**1. Introduction**

The dynamic technological development of electric vehicles (EV) and different support instruments introduced in various countries according to EU directives encourage individual customers to invest in EVs. The goal of the European Union is to reduce the greenhouse gas emissions into the atmosphere by 2050 by 60% compared to 1990. One of the assumptions to achieve the above objective is halving the number of vehicles with conventional drive in the urban transport by 2030 and total elimination of such vehicles from cities by 2050 [1].

There are three main types of EVs available on the market: hybrid vehicles (HEV), hybrid vehicles with the possibility of charging a battery pack (PHEV) and fully electric vehicles (BEV) [2,3]. The BEV vehicles are the subject of this paper. Due to the high energy density, reasonable battery life and acceptable recharging speed the lithium-ion batteries are used to power this type of vehicle [4].

The increasing number of EVs may bring a significant impact on the supply network. The most negative aspect for the network is an uncontrolled EV charging process, especially if it takes place during a time overlapping with high power demand. The increase of peak load due to mass charging may lead to branch congestion and large voltage drops. This problem is described in the literature. The assessment framework of a plug-in electric vehicles (PEV) impact on the supplying network is proposed in [5] taking into account the great uncertainty in many crucial assumptions and parameters (e.g., EV battery charging power and time). In [6,7] the rating of electricity demand profile is assessed on the basis of information about EV user behaviors. Furthermore, in [8] the diagrams of medium voltage (MV) network loading are presented for a scenario where 52% of all used cars are EVs. It is shown that dump charging can cause peak a power increase by about 100% and controllable charging is necessary to avoid network disruptions. Similarly, in [9,10] the impact of the increased number of EVs on the operation of low voltage (LV) power network by both controlled and uncontrolled EVs

charging is analyzed. Different charging strategies are tested and compared in [11–13]. The concept of using renewables, in particular the solar panels, in charging infrastructure is discussed in [14].

The impact of EVs on the supply network significantly depends on EV user behaviors. If EV is used for commercial purposes or to travel for longer distances, it requires the infrastructure of fast and superfast chargers. In that case the location of charging points must be based on factors such as EV ranges, road infrastructure, investment costs, etc. In certain cases, there will be a need to reinforce a supply network and so the planning is crucial to minimize additional costs. The methodology for planning minimal fast charging infrastructure deployment is evaluated and depicted in [15].

If the user exploits EV on relatively short distances, for example for commuting, the EV can be charged at home in the evening. At present this is the most typical scenario and it will be discussed further. While the EV is connected to the home electrical installation, the energy stored in EV battery can be used to support the installation operation and improve the reliability of supply. Such an EV service, called the vehicle-to-home (V2H), is especially useful in the case of supply network failure or when the EV user wants to reduce energy costs by using an EV battery to supply loads in the period of high energy prices.

Benefits from using EV for additional services have already been indicated in the literature [16]. It is shown that through demand side management (DSM) the V2H may support the local loads during severe supply network loading or outages, hence alleviating energy demand on the network and its reliability requirements. In [17] an active management model integrated with generation curtailment mechanism and the charging/discharging management of plug-in EVs was built for the local distribution system. In [18–20] PEVs are used for the backup power during an outage and on the basis of residential energy usage data, the duration of backup power that could be achieved is identified. Similarly, in [21,22] EVs are used as energy storage for a local smart grid to reduce energy costs. In [23] the exploitation of vehicle-to-grid (V2G) services for power quality improvement is discussed. The optimal charge/discharge schedule for an EV plugged into a smart building is presented in [24,25] taking into account time-varying electricity pricing schemes.

At present the V2H and V2G services require an off-board bi-directional inverter which generate high additional costs. In addition, the size of such an inverter is not without significance, especially in the context of limited space in garages or parking lots. In this paper, authors analyze the usage of an on-board motor inverter (instead of off-board) for V2H services. It means that the motor inverter is used for both: motor propulsion and ancillary (V2G/V2H) services. Different approaches to the adaptation of motor converters for the ancillary services are available in the literature. The review of the drivelines in all-electric vehicles is presented in [26]. The topology of an on-board integrated battery charger using an asymmetrical nine-phase machine is described in [27]. In [28], a single-phase integrated charger, using the EV propulsion machine and its traction converter, is introduced.

The presented literature concentrates on indicating the possible benefits of the V2H services for EV users and the supplying network operators. However, to implement the additional functionalities of EV some technical issues should be examined including the control of EV motor inverter. In this paper the authors present an original simulation model, which can be a useful tool for both: the examination of EV motor inverter for V2H services and for the adaptation of home installation for such services.

The paper is arranged as follows. In Section 2 the EV user behavior scenarios are identified to justify the possibilities and significance of EV additional functionalities. Then in Section 3 we describe the simulation model. In the next Section, we present the simulation results for the chosen case study. The paper finishes with some conclusions.
