Probabilistic planning of electric vehicles charging stations in an integrated electricity-transport system

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Aghapour, R (Author) Other; Sepasian, MS (Author) Other; Arasteh, H (Author) Other; Vahidinasab, V (Author) Other; Catalao, JPS (Author) FEUP

Journal

Title: Electric Power Systems Research

Vol. 189

ISSN: 0378-7796

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 20 Citations

Scopus - 32 Citations

Other information

Authenticus ID: P-00S-JYS

DOI: 10.1016/j.epsr.2020.106698

Abstract (EN): One of the most important aspects of the development of Electric Vehicles (EVs) is the optimal sizing and allocation of charging stations. Due to the interactions between the electricity and transportation systems, the key features of these systems (such as traffic network characteristics, charging demands and power system constraints) should be taken into account for the optimal planning. This paper addressed the optimal sizing and allocation of the fast-charging stations in a distribution network. The traffic flow of EVs is modeled using the User Equilibrium-based Traffic Assignment Model (UETAM). Moreover, a stochastic framework is developed based on the Queuing Theory (QT) to model the load levels (EVs' charging demand). The objective function of the problem is to minimize the annual investment cost, as well as the energy losses that are optimized through chance-constrained programming. The probabilistic aspects of the proposed problem are modeled by using the point estimation method and Gram-Charlier expansion. Furthermore, the probabilistic dominance criteria are employed in order to compare the uncertain alternatives. Finally, the simulation results are provided for both the distribution and traffic systems to illustrate the performance of the proposed problem.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8