**5. Conclusions**

In this paper, we have computed the value of the radiation view factor to determine the reflected solar irradiance reaching the rear side of the bifacial solar PV. We have verified the results with the existing analytical solutions. In this scenario, we focus on the computing performance to examine the improvement in computation speed of Python as compared to VBA. It has been shown that, Python can be used more e ffectively than VBA for radiation view factor analysis between two surfaces. With the utilization of an appropriate mathematical library, computation time was significantly reduced by 71–180 times for Python when compared with VBA. This improvement in computation speed not only saves time, but also provides an optimized design tool for the research. An important finding of the view factor simulation is that, as the element size of the finite element grid decreased, the computed output converged to the analytical view factor value. Thus, the simulation accuracy could be achieved up to 99.4% for the maximum number of iterations considered for this paper, i.e., 250 billion and the response time of the simulation in Python and VBA was 1628.51 s and 292,714 s, respectively. The application presently considered in this article are for relatively small areas of the reflecting and the receiving surfaces. In an actual industrial environment where the designer will deal with multi-gigawatt solar PV farms, that may employ enhanced reflections near the horizon. In that case, to model such large-scale systems, the number of iterations the computer simulations have to run will increase to the order of a few quadrillion or more. Therefore, the importance of faster code written in a computation environment such as Python will be of grea<sup>t</sup> benefit to the PV system designers. Hence, it is concluded that, Python can be utilized as a reliable simulation tool to develop the code further for bifacial solar PV research.

**Author Contributions:** Conceptualization: T.M., M.S.G., and M.A. Methodology: M.A., T.M., and M.S.G. Formal analysis: M.S.G., T.M., and M.A. Coding: T.M., M.A. Resources: T.M., M.S.G., and M.A. Data curation: M.A., T.M., and M.S.G. Writing—original draft preparation: M.A., M.S.G., and T.M. Writing—review and editing: T.M., M.S.G., and M.A. Supervision: M.S.G. and T.M.

**Funding:** This project is being run in collaboration with four partners: Energy Technology Partnership (ETP-Project 161) Scotland, Wood Group-Clean Energy, Heriot-Watt University and Edinburgh Napier University, UK.

**Conflicts of Interest:** The authors declare no conflict of interest. *Energies* **2019**, *12*, 3826

#### **Appendix A View Factor Calculation Tables at Di**ff**erent Element Sizes**


**Table A1.** View factor simulation data for element size *hi* = 0.01 m.

**Table A2.** View factor simulation data for element size *hi* = 0.008 m.


**Table A3.** View factor for element size *hi* = 0.004 m.



**Table A4.** View factor for element size *hi* = 0.002 m.
