Renewable energy is a type of energy that is derived from ongoing natural processes and energy of natural processes converted into available forms. Renewable energy sources can be listed as sunlight, wind, flowing water, biological processes, and geothermal. The use of renewable energy sources is growing rapidly because of the fact that fossil fuels are limited, being rapidly depleted, pollute the environment and cause climate change. In addition, another factor that increases the use of renewable energy sources is that they can be installed everywhere, and can be developed using various technologies.
The most common sources of renewable energy are solar and wind energy. The siting of wind turbines must ensure maximum exposure to wind in order to achieve wind energy, but not every province in Turkey can provide such conditions. Also, wind turbines must be built far from residential areas, due to the fact that the sound of wind turbines greatly inconveniences people. In addition to this, the rural setting of wind turbines is generally on the migration route of birds. Research shows that birds often change their migration routes or that birds die by hitting operational turbines due to the siting of such turbines (Akkaya et al. 2002). Accordingly, it is observed that solar farms, as a source of renewable energy, are more widespread than wind turbines.
Due to the fact this method of obtaining electrical energy using solar energy is easier, more practical, less harmful, and at lower cost than other renewable energy sources, it is rapidly becoming widespread. However, the efficiency of solar cells is only around 20 %, so it prevents the conversion of solar energy into electrical energy at full efficiency (Green et al. 2000). Therefore, solar tracking systems have emerged, in order to obtain the greatest efficiency from sunlight.
A solar tracking system is a monitoring system which aims for solar panels to operate by tracking the sun at full efficiency during the day to allow for the sun rays arrive perpendicular to the panels. It can be seen that the efficiency achieved from the solar panels increases from between 25 and 55 % (Irina and Cătălin 2010).
In recent years, there have been many studies concerning the development of solar tracking systems. Studies are currently being conducted to get sun rays perpendicular to panels using a variety of control techniques (Shugar et al. 1996; Roth et al. 2004; Colak et al. 2005). According to the study, applications on solar energy have increased rapidly in recent years, and new materials and methods are being developed for this energy source.
In another study, a SCADA system is developed in order to allow for optimal sun tracking and real-time control using a programmable logic controller (PLC) and step motor in a two degrees of freedom (DOF) tracking system. In this study, power generation increases, compared to other PV systems, and non-tracking systems because real-time control and monitoring is provided (Figueiredo and Costa 2008).
It can be seen that the tracking system is made very stable by the development of a microprocessor-based solar tracking system. A microprocessor-based solar tracking controller was designed and manufactured in 1990, in New Delhi, India. The controller has several features which makes it versatile for tracking and system control/monitoring applications (Saxena and Dutta 1990).
Environmental conditions effect power production in solar energy, but our devices work on a constant voltage. If light intensity and temperature do not change, a maximum power point (MPP) will occur at a constant voltage. However, if the environmental conditions change over time, the voltage in the MPP will also change. In this case, for better performance, a more complicated controller is required with parameter changes according to atmospheric conditional changes (Nopporn et al. 2005). The output power of a solar panel depends on the amount of light on the panel (Li et al. 2005). The designed Fuzzy logic controller technique can find peak power by doing wide range of illumination and temperature variations (Ghassami et al. 2013).
A fuzzy logic-based two-axis solar tracking system increases efficiency by 33.416 % compared to a non-tracking system. In this study, a stepper motor is used for the direction control and an Arduino Uno is used for the microcontroller. In addition, the proposed fuzzy logic controller has been implemented and tested using MATLAB for this study (Bawa and Patil 2013).
Fuzzy logic is used in many engineering applications, because it is considered by designers to be the simplest solution available for a specific problem, for instance, in household electrical appliances, auto electronics applications, and industrial automation systems (Peri and Simon 2005). With complicated processes where control is hard, it becomes necessary to use a fuzzy logic controller (Takagi and Sugeno 1985). Fuzzy logic controller is adaptive and nonlinear nature, which provides it robust enactment under load, supply voltage disturbances, and parameter variation (Punithaa et al. 2013).
So far Fuzzy logic control-based solar trackers of different configurations have been implemented on FPGA and PIC microcontrollers, but the control logic for this research was implemented on a simple microcontroller board Arduino Uno (Hamed and Mohammed 2012; Khaehintung et al. 2007).
In the solution there is a dual-axis solar tracking system, based on solar maps, which can predict the exact apparent position of the sun, by latitude location, thereby avoiding the need to use sensors or guidance systems (Abdallah and Nijmeh 2004).
In another study, a solar tracking algorithm is designed and implemented on a solar tracking experimental platform, using a tri-positional control strategy. It makes use of measured values for radiation from appropriate sensors and assures command of the platform’s two positioning motors. The implementation technique reduces the cost of the tracking method and makes it cost-effective technology (Arghira and Iliescu 2013).
A solar cooling system is important for improving of energy efficiency. This study’s aim is to improve energy efficiency of a solar cooling system by an innovative combination of optimized solar cooling, storage techniques, and an absorption chiller, with highly developed techniques for control using known tool; TRNSYS and MATLAB with Simulink (Visek et al. 2014).
A single-axis sun tracking system with two sensors was designed. The data acquisition, control, and monitoring of the mechanical movement of the photovoltaic module were implemented based on a programmable logic-controlling unit (Al-Mohamad 2004).
In this study, the design and application for a single-axis solar tracking system is developed based on both fuzzy logic and PID controller in a real system. The necessary control circuits are designed. The control circuit is built on an Atmega 328 microcontroller and necessary software is installed into the control unit according to MATLAB simulations. In this study, it has been shown that fuzzy controllers are more efficient than PID controllers in single-axis solar tracking system. This result is reached using real-time measurement data obtained in the scope of the study.