## 3 Methodology
### Station Demand
The expected number of EVs (E) is forecasted by multiplying (C) by the average conversion percentage to EVs (T) having the percentage of private charging (PC):  
\[E=C\times T\times(1-\%PC) \tag{6}\]  
The usual charging rate is based on the average trip length (L) vs. the EV consumption rate (R) = 0.20 kWh/km as per [45], with approximately 60% of cars being charged at home as per [15; 46]. Moreover, the battery capacity (BC) has been set as 75 kWh as an average between 40 and 100 kWh [47]. (L) has been determined based on the conducted survey using the weighted average criteria as follows:  
Figure 2:0  
where:  
\(\mathrm{L_{i}}\) = Trip length per day,  
\(\mathrm{z_{i}}\) = Percentage of respondents in the trip length category,  
\(\mathrm{m}\) = Total number of ownership categories. The car battery consumption (CBC) per day is calculated as demonstrated in Equation (8):  
Figure 2:1Average recharging days (RD): This measures the frequency of recharging needed for a car. It is calculated as demonstrated in Equation (9):  
Figure 2:2  
Hours needed for full charge: It is computed by dividing the BC by the charger power CP, which has been assumed to be 45 kWh [48]. Figure 2:3  
Fully charged number of charging cycles (Nf): This represents the total charging cycles a station can complete in a day. It is calculated by dividing the operational hours of a day (24 h minus 5 h off) by the hours needed for a full charge:  
Figure 2:4  
Station capacity per day (SD): This reflects the daily service capacity of a charging station. It is determined by multiplying the number of car slots per station CS at the station capacity with the number of full charging cycles possible in a day Nf:  
Figure 2:5  
Station capacity (SC): This indicates the overall capacity of a charging station over the average recharging day, as follows:  
Figure 2:6  
Number of stations (NS): The total number of charging stations needed is estimated as follows:  
Figure 2:7  
Adjusted number of stations (NS'): Accounts for additional stations needed for maintenance. It is calculated by increasing the NS by 10%. Figure 2:8  
A parametric study will be conducted by focusing on Al-Wosyataa (number 7), along with the average calculations for all the other zones on the normal average basis assumed in Section 3.2, a central area in the city, due to its significance in terms of population density and urban dynamics. This study aims to analyze the impact of varying key parameters on the required number of EVCSs. The central location of Al-Wosyataa makes it an ideal representative area for this study, as it likely reflects a higher concentration of EV usage and charging needs, providing valuable insights for urban EV infrastructure planning. This study explores all the possible combinations of these parameters, totaling 15,360 cases, as per Figure 2:9  
In analyzing the EV charging infrastructure requirements across the 17 different zones of Hail, a standardized set of assumptions has been employed, see Table 2.0 This approach provides a foundational overview of the charging station needs in each zone, facilitating a comprehensive understanding of the infrastructure demands. In addition to these standard \begin{table}
\begin{tabular}{c c c c} \hline
**EV Consumption Rate R** & **Car Battery Capacity BC** & **Car Slots per Station CS** & **Charger Power CP** \\
**(kWh/km)** & **(kWh)** & **(Cars)** & **(kWh)** \\ \hline Increased from 0.05 to 0.40 & Increased from 25 to 100 & Increased from 50 to 500 & Studied from 20 to 75 \\ with a step of 0.05 & with a step of 5 & with a step of 50 & with a step of 5 \\ \hline \end{tabular}
\end{table} 
Table 3: Parametric study initial sample. assumptions, a key practical consideration is incorporated to reflect real-world charging behaviors: the assumption is that 60% of EVs will be via private chargers, according to [PERSON] et al. [17] and [PERSON] [15].