## 3 Tests and Results  
### PV System Power Generation Test  
#### 3.1.1 Solar Irradiation Testing and Analysis  
Factors affecting the performance of PV power generation mainly include solar radiation intensity and ambient temperature. Solar radiation intensity is the most important factor affecting the performance of PV power generation, while ambient temperature affects the operating performance of the electronic devices in the PV panels [36,37].  
In this project, the data on annual irradiance and ambient temperature of Qingdao city in 2022 were tested using Jinzhou PV meteorological stations. The test device is shown in Figure 6[38], the technical indicators are shown in Table 3, and the daily average values of ambient temperature and daily solar radiation are shown in Figures 7 and 8.  
The weather station used in Figure 6 is equipped with an automatic tracking solar radiometer, an illuminance sensor, a total radiation meter, and other devices to detect the light intensity and temperature of Qingdao throughout the day and record historical data via its special software.  
\begin{table}
\begin{tabular}{c c c} \hline
**Instrument Name** & **Model** & **Function** \\ \hline \multirow{2}{*}{Solar battery} & Colloidal battery (12 V/65 AH) & Storage of DC power from PV panels \\ \hline \multirow{2}{*}{DC Detector} & Voltage 200 V & Total amount of electricity generated on the \\  & Current 20 A & day of testing \\ \hline Environmental testing system for PV power plants & FSZJ-J-1-01 & Solar irradiance detection \\ \hline \end{tabular}
\end{table}
Table 2: Summary of devices required for field measurement of PV power generation.  
Figure 4: Adjustable buck circuit.  
Figure 5: Schematic diagram of PV system. (**a**) Experimental bench building circuit diagram. (**b**) Field wiring diagram. (**c**) DC power tester actual measurement chart.  
Figure 8: Distribution of total daily radiation in 2022.  
Figure 6: Jinzhou Photovoltaic weather station (small).  
\begin{table}
\begin{tabular}{c c c c} \hline
**Meteorological Element** & **Resolution** & **Measuring Range** & **Precision** \\ \hline ambient temperature & 0.1 \({}^{\circ}\)C & \(-\)40–80 \({}^{\circ}\)C & \(\pm\)0.1 \({}^{\circ}\)C \\ illuminance & 1 LUX & 0–200,000 LUX & \(\pm\)5\% \\ radiation & 1 W/m\({}^{2}\) & 0–2000 W/m\({}^{2}\) & \(<\)5\% \\ \hline \end{tabular}
\end{table}
Table 3: Summary of technical indicators.  
Figure 7: Daily temperature distribution in 2022.  
The day 1 in Figures 7 and 8 represents 1 January, and day 365 represents 31 December. The yearly average of ambient temperature in Figure 7 is 14.0 \({}^{\circ}\)C, and the number of days close to it is 98-130 and 278-331. Figure 8 focuses on the solar radiation and its numerical fit; the mean value of solar radiation is 13.004 MJ/m\({}^{2}\), which is in the zone of average PV potential [39]. Comparing the fitting effect between days 98-130 and 278-331 in the two figures, we can see that the fitted value of days 98-130 is closer to the mean value and the fitting effect is better. Therefore, in order to simplify the test process without losing accuracy, the mean value of PV panel power generation from days 98-130 can be used to represent the mean value of annual power generation.