## 2 Material and Methods
### Data Processing and Analysis  
The data collection for the research was carried out in the summers of 2017, 2018 and 2019 on fourteen different days between 11:00 am and 1:30 pm. In each case, measurements were  
Figure 6: Schematic illustration of PV module measuring station ‘B’.  
Figure 7: The accuracy of the alignment to the sun can be illustrated with the help of the CPV cells (upper image: incorrect setting; lower image: precise setting).  
taken continuously (every second, station 'A') and at an interval of an average of 10 s (station 'B'). The measurements of the PV performance and irradiance were made altering the inclination of the PV module towards the north, north-west, west, south-west, south, south-east, east and north-east as follows:  
* Module performance and irradiance measurements between the FP and a solar tracking uncertainty of 5\({}^{\circ}\) at 0.5-degree intervals in all directions to find the performance insensitivity threshold of the m-Si, p-Si and a-Si technologies. It was possible to measure the performance values directly without any loss in the TMPS devices.
* Module performance and irradiance measurements between the FP and a solar tracking uncertainty of 30\({}^{\circ}\) by moving in 10-degree steps in all directions to see the technology-specific performance properties of m-Si, p-Si and a-Si technologies. It was possible to measure the performance values directly without any loss in the TMPS devices.  
For all angles the starting position of the PV modules was the FP of the CPV solar cells, after which the aforementioned orientations, radiation and performance data were measured. The performance output for each position was measured over 10 s, and switching to the next measurement lasted for 2-20 s. Due to the switching of the measuring instruments, it was necessary to wait about 6 s. During the measurements this method made it possible to eliminate the effect of the changing environmental conditions (for example, temperature changes of PV modules), since the starting point for each measurement was the FP.  
Appropriate measurements of yield loss for a solar tracking position from the FP to a solar tracking uncertainty of 5\({}^{\circ}\) were achieved during 2018 and 2019. In the summers of both years, measurements were performed 20 times for each direction. These data were averaged and checked using relative standard deviation (CV%). A relative standard deviation between 0 and 10% shows homogeneous conditions, between 10.1 and 20% it shows a medium variability, between 20.1 and 30% it shows strong variability, while above 30.1% it is related to strongly heterogeneous conditions [52]. For all measurements, the relative standard deviation of the averaged data was below 1%, which was an excellent result. To manage, evaluate and analyse the data Microsoft Excel (version: 2016, Redmond, DC, USA), PicoScope (version: R5.23.0, St Neots, UK), Matlab (version: R2017a, Natick, MA, USA) and SPSS Statistics (version: 24, Armonk, NY, USA) software were used. It is difficult to detect systematic mistakes but these phenomena do not increase the deviation of the measurements. The given measuring accuracy and calibration (which should be independent of the measuring system) of the measuring devices can help solve this problem.