This article proposes a methodology for the optimal selection of the control strategy for two-axis solar tracking systems, that simultaneously reduces tracking error and energy consumption in existing solar tracking systems, improving their overall performance. Begins with the characterization of the tracking system, then the constraint definition helps to pre-select the possible controllers. Subsequently, a selection stage is carried out from a heuristic approach, based on a multibody simulation analysis and an experimental analysis, and the feasible controllers for the application of the tracker are defined. Finally, a comparative analysis is carried out to find the best control strategy for the existing tracker and the solar application. The optimal selection approach was implemented in a solar tracking system for low-power photovoltaic applications. Based on the defined constraints, six control strategies were pre-selected, which were simulated and implemented in the physical system. The multibody simulation process allows the designer to know the dynamics of each controller, and in turn determine an approximation of the best configuration of the elements that compose it. This, with the aim of validating that each proposal is compatible with the application of the solar tracker, and that it can be taken to the real experimental environment. From the experimental results, the MPC controller shows the best performance. Well, although it has a greater error than other alternatives, its value is still below the permissible precision level (less than 2°) and in turn has the lowest energy consumption 0.7867 Wh. That is, a reduction ranging from 34 to 76% with respect to each performance of the alternatives considered. In addition, the dynamics of the control actions it performs are smoother, thus reducing wear on the actuators.Thus, the results obtained to support that with the proposed methodology the overall performance of solar tracking systems can be increased, significantly reducing tracking error and energy consumption.

This paper proposes a methodology for optimizing a class of robotic solar tracking systems with two degrees of freedom using a heuristic approach. The proposal allows a balance to be found between the energy consumption and tracking accuracy in the tracking system. The main purpose is the behavior modification of the system through the combination of two manipulation strategies, one associated with the energy savings and the other with the tracking error. The heuristic approach was implemented in a solar tracking system with the end effector connected to a solar measurement device. Four energy saving strategies and three tracking strategies were developed, simulated and implemented in the system. The simulation results show that the resulting strategy combination (tracking error and energy saving approach) led to 31.55% energy saved compared to the reference values, with a tracking error of 0.06∘. Moreover, the experimental assessment of the same combination led to 26.98% energy being saved, with an azimuthal tracking error of 0.062∘ and elevation tracking error of 0.071∘. The preceding values support the aim of the presented proposal to significantly reduce the energy consumption while concurrently achieving a competitive tracking error.

Solar Tracking Systems are useful to increase the generation efficiency of photovoltaic technology, mainly for concentration technology, where dual-axis is required on account of the high accurate alignment to the Sun. Even when there exists a strong relation between tracking error and energy efficiency, multiple technological and research developments have sought to solve these problems independently. The present research proposes a novel concurrent design methodology for optimizing the overall performance of two-axis trackers, allowing to keep a balance between the tracking error and the energy consumption from the design stage, from an optimization approach. The concurrent approach was implemented to design a Solar Tracker as a solar monitoring system, was compared with four commercial systems, obtaining a similar pointing accuracy with a mixed tracking error of ${0.0942}^{°}$. The system has the best energy balance, consuming only $0.9641\%$ of the energy generated for the tracking action, below commercial models. Finally, a CO${}_2$ impact analysis was carried out, where the proposed tracker obtained the lowest value, with $25.7018$ g. The results support the developed concurrent strategy for the optimization of the overall performance of dual-axis systems, allowing us to find a harmonic balance between the energy consumption and the required tracking accuracy.