## 1 Introduction
Hence, although solar tracking systems have a higher cost than fixed systems, their maintenance is more complex and their exposure to environmental conditions is greater [18]; the performance of dual-axis trackers are greater than those of fixed systems [19; 20] and single-axis trackers [21; 22; 23]. [PERSON] states in [21] that a dual-axis tracking system would result in greater irradiance than a single-axis due to its ability to minimize losses associated with cosine effect. Authors in [22] highlight their conclusion that using the two-axis sun tracker system enables the PV panel to collect and produce higher amounts of electrical energy than using single-axis and fixed structures; their study considered five configurations of sun tracking systems and two traditional fixed panels. The results presented in [23] show that the optimal trajectories for the tilt and azimuth angle depend on the available solar radiation, solar cell efficiency, tracking system consumption, and the optimization bounds. Therefore, based on these studies, it can be affirmed that the choice of the type of strategy depends on several factors, it being necessary to delve into the technological and economic components to reach useful conclusions [5]. Regarding the tracking mechanism, different driver methods can be distinguished to achieve the objectives of the collector movement [8]. Among them, the sensor driver systems stand out, whose operation is based on the variation of light received by optical sensors that cause the movement of the collectors looking for the position of the sun. Additionally, there are microprocessor driver systems that incorporate small processors with movement strategies programmed through mathematical models to locate the position of the sun. Within these in the bibliography are the open-loop driver systems that modify the movement of the actuators of the modules from mathematical equations that fix the position of the sun from the day and the hour. In contrast, closed-loop driver systems modify the movement of the actuators based on the information provided by position sensors, recalculating the position of the sun. Finally, intelligent driver systems incorporate artificial intelligence techniques to control the movement of collectors [24]. Another of the determining factors in the performance of a PV plant is the shading of its modules, since these shadows not only imply a lower incident irradiance [25] but also give rise to the appearance of hot spots that bring with them overheating and losses in energy production [26]. In this regard, the behavior of PV modules when they are partially shaded has been widely debated. Several simulation models have been used to find a configuration less susceptible to shadow problems of solar cells [27; 28; 29; 30]. Specifically, [PERSON] et al. [31] have analyzed the effect of shading in a PV tracker with partially shaded astronomical tracking based on the exact arrangement of shaded cells and modules. Other authors have analyzed the energy cost in the production of PV plants as a function of the connections between the cells and the modules [32] of the ground cover ratio (GCR) of the plant that depends on the variables of their design [33] or of the tracking strategy [26; 34]. One possible solution to alleviate the effect of shadows in PV plants with solar tracking is back tracking [35], which consists of modifying the orientation of the collecting surfaces in shading situations between panels in order to eliminate such shadows. Another possible solution is to modify the geometry of the collecting surfaces. Thus, although most of the PV panels found in PV plants connected to grids are rectangular, there are already some installations with dual-axis solar tracking where the collectors have other geometric shapes, such as those developed by the Deger Iberica company in Tarragona (Spain), Ontario (Canada), or Estonia, with 15.6 kWp, 24 MWp, and 100 kWp installed, respectively [36].