Robust energy management for industrial microgrid considering charging and discharging pressure of electric vehicles

Shiliang Guo, Pengpeng Li, Kai Ma, Bo Yang and Jie Yang

Applied Energy, 2022, vol. 325, issue C, No S030626192201114X

Abstract: The growing number of electric vehicles (EVs) has resulted in increasing availability of battery storage capacities. The energy storage capacity of EVs is used to provide demand flexibility for the supply side. However, the different preferences of EV users will affect the charge and discharge decision of EVs. To overcome this problem, the concept of charging and discharging pressure is proposed to restrict the charging and discharging behavior of EVs. It is mainly dominated by the electricity price. Simultaneously, the charging and discharging time anxiety and state of charge (SoC) of EVs also affect the charging and discharging mode of EVs. This paper proposes a novel industrial microgrid (IMG) structure, which is mainly composed of power demand of industrial production, renewable energy sources (RES), energy storage systems (ESS), EVs and thermal power generation units. The aim of the proposed model is to minimize the operation cost of IMG and maximize the income of EV users. For the management of demand side, the strategy of time of use (ToU) price is adopted. In addition, considering the uncertainty of RES and industrial load, a robust optimization algorithm is proposed, and the operation of IMG under different uncertain scenarios is analyzed. Finally, the robust mixed integer quadratic programming (MIQP) of IMG is studied. The detailed simulation and comparison results verify the effectiveness of the proposed energy system under different charging and discharging pressures based on EVs.

Keywords: Electric vehicles; Charging and discharging pressure; Industrial microgrid; Robust optimization; Energy management (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (11)

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DOI: 10.1016/j.apenergy.2022.119846

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