Optimal Design of Energy Storage System to Buffer Charging Infrastructure in Smart Cities

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

20 Scopus Citations
View graph of relations



Original languageEnglish
Article number04019048
Journal / PublicationJournal of Management in Engineering
Issue number2
Online published5 Dec 2019
Publication statusPublished - Mar 2020


A parallel trend of vehicle automation and electrification represents smart mobility in smart cities. Dramatic growth of electric vehicles (EVs) on roads is projected in the next decade. The pivotal challenge to infrastructure is how to fill the charging-capacity gap for the increased number of EVs. The challenge is twofold: one is the energy gap in charging stations due to peak demands, and the other is shortage of charging infrastructure owing to high construction costs. As an emerging solution, energy storage technology provides stable and reliable electricity buffers during peak hours; however, it is unknown how to effectively integrate energy storage to charging stations while obtaining the lowest cost. The objective of this paper is to develop a simulation model that determines the optimal design of the energy storage system (ESS) for a given network of charging stations. The model is made novel by integrating the charging station network and energy storage system as a whole. The optimal ESS design informs the configuration and distribution of battery type, size, amount, and location. A case study of the Detroit area in Michigan indicates the model is robust and provides efficient decision support for planners, designers, and engineers to construct energy storage systems. Strategies retrieved from the case suggest large-sized batteries and microgrids for cross-station energy exchange, which leads to a potential 20%-36% of cost savings for energy storage development.

Research Area(s)

  • Battery storage, Charging stations, Construction management, Electric vehicle, Monte Carlo, Network optimization, Smart mobility