## 4 Results  
This section provides the results obtained for the considered operation scenarios. The main aim is to investigate the economic effects of the proposed charging strategy, the PV sizing and the PEV number penetration into the microgrid. The real time electricity prices of the first year are depicted in Figure 10. It is assumed that the electricity price deviates \(\pm\)5% every next year. Similarly, the PV production is assumed to deviate \(\pm\)3% every next year. Figure 11 depicts the Watt per installed PV kWp obtained from a PV installation of the examined area. Five scenarios were considered regarding the number of the PEVs that would charge at the microgrid: (a) 100 PEVs, (b) 300 PEVs, (c) 500 PEVs, (d) 20 PEVs with 15% increase of their number every year and (e) 20 PEVs with 15% increase of their number every year, and only one-third of the PEV drivers would accept to participate in V2G. Table 3 shows the NPV of the investment when the uncoordinated charging strategy is applied. The NPV is independent from the number of PEVs in this case as it examines the contribution only of the PV investment to the microgrid. Doubling the capacity of PV leads to a corresponding doubling of the NPV. The application of the proposed charging strategy can bring more profit to the microgrid as shown in Table 4. In particular, Table 4 summarizes the gains of the proposed charging strategy compared with the uncoordinated charging strategy when the PV is installed in the sport center at the end of investment period. The proposed algorithm is examined taking into consideration only the electricity price (s1) or the electricity price and the PV generation (s2). It can be observed that, as the number of the PEV increases, the profit is increasing as well. This happens because more PEVs participate in the V2G. More specifically, the energy can be sold back to the grid if there is a surplus of energy in the microgrid and the electricity price is high, or it can supply the microgrid. In this way, there is profit from selling the energy to the grid when the electricity price is high or the microgrid can reduce its demand during peak rates of the electricity price and subsequently increase its savings. Moreover, when s2 is applied the profits are increased more than 57%. It can be concluded that taking into consideration the electricity price and the PV generation could lead to better performance of the system. Furthermore, it can be observed that the profits in scenario e are almost 20% less than in scenario d even given the PEVs that were allowed to participate in V2G were one-third less in scenario e than in scenario d. This happened because Equation (1) should hold in order for a PEV to participate in V2G. Hence, a part of the PEV that was not allowed to participate in V2G in scenario e did not participate in V2G in scenario d either. Finally, in Table 5 can be observed the payback  
Figure 9: Microgrid layout. period (PP) for the different scenarios. As the PV capacity is being increased, the PP of the proposed charging strategies tends to be same as the uncoordinated charging. On the other hand, as the number of the PEV is being increased the PP of the proposed charging strategies tends to be reduced compared to the uncoordinated charging. The increase of the PV capacity increases also the initial investment cost. In addition, the increase of the PEV number increases the profit from the smart charging process. Hence, the greater the increase in the number of electric vehicles and the lower the initial investment are, the shorter the payback period will be and vice versa. Table 2 lists the input data of the optimization problem. Further than that, the PV degradation every year is considered 0.6% [28] and the efficiency of the DC/AC PV inverter is assumed to be 97.5%. Figure 11: Yearly Watt per installed PV kWp. Figure 10: Electricity price in the first year.