Performance and Economic Analysis of Designed Different Solar Tracking Systems for Mediterranean Climate

Abstract

Solar power occupies a significant position among global renewable energy sources due to its abundant energy potential. Consequently, its contribution to electricity generation is steadily increasing. However, obtaining peak efficiency from fixed solar photovoltaic (PV) panels is a formidable task due to their limited ability to consistently tap into solar energy. To tackle this issue and mitigate energy efficiency losses, the utilization of solar tracking systems has emerged as an exceptionally effective solution. These systems enable continuous adjustment of the panels’ position to align with the sun’s trajectory, optimizing energy absorption and enhancing overall performance. This paper presents the performance and cost analysis of three distinct solar panel tracking systems, namely, a fixed system, a single-axis system, and a dual-axis system. The systems are operated under identical coordinates and conditions. The production data are collected over a period of 15 days for comparative analysis. The tracking movements of the systems are controlled using Arduino. The mechanical components are specifically designed for the establishment of each system. The findings of this study indicate that both single-axis and dual-axis solar tracking systems outperformed fixed systems in terms of power generation. The single-axis system demonstrated a 24.367% increase in power production, while the dual-axis system showed a 32.247% increase compared to the fixed system. Moreover, a cost analysis was carried out considering the installation expenses and power production data of the three systems. It was determined that the single-axis tracking system achieved payback in 0.39 years less compared to the fixed system, while the dual-axis system achieved payback in 1.48 years less compared to the fixed system. Overall, this study underscores the advantages of implementing solar tracking systems, particularly in the single-axis and dual-axis configurations, as they contribute to higher power generation and cost-effectiveness compared to fixed systems.

1. Introduction

The widespread use of energy, which is one of the effects of the rapid growth of national economies, has increased the need for fossil resources. The depletion feature of fossil resources has made it necessary to turn to alternative energy sources. To address this, substantial efforts have been made to shift towards clean and sustainable energy generation using renewable sources such as wind and solar energy. The establishment of power plants utilizing renewable energy sources aims to create a sustainable energy system and mitigate the destruction of nature. This transition towards renewable energy is crucial for creating a sustainable and continuous energy supply. Technological advancements have enabled the establishment of more efficient production plants and systems, maximizing resource utilization and promoting an environmentally friendly lifestyle. Continuous research and development efforts are focused on achieving the highest efficiency in resource utilization. This paper represents one such study, contributing to the broader objective of creating a sustainable and environmentally friendly world.

This paper focuses on increasing the efficiency of electricity production through solar energy, a preferred renewable energy source for sustainable living. This study emphasizes the importance of sustainability and explores methods to maximize electricity generation from existing solar power plants. Solar energy is globally recognized as a renewable energy source and is harnessed using solar panels and associated systems. This paper highlights the significance of achieving high efficiency and real sustainability in the pursuit of a sustainable life. The paper investigates the implementation of solar tracking systems in existing and new power plants to enhance electricity generation. By utilizing these systems, the capacity of renewable energy systems can be increased while reducing time and costs, thereby accelerating the shift away from fossil fuel consumption. This paper presents the establishment of portable solar tracking systems and compares their production and cost with conventional fixed systems. The results demonstrate that the proposed system can generate more electricity using the same number of panels and land, promoting greater energy production with fewer resources. This paper explicitly suggests the use of solar energy systems for sustainable and clean energy production, emphasizing their crucial role in a sustainable future.

In this paper, solar tracking systems are designed to capture the most suitable angle for the panel from sunrise to sunset during the day. In this context, solar tracking systems are being developed daily with technology and aim to achieve the maximum possible energy production from the solar panels. Especially in recent years, many researchers have been working on tracker systems that allow panels to be exposed to more sun by imitating the movement of the sun throughout the day. These researchers carry out numerous studies such as new system analyses, design by simulation, and the comparison of production and performance analyses in their work on the tracker.

As a result of the widespread use of solar energy systems, new developments and efficiency studies have also become widespread. Many studies have been carried out on tracker systems, which are the most important gains of these studies. Some of these studies are described as follows.

1.1. Experimental Setup

A study was conducted to determine how much the radiation in the sun’s rays changes under certain conditions. The research led to the development of a hybrid system. The technology they suggest is a hybrid algorithm-based solar tracking system that runs on microcontrollers [1]. In this study, a special metal hybrid actuator was developed to be used instead of solar energy and electrical components. With this developed system, electricity production was maximized due to the sunlight falling on the panel, and the system was moved simultaneously with the normal movement of the sun during the day. Designed and implemented without the use of an electrical component, this solar tracking system has proven to be more efficient than traditional fixed systems [2]. A system has been designed to increase production efficiency by following the movement of the sun during the day with a single-axis mechanism connected to the photovoltaic panel. Arduino Uno was used in the designed system. It is stated that the system provides maximum production by continuously monitoring the light intensity by using the maximum light intensity [3]. A particularly created and applied solar azimuth tracking control system has been created for solar energy systems. The control unit for this system is an AT89S52 microcontroller with a straightforward control circuit [4]. A relay-based control system comprising an LDR sensor, servo motor, and Op-Amp is created for a single-axis controlled sun tracking system. This system’s implementation makes use of maximum power point tracking (MPPT). MATLAB software was used to generate the system simulation, which increases efficiency with these systems. As a consequence of the results, they proposed a single-axis solar tracking control system that makes more use of solar energy by tracking the sun and using MPPT [5]. How a fixed angle and horizontal axis single-axis solar tracking (HSAT) system affects the generation efficiency of PV systems is simulated with the help of a specially developed tool. The production efficiency of double-surface PV systems has been simulated [6]. A new algorithm is proposed for a single-axis maximum power generation solar tracker to determine the optimum stopping angle to increase the daily maximum electrical energy. As a result, a new algorithm for a single-axis maximum power generation (1A-MPG) solar tracker based on the 1A-3P solar tracker has been developed to automatically determine the optimum stand angle for PV modules, avoid any shading and then increase it [7]. Mathematical modelling and full simulation of the photovoltaic module were performed using solar energy tracking simulations on MATLAB Simulink. MATLAB/SIMULINK was used for Solar Tracker Applications, and suggestions were made on energy production efficiency according to the results [8]. Updated annual energy simulations were used to evaluate the kWh/m² increase achieved in single-axis tracking systems using bifacial modules. It was stated that surface energy gains measured between 7–9% and backlight gains of 11% were reported in the simulation. This result was consistent with the expectation modelled within 1–2% of the absolute value and was observed to be in line with the global average expectation [9]. The application design and development of inclined uniaxial and high azimuth biaxial solar tracking systems have been studied. LDR sensors are used for sun detection, which is necessary to follow the sun, and the L293D motor driver provides the movement of the solar panel in the desired direction. In addition, a controller consisting of a preprogrammed Atmega8 Microcontroller is used for system control [10]. Using the ray-tracing model of COMSOL 5.4, which uses separate plasmas and tracking outputs, a static cylindrical concentrator is designed, keeping the concentrator static while the absorber alone follows the daily movement of the sun. In the application of this system, it has been shown that when the overall annual variations and the radiated portion of solar radiation are included in the forecast model, using a static concentrator gives an increase of approximately 49% on average [11]. An optimal controller design has been studied in biaxial solar tracking systems using particle swarm optimization (PSO), the firefly algorithm (FFA) and the cuckoo search algorithm (CSA). Three swarm intelligence-based metaheuristic techniques were applied to tune the proportional-integral-derivative (PID) controller for both axes, and 100 independent studies were performed for each algorithm to obtain sufficient data for statistical analysis. Statistical analysis was performed for the obtained data, and the minimum, maximum, mean, variance and standard deviation were calculated for the necessary parameters [12]. They used a P&O-based sensorless method in the new unique single-axis-controlled solar tracking system they developed. In this design, it is stated that the sensorless P&O-based and two-level P&O method developed for a single-axis solar tracking system is applied [13]. To provide more efficiency from solar energy in the equatorial region, a study was conducted comparing tracking systems and fixed systems. These studies were carried out by considering all the weather data in the region where the system operates. As a consequence of the results of the study, the performance analyses of the solar tracking system were compared to the classical fixed panel system, and suggestions were made [14]. This work is a practical study of the dual-axis solar tracker to demonstrate the development, design and performance of the dual-axis solar tracker. In this design, the system was created using LDR sensors, motors, Arduino software and cards. The researcher stated that the proposed solar tracking system works more efficiently than fixed systems [15]. In this study, a single-axis solar tracking system was designed using the second-order lever principle. The originality of this study is achieved by balancing the mass of the water mass and the partial mass of the PV panel on one side of the abutment (left) and the mass of the PV panel on the other side (right) of the abutment, unlike the motor systems in other studies. Thus, they stated that there is no need to use a motor. This system was followed for 90 days with the installed portable system and compared with traditional fixed systems. As a result of the studies, an improvement of 22.93% was achieved in the average energy efficiency with this new system [16].

1.2. Maximum Power Point Tracking (MPTT) Algorithms

Measurements taken using the single-axis solar tracking algorithm they developed for photovoltaic systems were compared with a conventional fixed system created using a hardware block diagram. According to reports, the suggested single-axis solar tracking system typically absorbs 30% more solar energy than the conventional fixed system, increasing output [17]. The results are presented by comparing the production data and total costs of dual-axis control, single-axis control and conventional fixed-axis control systems developed in Bangladesh. According to reports, the effectiveness of the three methods employed was evaluated over 12 months using panels with similar types, attributes, and cloudiness rates [18]. A solar tracking system that aims to use solar energy at the maximum level by tracking the sun throughout the day and that is used to produce more energy in this direction has been proposed. Sun tracking involves the use of photosensitive sensors. The data from these sensors are utilized to drive a DC motor, which in turn drives a panel that follows the sun. By sharing the data, the researchers emphasized that their proposed single-axis solar tracking system produces more electricity than other conventional fixed systems [19]. A study was conducted on the effects of seasons on the fixed system and the solar tracking system. As a result of the study, the effects of solar azimuth and altitude during electricity generation at noon of the two systems are presented comparatively [20]. Performance analysis of the photovoltaic (PV) monitoring system was performed to evaluate the system’s performance using field data measurements. This analysis was performed by analysing the dual-axis tracking device with intelligent algorithms called maximum light detection (MLD). As a result of the analysis of the comparative results, such as sunny and cloudy in a tropical region with continuous heavy cloudy weather conditions, it was observed that the MLD monitor system significantly increased energy production in all these conditions [21]. A technical solution application that allows the conversion of a photovoltaic panel fixed to a movable panel to improve power generation performance is examined. For these studies, it was proven that they could monitor the position of the sun with an efficient and inexpensive 100% functional smart system. It is stated that the perspective of the study is to improve the processing and transmission of all the information detected in the solar tracker to a station using smart antennas associated with the developed embedded system [22].

1.3. Analysis

Double-surface photovoltaic (PV) panels (BP) and inclined and horizontal east-west solar trackers (IEW/HEW) were built and measured to follow the sun to produce energy. In this study, the data were taken from three regions in China for illustrative purposes, and the annual radiation increases of IEW, HEW and BP were analysed and reported under different sequence ranges and albedo conditions compared with optimum fixed mono-face PV systems [23]. A tracking system is proposed for the sun to reach the panels at the steepest angle using a special controller design and analysis method. He stated that the light tracking system is robust, and the analyses before and after the controller application were made using the partitioning method. With the robust controller, the system is proposed to avoid stress and vibrations and smoothly orient the PV panel to its new location [24]. Fuzzy logic and PID-based controllers were used to operate the solar tracking system, and a solar tracking system was created to boost solar energy efficiency, which is becoming increasingly important. In the research, it was shown that compared to other systems, the system in which the solar tracking system was designed increased by 21.2%. Additionally, it is claimed that the suggested system is 2.39% more efficient than fixed systems based on research and application findings generated with the proposed fuzzy logic-based controller and PID-based controller system [25]. The development of two brand-new, effective solar tracking systems using the adaptive neural fuzzy inference system (ANFIS) concept is suggested. Month, day, and time are utilized as input variables to forecast the ideal locations (tilt/orientation angles) for the sun tracker systems to evaluate the suggested sun-tracking controllers. According to what was said, the ANFIS models that were developed as a consequence of the study were assessed to determine their robustness and feature of adhering to the best angles for obtaining the most solar radiation [26]. The developed algorithm aims to bring photovoltaic panels to the most suitable position in real time. It has been reported that the system prediction model working with the algorithm developed in a short time can increase the daily effective irradiation by more than 16% at all stations or up to 264 Wh/day/m² on certain days. It was stated that due to the positive results obtained in the estimation analysis, no significant gain was obtained for the cases with kt′ < 0.05 or kt′ > 0.6, and two estimation algorithms were tested [27]. A separate single-axis solar tracking system operated three times a day in the azimuth plane has been proposed to achieve greater efficiency by tracking the sun. A theoretical simulation has been made in the system to calculate the optimum viewing angles for the city of Irbid. Looking at the simulation results, it was observed that there was no significant difference in solar energy production, and similar results were obtained [28]. They examined Turkey’s present energy strategy and the country’s distributed solar power generating growth at various phases, identifying the country’s strengths and weaknesses in each. Strengths (S), weaknesses (W), external opportunities (O), and threats (T) analyses were conducted in light of the study to provide urgent solutions that would aid in the growth of the DPPG sector in Turkey. In conclusion, it is recommended to open discussion on the future roles of management and the energy market to comprehensively increase the integration of distributed photovoltaic power generation (DPPG) into the Turkish renewable energy market [29]. An affordable and sustainable solution for electrification in these regions has been recognized as hybrid power generation using current renewable sources (wind and solar) and diesel engines. This study intended to find the ideal configuration of these systems for rural Peru because there has not been a thorough investigation into the techno-economic analysis of hybrid systems (PV-Wind-Diesel) for off-grid electrification in Peru, which has been demonstrated to be among developing countries. Seven possible configurations were taken into account, including hybrid systems and single-component systems (solar, wind, and diesel). According to the research findings, the hybrid solar-wind-diesel system is the most financially feasible option [30]. They analysed key policies in India, including radical legislative changes to restructure to give its population universal access to clean electricity. It has been proposed to increase renewable energy resources in the energy sector following international commitments to limit global warming. It is also emphasized that, especially with the Paris Agreement, the transition of the energy sector to renewable energy has accelerated in the last 5 years, and little attention has been given to waste management from the renewable energy sector. This highlights the urgent need for policy coherence across sectors in India to ensure that the core principle of the circular economy is adopted in the development of “clean” renewable energy. [31]. The power generation of a 20-kW photovoltaic power plant with fixed-angle panels is compared to two-axis solar trackers. The study aims to evaluate the feasibility of using more efficient but costlier tracking systems as a standard for future photovoltaic power plants. Simulations conducted in Tehran, Iran, demonstrate that two-axis solar trackers generate more annual energy than fixed-angle panels. An economic analysis also shows improved efficiency and output power with the two-axis tracker system. Despite the complexity and higher costs associated with solar tracking, the study concludes that two-axis trackers allow for the same energy output with fewer solar modules, making them a practical choice for limited installation spaces [32]. The optimal scenario for maximizing efficiency and profitability in a rural household in Africa is presented. It compares different tracking options, such as fixed-tilt, horizontal axis, vertical axis, and dual-axis trackers, and evaluates the lowest-cost solution. The study identifies the optimal solution based on the lowest net present cost (NPC) and conducts a sensitivity analysis to generalise the results for various technical, economic, and climate conditions. The findings indicate that the fixed-tilt-based solution is the most profitable, with an NPC of $13.7k, a levelized energy cost (LCOE) of $0.258/kWh, and CO₂ emissions of 281.11 kg/year [33]. A fuzzy logic solar tracker designed to maximize the efficiency of a photovoltaic system by dynamically adjusting the position of the solar panel for optimal solar radiation utilization is presented. Through analysis of different control strategies, the study establishes that the fuzzy control approach meets all the necessary criteria for the photovoltaic system. A prototype is developed and tested extensively to evaluate the performance of the solar tracker. The results confirm its superiority over fixed solar systems, delivering a noteworthy 40% efficiency improvement [34].

The solar tracking systems which are being studied maximise production by ensuring that the sun’s rays come vertically on the solar PV panels. In this paper, the most efficient system has been proposed by comparing the production data of three portable units, namely, a fixed system, a single-axis tracker and a biaxial tracker, in the Çukurova region of the Adana province. The Çukurova Region is preferred because it is a suitable region for the establishment of solar energy systems in terms of insolation angle and the number of days. Some advantages of the proposed solar tracking systems are presented below:

➢

The solar power production data of the solar tracking systems are presented experimentally. It is clear from the measurements and analysis that the single-axis solar tracking sys-tem generates 24.367% more electricity than the old-style fixed systems, and the dual-axis solar tracking system generates 32.247% more electricity.

➢

The dual-axis system generates 7.871% more power than the single-axis system when the developed solar tracking systems are compared to one another.

➢

It has been observed that the installation and operation of the solar tracking system do not bring much additional load compared to normal fixed systems. The cost analysis for this is included in the study.

➢

Thanks to the Arduino software and card, solar tracking has been performed, and it has been verified with the production results that sun tracking is performed correctly.

➢

The main purpose of this study is to propose tracking systems with numerical evidence that will enable solar systems to produce more electricity by making more use of the sun.

2. Methods

An experimental study was carried out for tracking systems to increase the efficiency of solar energy systems. Portables were created in three different systems, and production was ensured under the same conditions. The results obtained were both analysed and compared.

A portable solar tracking system study was carried out for the solar tracking system, which is one of the most important studies to increase efficiency in solar energy systems. The content of the study includes a fixed system, single-axis solar tracking system and dual-axis solar tracking system. A portable product is designed for each of them separately. The aim is to determine which system is more successful in terms of efficiency by comparing the daily production data of these 3 separate systems consisting of 400-W solar panels in the same environment and conditions. In the systems, there are 400-W solar panels, a solar tracker actuator, a 600-W solar inverter, a 20-A solar charge controller, Arduino software and circuit elements used to control the tracking system, an analyser to measure energy, and LDR sensors to track the position of the sun. Chapter 2 provides detailed information on these materials.

In this study, the aim was to benefit more from solar energy and increase its efficiency in electricity production, and in this direction, systems were installed in the Adana province (Seyhan district, Zeytinli neighborhood) between the 4 and 10 September 2021, and production data were obtained. The geographical coordinates of the region where the systems are installed are 36°59′20.8″ N 35°09′55.1″ E. Since the first of these 3 systems is a fixed system, a solar panel was mounted on a fixed carrier, and measurements were taken with the help of an inverter and charge controller. In the second system, the movement of the panel in the east and west directions is provided with the help of the mechanical part mounted on the carrier and the solar tracking actuator (linear motor). With the aid of mechanical equipment specifically created for this system and two solar tracker actuators, the third system offers the ability to move under the sun in the east, west, and north-south directions. These motion systems are specially written and controlled with Arduino.

With the applied study, it has been revealed that more electricity production can be achieved from solar energy systems by using the sun more efficiently. In this study, three different systems were compared; the most efficient system and production differences in percentage were stated. In light of all these data, it is thought that the tracker system would be more suitable for the solar power plants planned to be built in the Çukurova region, where the study was conducted, instead of the fixed system. Between the tracker systems, there is a 7% difference between the production obtained from the dual-axis system and the production obtained from the single-axis system. Since this production difference will be insufficient to cover the cost that will occur if dual-axis systems are preferred, it has been suggested that the preference be used in favor of a single-axis system.

Since the land structure of the Çukurova region is mostly flat, the installation and operation of single-axis systems for the planned solar power plants will be easy. It is advisable to modify the existing roof models used in industrial zones in order to accommodate the installation of solar tracking systems, taking into account the appropriate roof angles.

2.1. Parameters of the Material of the Solar Tracking System

Various materials were used in the solar tracking system, which was installed as portable and where application data were obtained. A solar charge controller is used to regulate the voltage and current coming from the solar panels in the solar energy systems we have installed. Datasheet data for this device are given in

Table 1. Solar charge controller parameters used in the solar tracking system.

Electrical Parameters
Maximum Working Current	20 A
System Voltage	12 V/24 V
Battery Max. Charging Voltage	13.7 V/27.4 V
Battery Low Voltage Protection	10.7 V/21.4 V

. Solar panels were used to generate electrical energy in the compared solar energy systems. The electrical data of the solar panels used are given in

Table 2. Panel electrical parameters used in the solar tracking system.

Electrical Characteristics
Module
Maximum Power at STC (Pmax)	380 W	400 W	405 W
Open-Circuit Voltage (Voc)	48.3 V	48.7 V	48.8 V
Short-Circuit Current (Isc)	10.3 A	10.8 A	10.9 A
Optimum Operating Voltage (Vmp)	39.9 V	40.7 V	40.9 V
Optimum Operating Current (Imp)	9.55 A	9.84 A	9.91 A
Module Efficiency	18.9%	19.9%	20.1%
Power Tolerance	0~+5 W
Maximum System Voltage	1000 V/1500 V DC
Maximum Series Fuse Rating	15/20 A

, and the mechanical data are given in

Table 3. Panel mechanical parameters used in the solar tracking system.

Mechanical Characteristics
Solar Cells	Monocrystalline 158.75 × 158.75 mm
No.of Cells	72 (6 × 12)
Dimensions	2008 mm × 1002 mm × 35 mm
Weight	22.5 kg
Front Glass	High-transmission tempered glass
Frame	Anodized aluminium alloy
Junction Box	IP68
Cable	4 mm2 (UL/IEC) Length: 1200 mm
Connectors	MC4 Compatible
Packaging Configuration	30 pcs/box, 715 pcs/40′HQ Container

. Electronic devices called inverters are used to convert the DC energy produced in solar energy systems established to produce electrical energy to AC energy. The parameter data of the inverters used in these systems are given in

Table 4. Inverter parameters used in solar tracking systems.

Electrical Characteristics
Normal Output Power:	600 W
Continuous Output Power	600 W
Maximum Power	1200 W
Normal Input Volt	12 V DC/24 V DC
Normal Output Volts	220 V AC
Frequency	50 Hz
Output Layout	±5%
Sine Output	Modified Sinus
Voltage Alarm Range	10.5 +/− 0.5 V
Cut-off Voltage Range	10.5 +/− 0.5 V
Efficiency Ratio	85–90%
Heat Preservation	65 C +/− 5 C
Short Circuit Protection	Available
Insurance Protection	Available
Short Circuit Protection	Available

. The main logic of the solar tracking system is to move the panels. Various engine groups can be preferred for this process. The data sheet data of the linear motor preferred in this study are given in

Table 5. Linear motor parameters used in solar tracking system.

Datasheet of Linear Motor
Main application	Industrial, Solar tracker
Input voltage	12 V DC/24 V DC
Rated load	7000 N
Max. static load	17,100 N
Max. dynamic load	9000 N
Max. the speed at no load	5.5 mm/s
Max. the speed at full load	4.4 mm/s
Power cord length	250 mm (with tinned wires)
Ambient operation temperature	−25 °C~+65 °C

.

LDR Sensor

“Light sensitive resistor (LDR)”, one of the basic components of light sensors, is a passive circuit element that detects the light falling on it or the environment and changes the resistance values according to the intensity of the light. LDR, which is also used as a photoresistor, functions almost the same as the photodiodes and phototransistors found in the sensors. However, it differs from them in structure. LDR is passive and causes a change in resistance as a result of light detection. In photodiodes and phototransistors, light perception is achieved with the help of pn junctions.

Since LDRs are sensitive to light, their resistance values in the dark are very high and are in the MΩ range. According to the applied light intensity, the resistance values decrease nonlinearly and regress to kΩ levels.

Each semiconductor material used in LDR has its wavelength sensitivity to light. If the applied light is not in the wavelength sensitivity range of the material, there is no change in the resistance value. Therefore, the wavelength range of the light and the amount of resistance change of each semiconductor material are different. Figure 1 presents the change in resistance according to light intensity.

2.2. Meteorological Data

Detailed information about the meteorological data in the Seyhan district of Adana province, where the portable system prepared for the application was established, is given in Figure 2 and Figure 3,

Table 6. Temperature, precipitation, and wind parameters for September 2021 spanning many years compared with values.

Temperature (°C)						Precipitation (mm)				Wind (m/s)
Long Year Average	Last Month Average	Long Year Maximum	Last Month Maximum	Long Year Minimum	Last Month Minimum	Long Year Months Average	Last Month Total	Long Year Maximum	Last Month Maximum	Long Year Maximum	Last Month Maximum
25.8	27.2	43.2	37.3	9.3	17.1	17.1	0	129	0	25.5	9.8

and

Table 7. Meteorological Data for September 2021.

Meteorological Data for September 2021
Day	Temperature Maximum	Temperature Minimum	Precipitation Probability (%)	Humidity (%)	Wind (km/h)
1	32	25	0	50	21
2	33	25	0	46	21
3	32	25	10	47	19
4	32	25	0	43	21
5	32	25	10	46	20
6	32	25	0	46	19
7	32	25	0	46	19
8	32	25	10	46	18
9	32	25	10	46	19
10	33	24	0	43	21
11	32	25	0	46	19
12	32	25	0	50	21
13	31	24	0	54	20
14	31	24	10	41	19
15	31	24	10	50	20
16	31	24	20	54	19
17	30	24	20	55	19
18	30	24	10	51	19
19	30	23	20	51	18
20	29	23	30	55	19
21	29	23	40	54	19
22	29	22	20	52	19
23	29	23	30	50	15
24	29	23	0	43	17
25	29	23	10	44	16
26	29	23	10	50	15
27	28	23	10	57	18
28	29	22	10	43	19
29	29	23	10	43	18
30	29	22	10	38	18

. The geographical coordinates of the region where the systems are installed are 36°59′20.8″ N 35°09′55.1″ E. The sunshine timetable and radiation distribution are given below.

2.3. Mathematical Modelling of the Solar Tracker System

First, the parts to be used for the system where the application will be made were created, and the materials were prepared. The materials to be used are mathematically modelled so that the data are correct and valid. These models are calculated and explained separately for each part.

2.3.1. Modelling of Sunlight Absorb Sensors

In this project, the movement of the sun is ensured by using LDR sensors that detect sunlight. The voltages of light shining on these sensors were likewise altered by employing their voltage divider circuits. The following is a definition of the radiation-dependent variation of an LDR sensor coupled to a voltage divider circuit [35]:

$$V_{LDR}=V_g\frac{R}{R+R_{LDR}{G}_{LDR}}$$

(1)

In Equation (1), VLDR is the sensor’s output voltage, V_g is the voltage divider’s input voltage, and R is the circuit’s series resistance. The effective radiation levels hitting the sensor are R_LDR, sensor resistance, and G_LDR. The radiation value falling perpendicular to the sensor surface is referred to as the effective radiation value falling on the sensor. The data relating to the calculation of the effective radiation value are given in Equation (2) [35].

$$G_{LDRi}=G*\cos [\alpha -(\theta -{\beta }_i)]i=1,2$$

(2)

2.3.2. Sun Angle Modelling

The relationship between the sun’s angle and the PV panel in this model is [35].

$$\alpha =\gamma *t+\varphi$$

(3)

Equation (3) denotes the angle that the sun makes with the PV panel, $\gamma$ denotes the sun’s change in angle over one second, t denotes the system time (at one-second intervals), and $\varphi$ denotes the sun’s initial angle.

2.3.3. Effective Radiation Modelling

Correctly detecting the sun’s rays will ensure that the movement of the panel works correctly. For this purpose, solar modelling is very important. To correctly perceive the movement of the sun throughout the day, it is very important to correctly transfer the radiation from the sun to the control part of the information. In short, correctly estimating the movement of the sun throughout the day will ensure that the panel follows the sun correctly. This will directly affect the production data. Equation (4) may be used to obtain the effective radiation value that is generated by the radiation value acquired from the solar model on the panel [35].

$$G_{PV\_panel}=G*\cos (\alpha -\theta )$$

(4)

3. Performance Analysis

To maximize energy production by making more use of solar energy, three different portables have been created to figure out which system is the most accurate. The first is the fixed system where no movement has taken place, the second is the single-axis tracker system moving in the east and west directions, and the last is the dual-axis tracker system moving in the east–west and north–south directions. An LDR sensor, a linear motor, and Arduino software were used to provide the movement of the second and third systems. With the help of the software written with Arduino, attempts have been made to ensure that the panels produce more energy by tracking the sun through the information received from the LDR sensors. The size information of the designed systems is shown in

Table 8. Dimensions of portable systems.

System Name	Weight (kg)	Height (cm)	Dimensions of Panel (cm)
Fixed System	24	158	202 × 102
Single Axis System	39	158	202 × 102
Double Axis System	51	158	202 × 102

.

The systems were created for comparison; first, three identical 400-W solar panels were arranged. For the positioning of these panels, three mechanical materials consisting of legs and stands were arranged. Figure 4 presents the experimental view of the solar tracker system. In Figure 4a, the general view of the system covering all the equipment is shown. In Figure 4b, the mechanical part of the system prepared as a dual-axis is shown. Figure 4c shows the mechanical parts of the single-axis system. Afterward, linear mounting was made to two of the systems for the operation of the system, which we call the solar tracker. A single motor was installed on the system, which was considered a single-axis solar tracker, and two linear motors were mounted on the system, which was considered a dual-axis solar tracker. LDR sensors used to determine the angle of the sun were installed in two systems considered for solar trackers. Two LDR sensors, north and south for the single-axis solar tracker system, and four LDR sensors, north, south, west and east for the dual-axis LDR system, were installed. Figure 5 presents the control and mechanical parts used in the solar tracker system. In Figure 5a, linear motor label information, Figure 5b LDR sensor connection type and location, Figure 5c linear motor mechanical connection type, Figure 5d Arduino board connection type, Figure 5e the connection type and general view of the control unit and Figure 5f the general view of the energy meters are shown.

The three prepared systems were moved to their predetermined locations and fixed so that they would not cast shadows on each other. For each of them, the cables of the panels were connected and assembled. The energy cables of the panels were first connected to the solar charger, then from the solar charger to the solar inverter, and lastly, from the inverter to the consumption point. A connection was made from the inverter output to the energy analyser with the help of current transformers, and thus, the production data were followed with the help of the analyser. The LDR sensors used for the two systems with the mobile system were connected to the digital inputs of the Arduino UNO card. Thus, the LDR sensor transferred the data it received from the movement of the sun to the Arduino. These data allowed Arduino to enable the panel to follow the sun by changing the direction and giving output to linear motors. Calculations of LDR sensor data coming through the Arduino IDE software were made, and outputs were adjusted to ensure correct movement. Since the Arduino UNO board can give 5 V as an output, 5-V relays are used to supply 36 V to the motors through the power supply. The relays, which give output according to 5 V coming from the Arduino, provide the movement by pulling a 24-V relay through which a 36-V supply passes. To provide the supply voltage of the motors, a power supply with a 220-V input supply and 36-V output is used. Thus, as a result of the data coming from the LDR sensor, the solar tracking system was operated by running linear motors thanks to the Arduino software written specifically for this system.

The next step in the operation of the system was the monitoring of production data. Daily production data were taken at the same time each day from each analyser in the three systems shown in

Table 9. Production data of three portable systems installed.

400 W PHOTOVOLTAIC SOLAR PANEL SYSTEMS
Date	Fixed System (W)	Single Axis System (W)	Double Axis System (W)	Single %	Double %
10.09.2021	1503.47	1867.67	1976.60	24.224	31.469
11.09.2021	1476.65	1839.23	1955.17	24.554	32.406
12.09.2021	1482.64	1842.79	1953.76	24.291	31.776
13.09.2021	1515.77	1872.29	1992.76	23.521	31.468
14.09.2021	1421.13	1759.55	1866.50	23.813	31.339
15.09.2021	1748.26	2185.26	2321.37	24.996	32.782
16.09.2021	1942.27	2421.56	2567.29	24.677	32.180
17.09.2021	2073.18	2591.59	2751.05	25.006	32.697
18.09.2021	2062.14	2580.07	2747.17	25.116	33.219
19.09.2021	1948.26	2428.53	2587.35	24.651	32.803
20.09.2021	1915.45	2403.95	2562.54	25.503	33.783
21.09.2021	1864.35	2308.42	2453.48	23.819	31.600
22.09.2021	1218.29	1500.79	1601.60	23.188	31.463
23.09.2021	1472.87	1819.91	1941.89	23.562	31.844
24.09.2021	2144.16	2674.28	2849.08	24.724	32.876
Total	25,788.89	32,095.89	34,127.61	24.376	32.247

, and these data were recorded. The records were then used to compare the efficiency of the three systems.

The production data of the three solar systems installed were recorded for 15 days. The recordings were taken daily and simultaneously at the same time each day. The data relating to the records received are shown in Figure 6 and Figure 7.

3.1. Cost Analysis of Solar Tracker Systems

To make a more accurate comparison between the portable sun tracker systems, a cost analysis and study on how much budget should be allocated for each system were completed. Cost analysis was created by pricing the data taken from the production data of these budgets. In particular, a comparison of the prices for the two proposed and studied tracker systems will help future studies in making the right choice. The quantities and prices of the materials used in the installed systems are explained in

Table 10. Cost analysis of the fixed system.

Cost Analysis of Fixed System
Material Name	Number	Unit	Price ($)
400 Watt Panel	1	number	315
Mechanical Parts	1	number	75
Linear Motor	0	number	0
LDR Sensor	0	number	0
Arduino Uno	0	number	0
Energy Analyser	1	number	25
Solar Charge Controller	1	number	30
Solar Inverter	1	number	72
Cable	10	meter	5
Solar Gel Battery	1	number	59
Total			581

,

Table 11. Cost analysis of a single-axis tracker system.

Cost Analysis of Single Axis Tracker System
Material Name	Number	Unit	Price ($)
400 Watt Panel	1	number	315
Mechanical Parts	1	number	75
Linear Motor	1	number	180
LDR Sensor	2	number	0.2
Arduino Uno	1	number	15
Energy Analyser	1	number	25
Solar Charge Controller	1	number	30
Solar Inverter	1	number	72
Cable	10	meter	5
Solar Gel Battery	1	number	59
		Total	776.2

and

Table 12. Cost analysis of the double-axis tracker system.

Cost Analysis of Double Axis Tracker System
Material Name	Number	Unit	Price ($)
400 Watt Panel	1	number	315
Mechanical Parts	1	number	75
Linear Motor	2	number	360
LDR Sensor	4	number	0,4
Arduino Uno	1	number	15
Energy Analyser	1	number	25
Solar Charge Controller	1	number	30
Solar Inverter	1	number	72
Cable	15	meter	7
Solar Gel Battery	1	number	59
		Total	958.4

. In the cost analysis calculations made during the period when the system was operating, the unit price of electricity was accepted as 0.16 cents in kWh. Comparative analyses are shown in

Table 13. Total gains of the systems.

Systems	15 Days Production (kW)	Unit Price ($/kW)	Total Profit ($)
Fixed System	25.788	0.16	4.13
Single Axis System	32.095	0.16	5.14
Double Axis System	34.127	0.16	5.46

,

Table 14. Installation cost comparison of tracker systems with a fixed system.

Systems	Installation Cost	Difference	Ratio
Fixed System	581	---	---
Single Axis System	776.2	195.2	25.15
Double Axis System	958.4	377.4	39.38

and

Table 15. Installation cost comparison of a single-axis tracker system with a dual-axis tracker system.

Systems	Installation Cost	Difference	Ratio
Single Axis System	776.2	---	---
Double Axis System	958.4	182.2	19.01

.

Table 16. Depreciation analysis of systems.

Systems	Annual Gain (year/$)	Installation Cost ($)	Depreciation Period (year)
Fixed System	99.03	581	5.87
Single Axis System	123.24	771.2	6.26
Double Axis System	131.05	963.4	7.35

shows the findings of the analysis, which show that the single-axis tracker system pays for itself 0.39 years later than the fixed system, and the double-axis system does so 1.48 years later. The single-axis system will be more lucrative and effective than the fixed system, according to this analysis. The amortization period of the dual-axis system is 18% longer than that of the fixed system. When choosing between two-tracker systems, it is recommended that the decision be made according to the feasibility study to be conducted at the locations where the power plants will be established.

3.2. Performance of the Solar Tracking System

The performances of the three different systems that were applied were analysed with the method explained below, and it was stated that the actual results and the calculated results were close to each other.

The EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) produced the initial edition of the SARAH solar radiation data record from which the PVGIS-SARAH solar radiation data made accessible here were generated [36]. The two primary ways that PVGIS-SARAH differs from the CM SAF SARAH data record are that it uses photos from two METEOSAT geostationary satellites that encompass Europe, Africa, and Asia (0° and 57° E) and that it derives its hourly values from a single satellite image. We are also supplying PV-specific data records, such as the irradiance on ideally sloped surfaces, in addition to the data supplied by CM SAF.

The productions of the three applied systems were measured and analysed in detail. As a result of this analysis, the fixed-axis solar energy system production data are shown in Figure 8. Production data and comparison of single and dual-axis tracking systems are shown in Figure 9.

4. Discussion

The demand for cleaner and environmentally friendly energy production is increasing for the electricity generated from solar energy. Obtaining maximum efficiency from solar energy is important in terms of sustainability. Because fixed-angle solar panels are unable to utilize solar energy effectively, it is challenging to achieve optimum efficiency. Some studies have been initiated to obtain more energy from established solar power plants. Solar tracking systems are at the forefront of these studies. Thanks to this system, which enables more electricity to be produced by following the sun all day long, more instantaneous electricity is produced from the same installed power plant. Developing technology has made it possible to work more efficiently in energy production.

In this study, solar tracking systems developed to keep the electrical energy produced from solar energy panels at the maximum level were compared. Three different systems have been established. The first system installed is the fixed solar energy system, the second is the single-axis solar tracking system moving between the east and west direction, and the third is the dual-axis solar tracking system moving between the east and west direction and the north and south directions. These systems are placed in the same place as the switchboards with the same conditions and characteristics. The production data of 15 days were taken from these panels and compared. Production gains were compared by calculating the installation costs, and how long it took the systems to pay for themselves was analysed. The results of the analysis helped to choose the most suitable system among the systems. The production rates resulting from these results are shown in

Table 17. Comparison of production data.

Systems	Annual Production (Kw)	Difference	Difference Ratio
Fixed System	53.78	---	---
Single Axis System	72.34	18.56	25.65
Double Axis System	79.00	25.22	31.92

. The results obtained are examined in light of this information;

Table 18. Comparison of Portable systems with PVGIS-SARAH.

Systems	Production Ratio of Portable Systems	Production Ratio of PVGIS-SARAH
Fixed System	---	---
Single Axis System	24.38	25.66
Double Axis System	32.25	31.92

shows that the actual measured values and the values obtained as a result of the analysis are close to each other. Depreciation data of the installed systems are shared in Table 16 and explained in detail in the cost analysis section.

They compared the efficiency obtained from the single-axis solar tracking system and the fixed plate system in their study, where they designed and implemented a dual-axis solar tracker. The results of their study, in which four LDR sensors, Arduino as a microcontroller (controller) and a motor as an actuator are used, contain values parallel to the results of this study. They stated that the solar tracking system has an efficiency difference of 30–40% compared to the fixed systems [37]. In this study, it can be clearly seen that solar tracking systems are more efficient than fixed systems. This result is also supported by literature studies. Considering the application life of the solar energy system, it was emphasized that the financial burden brought by the tracking system to the existing system is not very important. It has been demonstrated by the application data that the single-axis system is 24–25% more efficient than fixed systems and dual -axis system 32–33% more efficient than fixed systems.

5. Conclusions

In this study, solar tracking systems developed to keep the electrical energy produced from solar energy panels at the maximum level were compared. Three different systems have been established. The first installed system is a fixed solar energy system; the second is a single-axis solar tracking system that moves from east to west; the third is a double-axis solar tracking system that moves from east to west and from north to south directions. Production data from 15 days were taken from these panels and compared. Production gains were compared by calculating the installation costs, and how long it took the systems to pay for themselves was analysed. The results of the analysis helped to choose the most suitable system among the systems. Thus, some results emerged from a comparison of the data obtained. The results of these studies are presented below:

✓

The study emphasized the importance of solar energy, a renewable energy source, which is characterized as environmentally friendly, sustainable and clean energy, instead of fossil fuels that harm the environment. Systems that will obtain more efficiency from solar energy have been designed and contributed to their sustainability.

✓

When the energy production of the installed systems is compared to the fixed systems, it is seen that the single-axis solar tracking system produces 24.367% more electricity, and the dual-axis solar tracking system produces 32.247% more electricity.

✓

Comparing several solar tracking systems reveals that the dual-axis system generates 7.871% more power than the single-axis system.

✓

It has been observed that the installation and operation of the solar tracking system do not require additional load compared to normal fixed systems.

✓

Thanks to smart control, accurate sun tracking was performed with the production results.

✓

It has been calculated that the single-axis tracking system pays for itself 0.39 years after the fixed system and 1.48 years after the dual-axis system. As a result of this analysis, it has been seen that the uniaxial system is more profitable and efficient than the fixed system. The amortization period of the biaxial system is 18% longer than that of the fixed system. It was stated that when choosing between biaxial tracking systems, the decision should be made according to feasibility studies to be conducted at the locations where the power plants will be established.

As a result of this study, there will be an increase in the amount of energy produced from solar energy, which is environmentally friendly and clean energy; this will increase the interest in solar energy and provide ease of investment thanks to the solar tracking device. This study, which will contribute to the sustainability of nature, will encourage the use of clean energy. Thus, the number of solar power plants will increase, and the use of fossil fuels will decrease; therefore, the damage to the environment will also decrease.

Future studies should be carried out to reduce the installation costs of uniaxial and biaxial systems and to make more sample applications to eliminate fixed systems.