Behavioural modelling for personal and societal benefits of V2G/V2H integration on EV adoption

• ‘Risk-averseness’ and ‘knowledge-gap’ are modelled as dominant behavioural factors for slow EV-adoption. • Behavioural modelling for energy users ‘personal and societal payoff of V2G/V2H integration is performed. • An MINLP optimization problem is used to maximize the total welfare for uniformly distributed behavioural parameters of energy users. • The impact of EV adoption is discussed for two types of micro-grid (MGs) settings, namely: MG-I and MG-II. • A GHG mapping formulation is introduced to evaluate of EV-prosumer’s contribution to the environmental payoff. • EV-prosumer has the potential to substitute the scheduling of a power-producing entity at peak-hours. The prevailing knowledge-value-intention-action gaps on personal and societal benefits of electric vehicle (EV), challenges an energy user’s ability from its wider adoption. 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 categories of energy users are defined and considered to model the problem as per their behavioural outlook on EV adoption. The first two energy user categories inactive and active consumers are considered without EV integration. And, the comparative analysis of their personal payoff is discussed with the another two energy user categories considered with EVs: Type I EV-prosumer with single EV, and Type II EV-prosumer with multiple EVs. 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 the 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.