EduSolar: A Remote-Controlled Photovoltaic/Thermal Educational Lab with Integrated Daylight Simulation

Abstract

This study presents a compact educational photovoltaic/thermal (PV/T) system designed for thorough performance assessment under simulated weather conditions. As an affordable educational tool, the system offers significant pedagogical value. The PV/T system features two photovoltaic modules: a thermally enhanced module and a standard one. The thermally enhanced module uses water as a coolant, which transfers heat from the PV cells to a fan-operated heat exchanger, with the coolant being recirculated to maintain optimal conditions. A halogen lamp, placed between the modules, simulates solar radiation to ensure effective electrical current generation. The system’s remote-control capabilities, managed via the Message Queuing Telemetry Transport (MQTT) protocol, enable real-time adjustments to the coolant flow rate, heat exchanger efficiency, and lamp brightness, as well as monitoring of electrical parameters. Experimental findings indicate that the PV/T module achieves a 7.71% increase in power output compared to the standard PV module and offers a 17.41% improvement in cooling efficiency over scenarios without cooling. Additionally, the numerical methods used in the study show a maximum deviation of 4.29% from the experimental results, which is considered acceptable. This study showcases a best practice model for solar training, applicable from elementary to university levels, and suggests innovative approaches to enhancing solar energy education.

1. Introduction

The increasing demand for efficient and sustainable energy solutions underscores the necessity for advanced educational tools to proficiently illustrate the principles and performance metrics of photovoltaic (PV) and photovoltaic/thermal (PV/T) systems. Solar energy, as a pivotal component of modern energy strategies, offers a renewable and environmentally friendly alternative to fossil fuels [1]. PV systems convert sunlight directly into electricity, providing a clean energy source that reduces greenhouse gas emissions. PV/T systems, on the other hand, combine photovoltaic and thermal technologies to simultaneously generate electricity and capture thermal energy, thereby enhancing the overall efficiency and utility of solar installations. These hybrid systems not only maximize the energy harvested from solar radiation but also address thermal management issues, which can significantly improve the electrical performance of PV modules [2,3].

Chala and Al Alshaikh emphasize the promising role of solar photovoltaic energy in the future energy mix, highlighting its potential to significantly increase the share of clean energy sources [4]. They also discuss the advancements in PV technologies, including the integration with thermal systems to form PV/T setups, which offer enhanced energy output and improved system efficiency.

Despite these advancements, traditional educational resources often fail to accurately simulate real-world conditions, hindering students’ and professionals’ comprehensive understanding of these systems’ dynamic behaviors and operational intricacies [5]. This limitation is further compounded by the lack of practical, hands-on educational tools that simulate real-world PV system conditions and by insufficient focus on the thermal management of PV modules in educational settings. Most previous studies have concentrated on large-scale systems, leaving a gap in research on lab-scale PV/T systems and their performance under various cooling scenarios [6,7].

Recent advancements in solar simulation technology have aimed to address these limitations. Solar simulators with halogen lamps are crucial in PV system research, providing consistent and controlled testing environments that mimic natural sunlight. Namin et al. constructed a hybrid solar simulator utilizing tungsten halogen and LED lamps, effectively characterizing solar cells and determining their electrical parameters [8]. Similarly, Soetedjo et al. developed a halogen lamp-based solar simulator for measuring the I-V characteristics of PV modules, offering a flexible testing solution independent of natural sunlight conditions [9]. Wang and Laumert highlighted the significant role of halogen lamps in providing consistent and reliable light sources for PV module testing [10]. Uniformity and calibration in solar simulator technology are critical for accurate testing of PV systems, as detailed by Abuseada et al. [11] and Shatat et al. [12]. Sidopekso et al. designed a simple sun simulator for I-V measurements, emphasizing the necessity of uniform light distribution for accurate performance metrics in PV research [13].

Understanding the temperature dependency and efficiency of PV cells is crucial for optimizing their performance under various conditions. Grandi et al. used a hybrid LED–halogen solar simulator to study the temperature effects on PV cells, finding that halogen lamps maintained stable temperatures essential for accurate efficiency measurements [14]. Llenas and Carreras investigated arbitrary spectral matching using multi-LED lighting systems, demonstrating the significance of stable spectral measurements provided by halogen lamps for analyzing the thermal behavior of PV cells [15]. Yandri presented a dataset on PV surface temperature distribution using a halogen solar simulator, offering insights into the thermal characteristics of PV cells during electricity generation and non-generation phases [16].

Herrando et al. provide a comprehensive review of solar hybrid PV-T collectors and systems, emphasizing recent advancements and ongoing challenges in the field. This review highlights the need for more effective simulation tools and educational resources to better understand the performance and efficiency of PV/T systems [17].

Despite these advancements, significant gaps remain in existing educational tools that simulate the dynamic behavior of these systems under varying conditions. This study addresses the following gaps:

• Lack of practical, hands-on educational tools that accurately simulate real-world PV system conditions;
• Insufficient focus on the thermal management of PV modules in educational settings;
• Limited research on the performance of lab-scale PV/T systems under different cooling scenarios;
• Absence of comprehensive training models that integrate both theoretical and practical aspects of solar energy systems.

This study focuses on the design and implementation of a compact educational photovoltaic/thermal (PV/T) system, called EduSolar, capable of operating under various simulated weather conditions. The primary objective is to provide a practical, hands-on educational tool that simulates the operational conditions of PV systems, thereby enhancing comprehension and promoting innovation in solar energy applications. By exploring the performance characteristics and thermal management of PV modules in different scenarios, this research aims to improve solar energy education and training. Furthermore, this study seeks to establish a best practice model for solar training by systematically analyzing these scenarios, addressing current gaps in educational methods, and proposing innovative approaches to enhance the pedagogical effectiveness of solar energy systems.

2. Materials and Methods

2.1. Definition of the Problem

The primary objective of EduSolar is to create a practical educational tool that simulates the operational environment of PV systems, thereby enhancing understanding and fostering innovation in solar energy applications. The scenarios explored in this study, detailed in

Table 1. Physical parameters for each scenario in the present study.

Scenario	Applied Physical Condition				Measurement
	* Gmin	* Gmax	* $\dot{\mathbf{m}}$	* N
1	0	1216	0	0	${\mathrm{T}}_{\mathrm{PV}}$, ${\mathrm{T}}_{\mathrm{PV}/\mathrm{T}}$, ${\mathrm{I}}_{\mathrm{PV}}$, ${\mathrm{I}}_{\mathrm{PV}/\mathrm{T}}$, ${\mathrm{V}}_{\mathrm{PV}}$, ${\mathrm{V}}_{\mathrm{PV}/\mathrm{T}}$
2	0	1216	0.22	3000
3	0	1216	0.11	1500

* ${\mathrm{G}}_{\min }$ and ${\mathrm{G}}_{\max }$ are measured in $\mathrm{W}/{\mathrm{m}}^2$, $\dot{\mathrm{m}}$ is measured in kg/s, and N is measured in RPM.

, aim to offer comprehensive insights into the performance characteristics of PV modules under different conditions, ultimately contributing to more effective solar energy education and training.

The study uses a consistent experimental setup for both PV and PV/T experiments to ensure comparability. The setup includes a halogen lamp to simulate daylight irradiation, with irradiance (G) fluctuating between its minimum ($G_{min}$) and maximum ($G_{max}$) values. In the initial scenario, no cooling system is employed, and the irradiance is adjusted every 20 ms to simulate a complete daylight cycle over 8 min. Each scenario encompasses a total of four cycles to examine the system’s behavior in detail.

In the second scenario, daylight irradiation is simulated with the cooling system functioning at maximum capacity, while the third scenario involves daylight irradiation with the cooling system operating at half capacity. During each experiment, the temperature (°C), current (A), and voltage (V) values of both PV and PV/T modules are recorded at high frequency using a data acquisition system. Data collection is carried out using the MQTT (Message Queuing Telemetry Transport) protocol, allowing for real-time monitoring and automatic logging of sensor data to the computer. Sensors are strategically placed to measure temperature and electrical parameters, ensuring precise and continuous data collection.

Table 1 summarizes the physical parameters applied in each scenario. This comprehensive approach ensures that the experiments are conducted under controlled and repeatable conditions, allowing for accurate comparisons between the PV and PV/T systems.

The study has several limitations, including its reliance on a small-sized educational PV/T system, which may not fully capture the complexities of large-scale PV installations. It also overlooks critical environmental factors such as ambient temperature, humidity, wind speed, and dust accumulation, which can significantly affect PV performance in real-world settings. The simulated irradiance used may not perfectly simulate natural sunlight, potentially impacting result accuracy. Additionally, the cooling system’s fixed operational parameters limit insights into its full performance range, and the long-term degradation of PV modules is not considered. Variations in the angle of sunlight, which influence PV efficiency, are also not addressed. The study does not explore the economic and practical constraints of scaling up findings to real-world applications, and results may not be generalizable to all geographic locations and climates. These limitations highlight the need for future research to incorporate more complex environmental conditions, variable operational parameters, and long-term degradation effects for a more comprehensive understanding of PV and PV/T system performance.

To address the educational needs in solar energy systems, the study is designed with the following objectives:

• Educational Tool Development: To create a practical, small-sized educational setup that simulates real-world operating conditions, providing a hands-on learning experience for students;
• Dynamic System Analysis: To explore how different environmental conditions and cooling strategies impact the performance of PV and PV/T systems, thereby enhancing students’ understanding of system behavior under varying conditions;
• Data Analysis Skills: To enable students to collect, analyze, and interpret experimental data, fostering critical thinking and data analysis skills;
• Best Practices for Solar Education: To establish best practices for incorporating practical, hands-on experiences into solar energy education, improving the quality and effectiveness of training programs.

By conducting these experiments, EduSolar aims to offer a detailed understanding of how cooling affects PV performance, the importance of thermal management, and how various conditions impact system behavior. This approach will provide valuable insights into the real-world application of PV and PV/T systems, focusing on how cooling systems enhance the electrical performance of PV/T modules, rather than thermal efficiency.

2.2. Pedagogical Activities in EduSolar

Table 1 outlines the physical parameters for each scenario in this study, as detailed in the previous subsection. Based on these scenarios, the following pedagogical activities are designed to enhance user understanding and engagement with the EduSolar system, providing opportunities to develop various technical and analytical skills.

• Basic System Operation and Familiarization:
  • Objective: Understand the basic components and operation of the PV/T system.
  • Activity: Identify and describe the function of each component, including PV modules, sensors, and control units. Conduct a walk-through of system startup and shutdown procedures.
  • Skills Gained: System familiarization, technical vocabulary, and basic operational skills.
• Performance Analysis Under Varying Conditions:
  • Objective: Understand the influence of varying irradiance levels and analyze the power output and efficiency of PV/T systems.
  • Activities:

    (a)

    Use the halogen lamp to simulate different irradiance conditions and record the system’s response. Focus on analyzing how changes in irradiance affect the system’s performance.

    (b)

    Measure and record the power output of both PV and PV/T systems under various simulated sunlight conditions. Compare the efficiency of the PV and PV/T modules and discuss factors influencing their performance.

  • Skills Gained: Environmental simulation, data interpretation, problem-solving, data collection, efficiency calculation, critical thinking, comparative analysis.
• Remote Monitoring and Control:
  • Objective: Explore the remote operation of PV/T systems.
  • Activity: Use the MQTT protocol to monitor system performance remotely. Practice adjusting operational parameters like cooling rate and lamp intensity to observe changes in real-time data.
  • Skills Gained: Remote monitoring, real-time data analysis, IoT skills, control systems management.
• Numerical Modeling and Prediction:
  • Objective: Use numerical methods to predict system performance.
  • Activity: Apply the study’s numerical models to predict power output and efficiency. Compare these predictions with experimental results to assess model accuracy and understand the deviations.
  • Skills Gained: Numerical modeling, prediction analysis, accuracy assessment.

These activities are designed to provide a comprehensive learning experience, equipping users with the necessary skills to effectively operate and analyze PV/T systems. Furthermore, this study is pedagogically planned to ensure that learners not only gain technical knowledge but also develop critical thinking and problem-solving skills, which are essential for advancing in the field of renewable energy.

2.3. System Design and Setup

The system primarily consists of two photovoltaic modules—one standard and one with thermal enhancement—a halogen lamp to simulate solar radiation, a cooling system, and a water-cooled radiator. The thermally enhanced module features a water-cooled radiator designed to capture and utilize the waste heat produced during the conversion of solar radiation into electricity.

The operational principles of the system are depicted in Figure 1 and summarized in

Table 2. Technical specifications of the components.

Component	Specification
PV Module	L × W: 0.09 × 0.06 m, ${\mathrm{P}}_{\mathrm{nom}}$: 1.32 W
Halogen Lamp	${\mathrm{P}}_{\mathrm{nom}}$: 55 W, ${\mathrm{P}}_{\mathrm{supp}}$: DC 12 V, $\mathrm{\Phi }$: 1450 lumen (±15%)
Water Pump	${\mathrm{P}}_{\mathrm{supp}}$: DC 12 V, $\dot{\mathrm{m}}$: 0.22 kg/s
Water-cooling Radiator	Aluminum, double-layer 24 pipes
Fan	${\mathrm{P}}_{\mathrm{supp}}$: DC 12 V, 3000 RPM, L × W × H: 0.12 × 0.12 × 0.025 m
Reservoir	L x W × H: 0.2 × 0.15 × 0.05 m

. The system is divided into two main components: the solar photovoltaic (PV) system and the cooling system. The solar PV system is powered by a cost-effective 55W halogen lamp, which provides a luminous flux of 1450 lumens with a tolerance of ±15%. Each photovoltaic module measures 6 cm by 9 cm and has a nominal power output of 1.32W under standard test conditions (1000 W/m² and 25 °C). The cooling system is driven by a water pump with a maximum mass flow rate of 0.22 kg/s. A serpentine-type water channel is positioned behind the PV module, where the coolant absorbs heat and transfers it to a water-cooling radiator. This radiator has a double-layer design with 24 channels and includes a fan capable of operating at a maximum speed of 3000 RPM.

In operation, the coolant first flows from the reservoir to the water-cooling radiator through the water pump, as shown in Figure 1. The cooled refrigerant fluid then enters the cooling channel within the PV module. After absorbing heat from the PV module, the coolant returns to the reservoir, completing the cycle.

The electrical diagram of the system is illustrated in Figure 2 and summarized in

Table 3. Technical specifications of the components.

Component	Subject	Specification
Voltage divider circuit	Power meter	${\mathrm{R}}_1$: 360 $\mathrm{\Omega }$, ${\mathrm{R}}_2$: 10k $\mathrm{\Omega }$, ${\mathrm{R}}_3$: 1k $\mathrm{\Omega }$ (±15%)
DS18B20	Temperature reading	$V_{cc}$: 3 to 5 V, Precision: 0.5% (−10 to +85 °C), Range: −55 to +125 °C
CC 10A SH-MD10	Driver	${\mathrm{V}}_{\mathrm{cc}}$: 7 to 30 V, ${\mathrm{I}}_{\max }$: 10 A, Logical levels: 3.3–5 V
ESP32	Microcontroller	Resolution: 12 bits, Frequency: 240 MHz

. The system is primarily controlled by an ESP32 microcontroller (Espressif Systems, Shanghai, China), which manages the overall operation. Two DS18B20 temperature sensors (Maxim Integrated, San Jose, CA, USA) are used to measure the temperature of both the PV and PV/T modules, ensuring precise thermal condition monitoring. Custom-designed voltage divider circuits are implemented to measure the open-circuit voltage and short-circuit current of the PV and PV/T modules, providing accurate electrical performance data.

The electrical performance of the modules is evaluated using an electrical load with a resistance value of 360 $\mathrm{\Omega }$ ($R_1$ – ±15%), ensuring consistent and reliable measurement conditions. The operation of the halogen lamp, fan, and water pump is controlled through three CC 10 A SH-MD10 motor drivers (Cytron Technologies, Penang, Malaysia), which provide efficient and stable control of these components. This integrated approach allows for comprehensive monitoring and control, enhancing the system’s overall efficiency and reliability.

The provided diagram (Figure 3) depicts a system architecture for monitoring and controlling a photovoltaic/thermal (PV/T) system using the MQTT (Message Queuing Telemetry Transport) protocol. The system includes sensors connected to a microcontroller, which functions as a MQTT client. This client transmits sensor data to a MQTT broker via a local area network (LAN) or the Internet. The MQTT broker acts as the central hub, receiving data from the microcontroller and distributing it to other MQTT clients, such as the experimenter’s device [18]. The experimenter, also connected via LAN or the Internet, can monitor the system’s performance and make real-time adjustments using the MQTT client interface. This configuration allows for efficient and flexible management of the PV/T system, ensuring accurate data transmission and effective implementation of control commands, thereby facilitating comprehensive analysis and optimization of the system under various simulated conditions.

2.4. Numerical Modeling

In this subsection, the authors present the numerical approach used in this study, which includes two modeling strategies: system efficiency correlations and the simulation of solar radiation.

2.4.1. System Efficiency and Power Correlations

Equation (1) models how the efficiency of a PV cell varies with temperature relative to a reference condition [19]. Generally, the efficiency of PV cells decreases as temperature increases. ${\eta }_{PV}$ is described as

$${\eta }_{PV}={\eta }_{ref}\left[1-{\beta }_{PV}\left(T_{PV}-T_{ref}\right)\right],$$

(1)

${\eta }_{ref}$ is the efficiency of the PV cell measured at the reference temperature, representing its performance under ideal conditions. ${\beta }_{PV}$ is a coefficient that indicates how temperature affects the PV cell’s efficiency. It is negative, meaning efficiency decreases with increasing temperature [20]. The term $\left(T_{PV}-T_{ref}\right)$ represents the difference between the current operating temperature and the reference temperature and the reference temperature is 25 °C. If the PV cell operates at a temperature higher than the reference temperature, this difference is positive, leading to decreased efficiency. $P_{out}$ represents the electrical power output at the PV and PV/T modules [21]. The electrical power output, as given in Equation (2), is expressed as follows:

$$P_{out}={\eta }_{PV}\left({\alpha }_{PV}{\tau }_{gls}{I}_{solar}\right)A,$$

(2)

where $I_{solar}$ represents the solar radiation (W/m ²), and A is the PV surface area (m²). ${\alpha }_{PV}$ and ${\tau }_{gls}$ represent the absorptivity of the PV cell and transmissivity of the lamination layer of the PV cell [19,22,23]. Absorptivity and transmissivity values were assumed as 0.90 and 0.95 in the present study.

2.4.2. Modeling of Radiation Source

This subsection quantifies the efficiency of the halogen lamp in converting electrical power into luminous flux. As indicated in Table 2, the nominal power of the halogen lamp used in the present study is 55 W. For a lamp emitting light uniformly in all directions, irradiance (G) measures the light intensity falling on a surface at a specific distance (r) from the lamp, in units of W/m² [24,25]. Assuming spherical emission, irradiance is calculated using the nominal power and the inverse square law:

$$G={\displaystyle \frac{P_{nom}}{4\pi r^2}}\left({\mathrm{W}/\mathrm{m}}^2\right),$$

(3)

This determination accounts for the actual power received by each PV module exposed to the lamp’s emitted light [26]. The received power (${\mathrm{P}}_{recv}$) in units of watts (W) from the irradiance (G) on the PV module area (A), considering the conversion efficiency (${\eta }_{lamp}$) of the halogen lamp, is given by [27]:

$$P_{recv}=GA{\eta }_{lamp}\left(\mathrm{W}\right),$$

(4)

Multiplying the received power by the efficiency of the PV cell (${\eta }_{PV}$) estimates the electrical power output ($P_{PV}$) from each PV module [28]:

$$P_{PV}=P_{recv}{\eta }_{PV}\left(\mathrm{W}\right),$$

(5)

Table 4. Comparison of technical parameters for different lamps [29,30].

Criteria	Tungsten Halogen	Metal Halide	Xenon Arc
Average lifetime (hours)	35–480	1000–6100	400–3500
Colour temperature (K)	2100–3350	4000–6000	6000
Average conversion efficiency (%)	10.21	24.59	18.77

lists the technical parameters of the presented lamp types. In our study, a tungsten-type lamp is used, making the conversion efficiency an essential factor in evaluating the power reaching the PV panels. Conversion efficiency, as discussed in previous studies such as that by Tawfik et al. [29], is expressed as the percentage ratio of the radiant output power to the nominal electrical power of the lamp. This efficiency metric is crucial because it provides a clear measure of how effectively the lamp converts electrical power into usable radiant energy. Consequently, the power incident on the PV panels is also evaluated in terms of this conversion efficiency (${\eta }_{lamp}$) to ensure accurate calculations and assessments.

Therefore, in this study, the conversion efficiency (${\eta }_{lamp}$) of the tungsten-type halogen lamp is assumed to be 10%.

3. Results and Discussion

In this section, the authors begin by analysing and evaluating the experimental measurements and theoretical calculation methods used to assess the performance of PV and PV/T modules under three different irradiance levels from halogen lamps. The second subsection addresses the determination of the optimal cycle count for the experiments. Finally, the third subsection presents the experimental studies on the performance analysis of PV and PV/T modules, integrating the validated methodologies.

3.1. Verification of Performance Measurements

The verification studies were carried out under three distinct scenarios, each considering varying irradiance (G) of halogen lamps. In

Table 5. Results of the verification study for PV and PV/T module performance measurements.

G	${\mathbf{P}}_{\mathit{m}}$	${\mathbf{P}}_{\mathit{m},\mathit{lower}}$	${\mathbf{P}}_{\mathit{m},\mathit{upper}}$	${\mathbf{P}}_{\mathit{recv}}$	${\mathbf{P}}_{\mathit{PV}}$
1220	90.2	76.6	104	657	98
811	61.9	52.6	71.1	437	65
405	29.3	24.9	33.6	218	32

G is measured in units of W/m², while P is measured in units of mW.

, $P_m$ represents the measured power generation, while $P_{m,\mathrm{lower}}$ and $P_{m,\mathrm{upper}}$ denote the lower and upper tolerance limits, respectively, for the measurements within the small-size PV/T system. The results demonstrate that both the empirical measurements and the theoretical approach employed to estimate the power generation of the PV modules in this study are within the predefined tolerance range. Consequently, the outcomes of this verification study enable further investigation into both the PV and PV/T modules.

3.2. Optimal Cycle Count

During our experiments, each test was conducted over a series of 8-min cycles. For each experimental condition, we performed four cycles to ensure data reliability and stability. This subsection discusses the rationale for selecting four cycles and examines the stability of the data observed after these cycles. Our findings indicate that after the fourth cycle, no significant changes occurred in the experimental data, confirming that the chosen number of cycles was adequate for obtaining consistent and reliable measurements.

Figure 4 shows the power output and temperature over six 8-min cycles for both PV and PV/T modules. The first four cycles (Cycle 1 to Cycle 4) illustrate significant variations in the data. However, as indicated by the horizontal dashed lines and the labeled “Stable Data Region”, the data stabilize after the fourth cycle, with no significant changes observed in subsequent cycles (Cycle 5 and Cycle 6). This confirms the consistency and reliability of the measurements post the fourth cycle. Therefore, the experimental studies consist of four cycles.

3.3. Experimental Findings and Discussion

As outlined in Section 2, the experimental studies began with the evaluation of both the PV and PV/T modules under a daylight simulator without a cooling mechanism. Figure 5 illustrates the system performance during the experiment.

• Power Output: Although the PV modules are identical products, this alone does not guarantee consistent performance characteristics. This experiment helps the authors normalize the characteristics of both PV and PV/T modules relative to each other.

  −

  Cycle 1: The power output for the PV system (black line) peaks at around 75 mW, while the PV/T system (red line) reaches up to approximately 70 mW.

  −

  Cycle 2: In this cycle, the power output of both PV and PV/T modules converges, peaking at approximately 68 mW.

  −

  Cycles 3 and 4: In these cycles, the PV and PV/T systems maintain their power outputs, with both systems peaking at approximately 66 to 65 mW.

• Temperature Profiles: The temperature for the PV system (black dashed line) peaks at around 50 °C, while the PV/T system (red dashed line) peaks at approximately 40 °C. The higher temperature in the PV system compared to the PV/T system indicates that the PV/T system dissipates heat more effectively, even without active cooling.

This initial scenario shows that despite the PV and PV/T modules being identical, there are notable differences in their performance, particularly in terms of temperature. In photovoltaic/thermal (PV/T) systems, the cooling mechanism is crucial for maintaining efficient operation by dissipating excess heat, which is not the case in standard PV systems. This difference in thermal management can lead to significant temperature variations during operation. Specifically, PV systems can reach higher temperatures compared to PV/T systems when the latter’s cooling function is inactive. This temperature disparity is due to the structural design of PV/T systems, which are inherently more efficient at distributing and dissipating heat [31,32]. Studies have demonstrated that the integrated cooling mechanisms in PV/T systems enhance heat dissipation, resulting in more stable and lower operational temperatures compared to standalone PV systems. Consequently, the results from this scenario are consistent with the existing literature and will aid in the normalization process for subsequent comparative performance analyses of the systems.

In the second scenario, a daylight simulator operating at full capacity with cooling was applied to the PV/T module, and its performance was evaluated alongside the PV module. Figure 6 shows the system’s performance during this experimental setup.

• Power Output:

  −

  Cycle 1: As in the initial scenario, the power output of the PV system (black line) peaks at around 75 mW, while the PV/T system (red line) reaches approximately 70 mW.

  −

  Cycle 2: The effects of the cooling system began to show in the second cycle. Here, the power output of the PV system peaked at approximately 67 mW, whereas the PV/T system reached a maximum of around 72 mW.

  −

  Cycles 3 and 4: In these cycles, the difference in power output between the PV and PV/T systems increased. The PV/T system maintained its power output, while the PV system peaked at 65 mW.

• Temperature Profiles: The temperature for the PV system (black dashed line) peaks at around 45 °C, while the PV/T system (red dashed line) peaks at approximately 35 °C. The full-capacity cooling effectively manages the heat, resulting in lower temperatures and higher power outputs.

Following the observation of the cooling system’s impact at full capacity, the third scenario involved applying the cooling system at half capacity and investigating its effects. Figure 7 illustrates the performance outcomes of both the PV and PV/T modules under these conditions.

• Power Output:

  −

  Cycle 1: As in the initial scenario, the power output of the PV system (black line) peaks at around 75 mW, while the PV/T system (red line) reaches approximately 70 mW.

  −

  Cycle 2: The effects of the cooling system began to manifest in the second cycle. During this cycle, the power output of the PV system peaked at approximately 67 mW, whereas the PV/T system reached a maximum of around 69 mW.

  −

  Cycles 3 and 4: In these cycles, the difference in power output between the PV and PV/T systems increased. The PV/T system maintained its power output, while the PV system peaked at 63 mW.

• Temperature Profiles: The temperature for the PV system (black dashed line) peaks at around 45 °C, whereas the PV/T system (red dashed line) peaks at approximately 37 °C. The lower temperature of the PV/T system indicates that even half-capacity cooling is effective at managing heat, resulting in slightly higher power output compared to the PV system.

It is important to address the observed discrepancy between the smooth temperature curves and the fluctuating power curves shown in Figure 5, Figure 6 and Figure 7. The stability of the temperature curve is due to the system’s thermal inertia, which dampens rapid fluctuations, resulting in a gradual, smooth trend. In contrast, the power curve shows peaks and valleys because power output is highly sensitive to rapid changes in environmental conditions, such as varying irradiance or transient shading. These fluctuations are captured at high frequency and do not significantly affect the overall temperature. This behavior aligns with the literature, where the temperature remains relatively stable while the power output responds more dynamically to short-term changes [17]. Understanding these differences enhances comprehension of the PV/T system’s performance and provides valuable insights into its operational efficiency.

The results indicate that the temperature and power generation rates of the PV/T system stabilize after the second cycle.

Table 6. In the PV/T system, measured peak power and temperature values in each cycle and scenario with comparison.

Cycle	Scenario 1		Scenario 2				Scenario 3
	1 P	2 T	1 P	3 D	2 T	3 D	1 P	3 D	2 T	3 D
1	73.7	22.9	75.1	1.92	22.8	0.82	72.8	1.15	22.9	0.17
2	69.7	30.1	72.5	3.87	28.2	6.41	70.8	1.60	29.9	0.79
3	67.2	33.3	72.0	6.57	30.1	9.75	69.2	2.79	32.6	2.04
4	66.2	35.6	71.7	7.71	29.4	17.4	68.6	3.58	32.9	7.36

¹ refers to the power in mW, ² refers to the temperature in °C, and ³ refers to the percentage difference.

presents the numerical outcomes for each scenario, detailing the power (P) and temperature (T) of the PV/T system, as well as the differences (D) between each scenario and Scenario 1 for the corresponding cycle.

In this table, P represents the power of the PV/T system in milliwatts (mW), T denotes the temperature of the PV/T system in degrees Celsius (°C), and D signifies the percentage difference (%) between the specified scenario and Scenario 1 for each cycle. The data illustrate the stability and variations in the performance of the PV/T system across different scenarios. The results highlight the electrical efficiency of the PV/T system compared to the PV system, emphasizing differences in electrical power generation. The maximum differences in the power generation and temperature of the PV/T module, when compared to Scenario 1, were found to be 7.71% and 17.41%, respectively.

Table 7. Comparison of experimental and numerical measurements.

Scenario 2
	Experimental				Numerical
Cycle	${\mathrm{P}}_{PV}$	${\mathrm{P}}_{PV/T}$	${\mathrm{T}}_{PV}$	${\mathrm{T}}_{PV/T}$	${\eta }_{PV}$	${\mathrm{P}}_{PV}$	D (%)	${\eta }_{PV/T}$	${\mathrm{P}}_{PV/T}$	D (%)
1	74.5	75.1	23.1	22.8	0.151	71.8	3.69	0.151	71.9	4.26
2	67.8	72.5	36.1	28.2	0.141	67.2	0.91	0.147	70.0	3.52
3	65.3	72.0	42.4	30.1	0.136	64.9	0.66	0.146	69.3	3.70
4	67.2	71.7	44.0	29.4	0.135	64.4	4.29	0.146	69.6	2.96
Scenario 3
1	72.8	72.8	24.8	22.9	0.150	71.2	2.26	0.151	71.9	1.33
2	67.2	70.8	38.2	29.9	0.140	66.4	1.23	0.146	69.4	2.07
3	64.3	69.2	45.0	32.6	0.135	64.0	0.42	0.144	68.4	1.12
4	62.7	68.6	47.3	32.9	0.133	63.2	0.80	0.144	68.3	0.47

T is measured in units of °C, while P is measured in units of mW.

compares the experimental and numerical methods used in this study. The experimental results include the PV and PV/T power measurements (P) and temperature values (T) recorded over four cycles for scenarios 2 and 3. The numerical results, calculated using equations (1) and (2), include the peak power measurements and efficiencies ($\eta$) of the PV and PV/T systems. The percentage differences (D (%)) in the D columns represent the discrepancies between the numerical and experimental P values for each row. The data indicate that the numerical methods yield results that closely align with the experimental data, with a maximum deviation of 4.29%. This demonstrates that the numerical models used in the study can reliably predict the experimental outcomes.

The results not only underscore the differences in electrical efficiency between the lab-scale PV/T system and the PV system but also provide significant pedagogical value. They aid in the transfer of knowledge and enhance users’ understanding of PV/T systems, contributing to both technical and educational advancements in the field.

4. Conclusions

This study successfully designed and implemented a compact educational PV/T system, named EduSolar, addressing the need for practical and effective tools in solar energy education. The system simulates real-world conditions and provides a hands-on, experiential learning platform for students and professionals. The key findings and contributions from the study are summarized as follows:

• Development of an Innovative Educational Tool: The PV/T system integrates both photovoltaic and thermal management components, offering a comprehensive educational tool that bridges the gap between theoretical knowledge and practical application. This tool enhances the understanding of the dynamic behaviors and operational complexities of PV systems under varying conditions.
• Performance and Efficiency Analysis: The experimental setup enabled detailed performance and efficiency analysis of PV and PV/T modules under different cooling scenarios and irradiance levels. The results demonstrated the effectiveness of the cooling system in enhancing the thermal management of PV modules, thereby improving overall energy conversion efficiency.
• Simulation of Real-World Conditions: Using a halogen lamp-based solar simulator, the study simulated various weather conditions and daylight cycles, providing valuable insights into the operational performance of PV systems. This method addresses the limitations of traditional educational resources that often fail to accurately simulate real-world conditions.
• Numerical Modeling and Verification: Numerical modeling was used to predict system efficiency and power output, which were validated through experimental measurements. The close agreement between theoretical and empirical results underscores the reliability of the models and the robustness of the experimental setup.
• Identification of Educational Gaps and Solutions: The research identified gaps in existing educational tools, such as the lack of practical simulation of real-world conditions and insufficient focus on thermal management. By addressing these gaps, the study proposes a best practice model for solar energy training, enhancing the pedagogical impact and fostering innovation in solar energy applications.
• Future Research Directions: While the study focused on a small-scale system, future research could expand to larger-scale installations to capture more complex environmental effects and long-term performance variations. Additionally, exploring different cooling system configurations and varying operational parameters could provide further insights into optimizing PV/T systems.

In conclusion, the development and implementation of this compact educational setup represent a significant advancement in solar energy education. By providing a realistic and interactive learning platform, this study contributes to more effective training and a deeper understanding of solar energy systems, ultimately supporting the transition towards sustainable and efficient energy solutions.