An energy management strategy with renewable energy and energy storage system for a large electric vehicle charging station

Desheng Li, Adama Zouma, Jian Tang Liao, Hong Tzer Yang

Research output: Contribution to journalArticlepeer-review

39 Citations (Scopus)


With the increase in the use of electric vehicles, charging stations may have congestion problems. The grid energy storage system can be used to satisfy the energy demand for charging electric vehicles batteries. Electric vehicles charging/discharging scheduling for vehicle-to-grid and grid-to-vehicle operations is challenging because customers have different energy requirements. Here, a charging and discharging power scheduling algorithm solved by a chance constrained programming method was applied to an electric vehicle charging station which contains maximal 500 charging piles, an 100kW/500 kWh energy storage system, and a 400 kWp photovoltaic system. Accordingly, the power dispatch can be beneficial to the charging station and electric vehicle users under the possible impact of the generation uncertainty of PV. The time-of-use adjustment method is proposed integrated with the charging/discharging priorities calculation and electricity prices, which ensures the energy usage does not exceed contract capacity. Based on the proposed algorithm, a blueprint for optimizing the contract capacity is analyzed for improving the cost of charging stations. The results indicate that the cost of electric vehicles charging can be decreased almost by 50% in a certain confidence level of photovoltaic forecasting comparing with uncoordinated method. The proposed method can assist charging station operators to evaluate suitable contract capacity and implement power dispatch strategies based on the possible scale of electric vehicles and distributed energy resources, which is conducive to the development of the power and EV industry.

Original languageEnglish
Article number100076
Publication statusPublished - 2020 Nov

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology
  • Transportation


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