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<p>This paper proposes building energy management systems (BEMS) to coordinate charging loads of electric vehicles (EVs) in residential premises using different electricity tariffs of real-time prices (RTP), time of use (ToU) tariffs, and critical peak prices (CPP). The tariffs are empirically synthesized to maintain fairness in calculating operational costs using these categories of electricity prices. Accordingly, identical operational costs are recorded using all of these tariffs for similar amounts of energy consumption. Subsequently, the tariffs are utilized to formulate objective functions aimed at decreasing operational costs of EV charging loads, considering distributed linear programming techniques. Simulation results show that the use of RTP, ToU and CPP tariffs is able to reduce operational costs of EV charging loads by 11%, 15% and 25%, respectively, while maintaining the state of charge (SoC) of EV batteries between 80 and 90%. The methodology proposed in this paper shows that RTP tariffs are appropriate for valley-filling methods of demand-side management (DSM) schemes. Meanwhile, ToU and CPP tariffs can implement peak shaving and load shedding strategies for DSM systems. Moreover, the BEMS proposed in this paper is studied in terms of seasonality, price elasticity, and high EV uptake to show their effects on charging EVs, while designing different electricity tariffs. Such methodological identification of using different electricity tariffs has the capability to integrate DSM schemes into building codes, achieving sustainable environmental benefits.</p>

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Building energy management systems of charging electric vehicles using different electricity tariffs

  • 期刊论文

  • 发表日期：

    2025年11月24日

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  • Mohammed Jasim M. Al Essa

摘要

This paper proposes building energy management systems (BEMS) to coordinate charging loads of electric vehicles (EVs) in residential premises using different electricity tariffs of real-time prices (RTP), time of use (ToU) tariffs, and critical peak prices (CPP). The tariffs are empirically synthesized to maintain fairness in calculating operational costs using these categories of electricity prices. Accordingly, identical operational costs are recorded using all of these tariffs for similar amounts of energy consumption. Subsequently, the tariffs are utilized to formulate objective functions aimed at decreasing operational costs of EV charging loads, considering distributed linear programming techniques. Simulation results show that the use of RTP, ToU and CPP tariffs is able to reduce operational costs of EV charging loads by 11%, 15% and 25%, respectively, while maintaining the state of charge (SoC) of EV batteries between 80 and 90%. The methodology proposed in this paper shows that RTP tariffs are appropriate for valley-filling methods of demand-side management (DSM) schemes. Meanwhile, ToU and CPP tariffs can implement peak shaving and load shedding strategies for DSM systems. Moreover, the BEMS proposed in this paper is studied in terms of seasonality, price elasticity, and high EV uptake to show their effects on charging EVs, while designing different electricity tariffs. Such methodological identification of using different electricity tariffs has the capability to integrate DSM schemes into building codes, achieving sustainable environmental benefits.