Abstract:

This work presents a model to empower an energy user to emerge as an EV-prosumer using vehicle-to-grid (V2G)/ vehicle-to-home (V2H) integration. The proposed algorithm uses an energy user's behavioural attributes ‘knowledge-gap’ and ‘risk-averseness’ to showcase the impact of EVs adoption on personal and societal benefits. Four types of energy users are defined and considered to model the problem based on their attitudes toward EV adoption. The first two energy user types, inactive and active consumers, are evaluated without EV integration. The other two energy user groups considered with EVs are Type I EV-prosumer with single EV and Type II EV-prosumer with multiple EVs, and the comparative analysis of their personal reward is discussed with them. Further, the impact of an EV prosumer’s emergence on societal benefits is discussed for two types of micro-grid (MG) settings: MG-I and MG-II. A mix-integer non-linear programming (MINLP) model is developed to optimize each type of energy user’s welfare for V2G/V2H interactions in MG-I and MG-II, respectively. The model results confirm that improvement in the awareness and risk-tolerance ability of an energy user's behaviour on EV adoption empowers them to emerge as a grid-independent entity during peak hours. Also, the objective function of an inactive user improves by 120%, 163%, and 147.6 % for an active, Type I EV-prosumer, and Type II EV-prosumer, respectively, with improvements in their behavioural parameters by 12.5%, 25%, and 27.5 %, correspondingly. The results show that the incremental welfare of Type I EV-prosumer is 63.5% higher than that of the active user, while for Type II EV-prosumer, it is as low as 25.2% than that of Type I EV-prosumer.