## 6 Grid Impact
### Smart Charging/Charge Management and Location
In the case of all impacts on a grid being controlled (power demand optimization, minimum voltage deviation, ensuring smooth load peaks, avoiding significant transformer impact, maximizing the grid load factor, maximum utilization of RES, and minimization of energy losses), one study indicates that the voltage deviation in a residential distribution network could be less than 10% for EV penetration of 30%. To reduce EV impact, smart chargers containing advanced control electronic converters must be used [125]. Uncontrolled EV charging shows investment increases in generation and transmission infrastructure as well as in operation, which can be avoided using smart charging strategies that balance the network and avoid peaks. Smart charging involves power and information transmission (SoC, voltage, current, and time to full charge). In the event that charging is unidirectional, control strategies can be used to manage the reactive power with current phase-angle control, maximizing the benefits for both aggregators and clients [126; 127]. In relation to energy losses and investment costs, energy losses could increase by up to 40% in off-peak hours for a penetration up to 60% of PEVs, and up to 15% of the total actual distribution network costs would need to be invested depending on the charging strategy [125]. Figure 20: Main elements of an electric network in the context of EV charging. In an ideal model simulation, for a certain level of PEV loads, if they are fully controllable then the invoiced costs would not be increased, while even 10% non-controlled lower penetrations could increase charging costs by up to 22% [128]. Similar data obtained from other studies demonstrate the network stress produced by uncontrolled EV charging, which generates higher infrastructure costs, indicating that 60-70% of these could be eliminated if charging was carried out in a controlled way. Different authors divide the charging process into centralized and decentralized strategies. In the former, EV charging is programmed through a controller located in the charging station or in the aggregator. The variables managed are the SoC, grid situation, and electricity prices. This strategy optimizes charging for large EV penetration, a necessary requirement for the existence of aggregators. The decentralized strategy leaves the charging schedule in the hands of the owner, making it more fault-tolerant, less technically complex, and easier to scale [129]. Other more recent works explain the same concepts in greater detail, referring to them as uncoordinated or coordinated strategies. In the first case, the user decides to make a \"direct\" or \"delayed\" charge. In the \"direct\" case, the EV is charged when desired until it reaches a certain battery level, then is disconnected. In the \"delayed\" case, the EV connection is delayed to favorable periods when the network is not as saturated. Coordinated strategies use optimization, scheduling, and pricing techniques belonging to the same transformer, and can be continuous or discrete. Uncoordinated strategies refer to a charging period during which an EV is continually charged without interruption. In discrete techniques, on the other hand, the charging period is divided into a number of intervals, with the system deciding whether to charge a certain vehicle or if it is better to charge another. The advantages of these strategies increase when working with networks that allow V2 GHV, although the strategies increase in complexity as well. Studies have shown that coordinated smart charging is much more efficient than uncoordinated charging [130]. In the case of bidirectional cables (V2G or V2H) [131; 132] or wireless [133] charging, cost increases for the customer are involved due to degradation of the batteries, more expensive power electronics (inverters and converters), metering, and control.