## 4 Results and Discussion
### Analysis of Measured Ambient Weather Parameters  
The PV power plant and all the sensors in the installed DAS were tested with a week of data, starting from 1 st to 7 th February 2019, the summer month, to authenticate the reliability of the system. The abovementioned measured ambient weather conditions are presented in Figure 11a,b. The module temperature is the average back-of-module surface temperatures of all PV systems.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{2}{c}{**Average \% Difference before and after Signal Conditioning**} \\ \cline{2-4}  & **Off-Grid System** & **Hybrid System** & **Grid-Assisted System** \\ \hline V\({}_{\text{out}}\) before signal conditioning & 0.37 & 0.07 & 0.39 \\ V\({}_{\text{out}}\) after signal conditioning & 0.26 & 0.04 & 0.23 \\ \% signal improvement & 29.73 & 42.86 & 41.03 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Average percentage difference before and after signal conditioning for the three systems.  
Figure 10: Regression distribution in (**a**) off-grid, (**b**) hybrid and (**c**) grid-assisted PV systems’ signal conditioner linearization.  
As seen in Figure 11, the module temperature was observed to follow the solar radiation (tilted and GHI) as well as air temperature closely. It should be noted that the overlapping tilted and horizontal surfaces' irradiance is due to the season (summer) in the measurements were conducted. In the winter season, a different irradiance is expected on both surfaces with a higher irradiance obtained during solar noon on the tilted surface. The varying seasonal irradiance on both surfaces is attributed to the low sun angle experienced in winter as compared to summer. The air relative humidity and wind speed are decreasing factors of the module temperature. Theoretically [31], at a fixed amount of water vapour in the air, an increase in temperature reduces air relative humidity and vice versa. The above findings tend to agree with the theory. Among some of the effects of wind speed on PV performance, it reduces the module temperature by the dissipation of convective heat transfer [32]. Nonetheless, the decrease in the module temperature at the peak wind speed period in Figure 11 cannot be wholly attributed to the cooling effect of wind. As peak wind speed period coincides with sunset. The direction is a major influencing factor of the wind cooling effect. Thus, a wind rose profile was developed and given in Figure 12.  
Figure 11: A week of ambient weather conditions of (**a**) temperature and relative humidity (**b**) wind speed and solar irradiance against days of the week at SolarWatt Park.  
Figure 12: A wind rose profile of the PV power plant’s premises over a week.  
Measured wind speed and direction data were integrated into the hourly interval and was used to develop the wind rose profile. The predominant wind showed by the resultant vector which was determined by the frequency count of the mean wind direction. As shown in Figure 12, 55% of the wind with a mean direction of 108\({}^{\circ}\) was observed to blow from the southeast; serving as the prevailing wind. Therefore, the wind direction favours the PV module regarding cooling as the predominant airflow is in the opposite direction of the PV array.  
However, Figure 13 shows a typical day profile of irradiance, relative humidity, array and ambient temperatures of a variable day with a rainstorm on 11 th February 2019. The data collected by the data logger displays a nice correlation despite the variable weather conditions. The data loggers functioned properly without faults in the day of stormy weather.  
The curves depict that the array temperatures are nearly similar to the ambient temperature at a zero solar irradiance. But immediately the solar irradiance rises, the array temperature increases and becomes more than the ambient temperature.