Modelling the agents of electro mobility In this section, we provide an overview of the proposed methodology, focusing on the system modelling and, in particular, on the interactions between the agents. In section 2.3.2 we present a brief game theoretic analysis of the system and in section 2.3.3 we present in detail the relevant mathematical formulation. We consider a set of decision makers which includes the EV consumers, the private sector investors, the policy maker and the DSO. Our modelling does not aim to simulate the agents’ decision making in full detail; the methodology is focused on the part of the decision making of agents that is relevant to our study, effectively ‘’projecting’’ the agents’ decision making onto the ‘’space’’ of electro-mobility. This way we circumvent the difficulty of providing an unnecessarily complex modelling of the agents’ behaviour as we reduce the latter to a set of conditions that can be efficiently formulated as an equilibrium problem with equilibrium constraints. In what follows, we elaborate on how we model behaviour of each agent: The private investors generally allocate their capital on investing options trying to maximize the overall returns while minimizing the investment risks and considering the opportunity costs. In this particular problem (i.e. investing in charging infrastructure), we utilize the internal rate of return (IRR) criterion to model whether the private investor will engage in the investment or not. We assume a decision threshold which represents an estimation of the opportunity cost incurred to the investor by the former choice, i.e. it represents a rate of return that the investor could achieve by investing in other choices. If the IRR of recharging infrastructure investments is below that threshold, the investor has no incentive to invest. The modelling considers only the case of fast charging points and assumes exogenously that a specific part of the electricity needs is provided by other types of charging points. The price of charging services comprises of the electricity price and the tariff for recovering the capital cost of the investment. The former is exogenous to the modelling and is provided by the PRIMES energy systems model. The latter is endogenously calculated based on the utilisation of the charging points assuming that the tariff is calculated using the levelized cost approach. The overall price of the charging service is capped to an upper limit and thus, considered being regulated. We carry out sensitivity...
