*5.3. PV Matching Panels*/*Inverters*

The car park has 114 parking spaces. The maximum number of shelters will therefore be 57 for a total of 513 PV panels to be installed. The maximum peak power of the generation plant will therefore be equal to 200 kWp. The plant was divided into three inverters of equal size, each with a rated power of 70 kW. 171 PV panels will be connected to each inverter, which are divided into 10 parallel strings. 9 strings consist of 17 panels in series and the 10th consists of 18 panels. Table 3 presents a summary table of these data. It proceeds with the verification of correct matching string/inverter, considering the limit temperatures of +70 ◦C and −10 ◦C. The conditions are summarized in Table 3 as well.



In particular:

$$N\_{\rm MPP,min,STR} = N\_{\rm pounds} \cdot \left[ V\_{\rm MPP} (25 \, ^\circ \text{C}) + (70 \, ^\circ \text{C} - 25 \, ^\circ \text{C}) \cdot \Delta V\_T \right] \tag{4}$$

$$N\_{MP,MAX,STR} = N\_{pounds} \cdot \left[ V\_{MPP} (25 \, ^\circ \text{C}) + (-10 \, ^\circ \text{C} - 25 \, ^\circ \text{C}) \cdot \Delta V\_T \right] \tag{5}$$

*Energies* **2020**, *13*, 3083

$$V\_{\rm OC,STR} = N\_{\rm panels} \cdot \left[ V\_{\rm OC} (25 \, ^\circ \text{C}) + (-10 \, ^\circ \text{C} - 25 \, ^\circ \text{C}) \cdot \Delta V\_T \right] \tag{6}$$

Therefore, after all the calculations are completed, the matching conditions are verified and are as reported in Table 4.


**Table 4.** String/inverter matching conditions and calculations.

### *5.4. Producibility of the Designed PV Plant*

Once the system is dimensioned, it is possible to evaluate the producibility, that is, the energy that this plant is able to generate in the calendar year. We have seen that the power generated by a single panel is given by Equation (2), which does not take into account any loss factors. Thus, in order to evaluate the actual power generated, Equation (7) must be considered:

$$\begin{aligned} P\_{\text{out}} &= \eta \cdot \mathcal{N}\_{\text{pounds}} \cdot P\_{\text{out,puel}}(G\_l) \\ \eta &= \eta\_{\text{el}} \cdot \eta\_{\text{Mis} \text{stchling}} \end{aligned} \tag{7}$$

where

> η*el*: a factor including all electrical losses (cables, inverters, etc.);

η*Mismatching*: a corrective factor affecting the output power of the panels due to various causes, including the difference in thermal gradient of the modules, different shading of the modules for passing clouds, accumulation of dirt, intrinsic differences of the modules, etc.

A correction factor η = 0.85 was assumed for this project. Figure 14 presents an estimate of the power supplied and the relative energy that can be produced by the PV plant.

(**a**) **Figure 14.** *Cont.*

**Figure 14.** (**a**) Daily output power of the photovoltaic (PV) plant month by month and (**b**) overall monthly producibility of the PV plant.

### **6. Smart Charging of the Electric Vehicles**

A possible algorithm for optimizing the charging process of EVs is presented. As discussed earlier in this study, the implementation of the smart charge for EVs is mandatory in order to avoid situations of dangerous overloads in the distribution network. However, the managemen<sup>t</sup> of energy flows is only possible in a mature context that has a reliable and stable smart grid. In the following paragraph, two separate optimization algorithms, which exploit two different principles, are proposed:

"Green" algorithm: the first algorithm proposed is based on a very simple principle. Given the presence of a photovoltaic system on the site of interest, the charging of the EVs is entrusted only to this last resource. That way, their recharge does not affect the distribution network. It is easy to see that if the generation system does not work (at night, or on a cloudy day), this algorithm will no longer be valid. In this case, we must consider a different principle such as that which will be explained later.

"Peak shaving" algorithm: this algorithm is applicable regardless of the presence of a renewable resource. Based on the energy absorption in the network and the presence of the parked EVs, the controller will decide whether to extract energy from the vehicles in order to reduce the peak rate of energy absorption, or whether to recharge them. The ultimate goal is therefore to level the power peaks and obtain a load curve that is as smooth as possible.
