## 6 Conclusions  
This study included the design of a solar charging station network for EVs in urban areas of the KSA, with Hail City serving as a case study. Through the meticulous integration of survey results, parametric studies, and economic and environmental analyses, this study presents a compelling case for the strategic deployment of PV-EVCS across Hail City.  
In assessing the number of charging stations required, the research identified that Zone 4 would demand the highest number, totaling seven stations, without private charging options. This demand notably decreases with the introduction of a 60% rate of private charging, highlighting the significant impact of private EV charging solutions on public infrastructure needs. This study meticulously calculated the adjustments necessary to accommodate station maintenance and downtime, ensuring the robustness of the proposed network.  
Parametric studies provided deep insights into the infrastructure requirements under varying conditions. For example, the impact of the average R on the number of stations needed illustrated that lower consumption rates could significantly reduce the number of required stations. Additionally, by exploring the scenarios across 17 zones in Hail City with standards such as a fixed average R of 0.20 kWh/km and BC set at 75 kWh, this study offers a nuanced understanding of the station distribution and capacity requirements.  
The economic evaluation of the 1047.35 kWp PV system reveals an estimated conventional PBT of 11.69 years, accompanied by a return on assets of 10.17%. The system generates accumulated cash flows amounting to SR 7,169,294.62 over 30 years, while the estimated operational and maintenance expenses are predicted to be SR 50,000 per year. The overall investment cost for the solar PV and EV charging stations is SR 4,487,982. This cost is offset by yearly electricity savings from solar and grid sources, which can reach up to SR 396,465.26 by year 30.  
The CO\({}_{2}\) savings for each EV were calculated using a rigorous generalization in the environmental study. These savings were estimated per km of driving. This methodology enabled a detailed assessment by considering the durations of the trips, which were obtained from a thorough investigation of the trip length (L), which was found to be approximately 77 km/day. The analysis was enhanced by considering the anticipated quantity of EVs. When using 80% PV energy, the emissions savings range from 3847 MtCO\({}_{2}\)/year for 1000 vehicles to 192,349 MtCO\({}_{2}\)/year for 50,000 vehicles, assuming a consumption rate of 0.15 kWh/km. The range of CO\({}_{2}\) emissions varies from 4917 MtCO\({}_{2}\)/year for 1000 EVsto 245,829 MtCO\({}_{2}\)/year for 50,000 EVs, assuming a consumption rate of 0.30 kWh/km. Even with a lower PV integration rate of 20%, there were noticeable reductions in the CO\({}_{2}\) emissions. In conclusion, this work presents a detailed framework for the deployment of PV-EVCSs in Hail City, balancing technical, economic, and environmental considerations.  
Conceptualization, A.A.-f. and R.A.A.; methodology, R.A.A.; software, A.A.A.-f.; validation, A.A.A.-f. and R.A.A.; formal analysis, A.A.A.-f.; investigation, R.A.A.A.; resources, A.A.A.-f.; data curation, R.A.A.; writing--original draft preparation, A.A.A.-f.; writing--review and editing, R.A.A.A.; visualization, R.A.A.; supervision, R.A.A. All authors have read and agreed to the published version of the manuscript.  
The Researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support (QU-APC-2024-9/1). The authors also thank K.A.CARE for its cooperation and provision of climate data.  
Not applicable.  
Data Availability Statement: Data is contained within the article.  
The authors declare no conflict of interest.