan the construction of charging facilities to meet the needs of electric vehicles has become an urgent situation in China. Different from other charging facilities, charging station could help to break the limitation of driving distance. It also has a special dual attribute of public service and high investment. So, this paper establishes a model with two objective functions of minimizing construction cost and maximizing its coverage and Particle Swarm Optimization was used to solve it. Besides, we take into account the conveniences of stations to charging vehicles and their influences on the loads of the power grid and GIS is used to overlay the traffic system diagram on power system diagram to find the alternative construction points. In this study, a district in Beijing is analyzed using the method and model we proposed. Finally, a planning strategy of charging station for Chinese market is suggested

Mots clés: Electric vehicle; Charging station; Multi-objective particle swarm optimization; GIS

Domaines: Sciences de l'Homme et Société; Economies et finances

Zhang Yue, Arash Farnoosh, Qi Zang, Siyuan Chen. GIS-Based Multi-Objective Particle Swarm Optimization of Charging Station of Electric Vehicles – Taking a District in Beijing as an Example: Cahiers de l'Economie, Série Recherche, n° 118. 2018. ⟨hal-03187920⟩