A Multi-Agent System for the Dynamic Emplacement of Electric Vehicle Charging Stations

Abstract

Abstract:One of the main current challenges of electric vehicles (EVs) is the creation of a reliable, accessible and comfortable charging infrastructure for citizens in order to enhance demand. In this paper, a multi-agent system (MAS) is proposed to facilitate the analysis of different placement configurations for EV charging stations. The proposed MAS integrates information from heterogeneous data sources as a starting point to characterize the areas where charging stations could potentially be placed. Through a genetic algorithm, the MAS is able to analyze a large number of possible configurations, taking into account a set of criteria to be optimized. Finally, the MAS returns a configuration with the areas of the city that are considered most appropriate for the establishment of charging stations according to the specified criteria.

Multi-Agent Systems

“…Additionally, a statistical analysis has been performed in order to show the differences in their performance and to determine the relevance of results. The second approach presented in this Special Issue regarding smart cities is the work done in [33], where a multi-agent system was proposed, in order to facilitate the analysis of different possible placement configurations for electric vehicles charging stations in a city. The MAS proposed in this paper integrates the information extracted from heterogeneous data sources as a starting point to specify the areas where future charging stations could potentially be placed.…”

Special Issue “Multi-Agent Systems”: Editorial

“…In [14] the authors apply multi-agent based modelling to the domain of urban planning, in particular, for supporting decision making about the design and deployment of an electric charging stations infrastructure in a city. The proposed multi-agent system features several agents in charge of complementary functionalities, such as querying open data portals of local administrations to gather info about potential offer and demand for charging stations as well as average traffic conditions, crawling social networks to rank potential locations where to put charging stations, and execute optimisation algorithms to find the best spots among a set of candidates.…”

Optimal Control Strategy to Maximize the Performance of Hybrid Energy Storage System for Electric Vehicle Considering Topography Information

“…The needs to reduce air pollution and harmful emissions by conventional vehicles have promoted the development of electric vehicles (EVs). EVs remain to face issues that need to be resolved [1][2][3]. Batteries are among the most common energy storage devices, and they represent a large promise for clean energy [4].…”