Open AccessLogistics system planning for battery-powered electric vehicle charging station networks
Author(s) -
Hassan S. Hayajneh,
Muath Bani Salim,
Srikanth Bashetty,
Xuewei Zhang
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1311/1/012025
Subject(s) - truck , software deployment , renewable energy , charging station , battery (electricity) , grid , electric vehicle , profitability index , energy storage , automotive engineering , transport engineering , computer science , engineering , electrical engineering , power (physics) , business , physics , geometry , mathematics , finance , quantum mechanics , operating system
This work proposes a promising scenario of large-scale deployment of battery-powered electric vehicle charging station networks that attempts to address three important issues toward a sustainable energy landscape in the near future: (1) Suppressed grid integration of variable renewable generations such as wind; (2) Low profitability of battery energy storage systems due to limited applications; and (3) Conflicts between the current power infrastructure and the installation of charging stations to meet the growing needs of electrical transportation. More specifically, we design a system in which electric trucks deliver large-volume batteries to electric vehicle charging stations. This facilitates the planning and operation of electric vehicle charging station networks without constraints from the grid. In regions where there are abundant renewable energy sources and the road networks do not suffer from frequent congestion, this could be a viable solution. Using the city of Corpus Christi, Texas (USA) and the nearby Chapman Ranch wind farm as a test case, we formulate the design problem based on the logistics system models and obtain the optimal sizes of charging station batteries and number of electric trucks to minimize cost. The obtained results can help potential stakeholders make business decisions or policy recommendations.