**5. Conclusions**

This study covers an on-grid PV system design in accordance with a self-consumption model developed for KAU Hospital. The solar PV system was simulated. In the design, the data of Harran university hospital, which produces electrical energy with the solar power plant, were used. The annual average PV electricity (AC) delivered by the total established capacity of the PV system was found to be 1843 kWh/kWp.


Additionally, the RSM and ANFIS models were developed to analyze the performance of the solar PV panels' energy generation system depending on uncertain parameter levels. The conclusions regarding the RSM approach showed that a polynomial model is rational for approximation and can be used for defining the relationships efficiently for the entire space of the independent parameters. Hence, Figure 9 showed the normality, and no extreme evidence pointing to possible outliers. Figure 16 examination showed that the parameters' lines are not parallel. This is the indication that an interaction exists between the factors. Hence, the optimal solar PV generation can be attained, at average module surface temperature, high radiation, wind direction and wind speed level. Changing from low to high module surface temperature and outdoor temperature reduces the solar PV yield. The optimal level of solar PV generation is achieved with average module surface temperature, high radiation, and high wind speed level. High surface temperature is not desired and can be reduced drastically with wind speed.

The conclusion demonstrated that the ANFIS model with nine rules gave the highest performance with the lowest residual. The ANFIS model can produce and predict the solar PV value for the output parameter regarding predetermined input parameters' intervals. The Gaussian MFs seems appropriate for defining the fuzzy linguistic terms used in fuzzy rules and in the inner loop of the model for fine-tuning the PV generation. Results and findings showed that the ANFIS model can successfully be utilized for the prediction of solar PV module performance.

As a result, meeting the electricity needs of KAU hospital is possible with a suitable capacity of PV system according to its economic resources. The PV systems' investment is particularly more attractive nowadays with the reducing PV system cost, and improved PV panel technologies (such as bifacial cell, hetero-junction solar cell). A 40 MW capacity PV system is recommended according to the self-consumption of KAU hospital. In addition, the capacity of the PV system for the self-sufficiency model should be 100 MW.

**Author Contributions:** The individual contribution of the authors was as follows: Conceptualization, O.T., M.A.A. and R.A.; together designed research, provide extensive advice throughout the study reading to research design, research methodology, data collection, and assessment of the results. Funding acquisition, E.H.-V.; writing—review and editing, R.A., O.T., M.A.A. and E.H.-V. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, under grant No. (D1441-135-626). The authors, therefore, acknowledge with thanks DSR technical and financial support.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data are contained within the article.

**Acknowledgments:** This work was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, under grant No. (D1441-135-626). The authors, therefore, acknowledge with thanks DSR for technical and financial support. In addition, the authors thank Harran University Presidency and GAPYENEV center for data supply and technical support.

**Conflicts of Interest:** The authors declare that they have no competing interests.
