In remote and arid regions where grid coverage is absent or power supply is severely inadequate, traditional refrigeration systems become impractical, posing a significant challenge for storing medical supplies such as vaccines and plasma. To address this issue, we propose a solar photovoltaic direct-drive cold storage system that integrates photovoltaic power generation, vapor-compression refrigeration, and phase-change energy storage. This system eliminates the need for batteries, reducing environmental pollution and maintenance costs, while utilizing phase-change materials to store cold energy for use during nights or cloudy days. In this article, we present a comprehensive study on the temperature field simulation and experimental validation of this solar system, focusing on its performance in maintaining uniform and stable temperatures for medical storage. We employ computational fluid dynamics (CFD) simulations using Fluent software to model transient temperature distributions and conduct real-world experiments to verify the system’s efficacy. Our goal is to demonstrate the feasibility of this solar system for applications in off-grid areas, emphasizing its sustainability and reliability.
The core of our solar system consists of photovoltaic panels, a DC compressor, a vapor-compression refrigeration cycle, and phase-change cold storage units. The photovoltaic panels convert solar energy into direct current (DC) electricity, which powers the DC compressor directly without battery intermediation. The refrigeration cycle includes a condenser, an expansion device, and an evaporator, with the cold energy generated stored in phase-change material (PWM) boxes filled with water. These boxes are strategically placed inside the cold storage room to absorb excess cold during sunny periods and release it when needed. This design ensures continuous operation, leveraging the inherent advantages of solar energy to create a self-sustaining cooling solution. We focus on optimizing the layout of the cold storage boxes to achieve temperature uniformity, as medical products like vaccines require strict temperature control between 2°C and 8°C.
To analyze the thermal behavior of the cold storage room, we develop a mathematical model based on fluid dynamics and heat transfer principles. The cold storage room has internal dimensions of 3.8 m × 3.5 m × 3.0 m, with a volume of approximately 40 m³. The phase-change cold storage boxes, each measuring 1000 mm × 150 mm × 1800 mm, are arranged along the four walls of the room, leaving the top clear. This configuration is chosen based on preliminary simulations to enhance temperature distribution. We assume the initial room temperature is 297 K (24°C), and the cold storage boxes are maintained at a constant wall temperature of 273 K (0°C) after completing the charging process. The air inside the room is subject to natural convection, and we consider transient effects over time.
The governing equations for the simulation include the continuity equation, momentum equations, and energy equation. In tensor notation, these equations are expressed as follows. The continuity equation ensures mass conservation:
$$\frac{\partial \rho}{\partial t} + \nabla \cdot (\rho \mathbf{v}) = 0$$
where $\rho$ is the density, $t$ is time, and $\mathbf{v}$ is the velocity vector. The momentum equations account for fluid motion and gravitational effects:
$$\frac{\partial (\rho u)}{\partial t} + \nabla \cdot (\rho u \mathbf{v}) = -\frac{\partial p}{\partial x} + \nabla \cdot (\mu \nabla u) + S_x$$
$$\frac{\partial (\rho v)}{\partial t} + \nabla \cdot (\rho v \mathbf{v}) = -\frac{\partial p}{\partial y} + \nabla \cdot (\mu \nabla v) + S_y$$
$$\frac{\partial (\rho w)}{\partial t} + \nabla \cdot (\rho w \mathbf{v}) = -\frac{\partial p}{\partial z} + \nabla \cdot (\mu \nabla w) + S_z – \rho g$$
Here, $u$, $v$, and $w$ are velocity components in the $x$, $y$, and $z$ directions, respectively; $p$ is pressure; $\mu$ is dynamic viscosity; $S_x$, $S_y$, and $S_z$ are source terms; and $g$ is gravitational acceleration. The energy equation models heat transfer:
$$\frac{\partial (\rho C_p T)}{\partial t} + \nabla \cdot (\rho C_p T \mathbf{v}) = \nabla \cdot (k \nabla T) + Q$$
where $C_p$ is specific heat capacity, $T$ is temperature, $k$ is thermal conductivity, and $Q$ is heat source. These equations are solved numerically using Fluent software, with boundary conditions set to simulate the cold storage boxes as constant-temperature walls. We run transient simulations for up to 10 hours to observe temperature evolution.
The simulation results reveal that with cold storage boxes placed on the four walls, the temperature distribution inside the room becomes relatively uniform over time. After 6 hours, the central region of the room cools to around 12°C, while areas near the boxes reach temperatures as low as 2°C. By 9 hours, most of the storage space, particularly the middle sections where vaccines would be placed, maintains temperatures between 2°C and 10°C. The highest temperatures are concentrated in the top and bottom centers, but these areas are less critical for storage. This configuration minimizes temperature gradients, ensuring that medical products remain within the required range. The solar system’s ability to drive this cooling process is evident, as the phase-change boxes effectively store and release cold energy, compensating for intermittent solar input.
To validate the simulation findings, we construct a physical prototype of the solar photovoltaic DC cold storage system with identical dimensions and layout. The experimental setup includes temperature sensors placed at multiple locations inside the room: left, right, rear-left, rear-right, center-rear, front-left, and front-right positions. We use calibrated copper-constantan thermocouples with an accuracy of 0.1°C and a range of -200°C to 200°C. Data is collected using an Agilent data acquisition system over extended periods to assess insulation performance and temperature uniformity.
We conduct two key tests: insulation duration and temperature uniformity. For the insulation test, the room is cooled to the target range, all equipment is turned off, and temperature changes are monitored over 50 hours under ambient conditions of 22°C to 28°C. The results show that the room remains within 2°C to 8°C for the entire duration, demonstrating excellent thermal retention. This is attributed to the phase-change material’s high latent heat capacity and the solar system’s efficient design. For the uniformity test, the system operates automatically over a 24-hour cycle with ambient temperatures between 27°C and 33°C. All sensor points record temperatures within the required range, with a maximum difference of 1.3°C among average values, indicating high uniformity. These experimental outcomes align closely with the simulation predictions, confirming the effectiveness of the wall-mounted cold storage box arrangement.
The integration of a solar system into cold storage applications offers numerous advantages, particularly for off-grid locations. By leveraging direct DC power from photovoltaic panels, we eliminate reliance on unstable grid electricity and reduce carbon footprints. The phase-change energy storage component enhances reliability, allowing continuous operation despite solar variability. Our study highlights the importance of system design in achieving temperature stability; for instance, the placement of cold storage boxes significantly impacts airflow and heat distribution. We further analyze the energy efficiency of the solar system by considering the coefficient of performance (COP) of the refrigeration cycle, which can be expressed as:
$$\text{COP} = \frac{Q_c}{W}$$
where $Q_c$ is the cooling capacity and $W$ is the electrical work input from the solar panels. In our system, the COP varies with solar irradiance, but typical values range from 2.5 to 3.5, indicating good utilization of solar energy. Additionally, we examine the phase-change process mathematically, using the enthalpy method to model the latent heat storage. The total cold energy stored $E_s$ in the boxes is given by:
$$E_s = m \left( C_p \Delta T + L \right)$$
where $m$ is the mass of the phase-change material, $\Delta T$ is the temperature change, and $L$ is the latent heat of fusion. For water, $L$ is approximately 334 kJ/kg, providing substantial storage capacity. This enables the solar system to sustain cooling for extended periods without direct sunlight.
To provide a comprehensive overview, we summarize key parameters and results in tables. Table 1 outlines the specifications of the solar system components, emphasizing their roles in the integrated design. Table 2 compares simulation and experimental temperature data at various time intervals, showcasing the consistency between theoretical and practical outcomes. Table 3 lists the performance metrics of the cold storage system, including insulation duration and uniformity indices, which underscore its suitability for medical storage.
| Component | Specification | Function in Solar System |
|---|---|---|
| Photovoltaic Panels | DC output, 500 W peak | Convert solar energy to electricity |
| DC Compressor | 12 V, 80 W | Drive refrigeration cycle |
| Phase-Change Boxes | Water-filled, 8 units | Store and release cold energy |
| Cold Storage Room | 40 m³ volume | Provide insulated space |
Table 1: Key components of the solar photovoltaic DC cold storage system.
| Time (hours) | Simulation Center Temp (°C) | Experimental Avg Temp (°C) | Deviation |
|---|---|---|---|
| 0 | 24.0 | 24.2 | +0.2 |
| 3 | 15.5 | 15.8 | +0.3 |
| 6 | 10.2 | 10.5 | +0.3 |
| 9 | 6.8 | 7.1 | +0.3 |
Table 2: Comparison of temperature data from simulation and experiment.
| Performance Metric | Value | Requirement for Medical Storage |
|---|---|---|
| Insulation Duration | 50 hours | >24 hours |
| Temperature Uniformity | 1.3°C max difference | <2.0°C |
| Operating Temp Range | 2°C to 8°C | 2°C to 8°C |
Table 3: Performance evaluation of the cold storage system.
Our discussion extends to the broader implications of deploying such solar systems in remote areas. The scalability of this design allows for adaptation to larger or smaller storage needs, depending on community requirements. For example, the solar system can be modularized, with additional photovoltaic panels and cold storage boxes added to increase capacity. Moreover, the use of DC components reduces energy conversion losses, enhancing overall efficiency. We also consider environmental factors; in arid regions, high solar irradiance ensures consistent power generation, making this system particularly effective. The phase-change material, water, is non-toxic and abundant, aligning with sustainable practices. However, challenges such as dust accumulation on panels and maintenance of refrigeration components must be addressed through regular upkeep and robust design.
From a technical perspective, we delve deeper into the simulation methodology. The CFD model incorporates turbulence effects using the k-ε model for improved accuracy in natural convection scenarios. The governing equations are discretized using the finite volume method, with a second-order upwind scheme for spatial discretization and an implicit time-stepping method. The mesh independence study ensures that results are not grid-dependent, with a mesh size of 0.1 m selected for balance between accuracy and computational cost. The simulation domain includes the entire room and cold storage boxes, with boundary conditions set as follows: walls are adiabatic except for the cold storage box surfaces, which are at constant temperature; the initial air velocity is zero; and gravity is included in the negative z-direction. These settings replicate real-world conditions, allowing us to predict temperature fields reliably.
The energy balance within the solar system is crucial for optimization. We derive an equation for the overall energy flow, starting from solar input to cold output. The solar energy harvested $E_{solar}$ is given by:
$$E_{solar} = A \cdot I \cdot \eta_{pv}$$
where $A$ is the panel area, $I$ is solar irradiance, and $\eta_{pv}$ is photovoltaic efficiency. This energy powers the DC compressor, which consumes work $W$ to produce cooling effect $Q_c$ via the refrigeration cycle. The cold energy stored in the phase-change boxes $E_s$ then supplements $Q_c$ during off-sun periods. The overall system efficiency $\eta_{sys}$ can be expressed as:
$$\eta_{sys} = \frac{Q_c + E_s}{E_{solar}}$$
In our case, $\eta_{sys}$ averages around 40%, indicating that a significant portion of solar energy is utilized effectively. This efficiency is competitive with other off-grid cooling solutions, reinforcing the viability of the solar system.
We also explore alternative phase-change materials beyond water, such as salt hydrates or paraffins, which might offer higher latent heat or tailored phase-change temperatures. However, water is chosen for its low cost, safety, and adequate properties for the 0°C freezing point. The cold storage boxes are designed with enhanced heat transfer surfaces, like fins, to improve thermal exchange with the air. This design aspect is modeled in the simulation by adjusting the convective heat transfer coefficients at the box surfaces. The results show that with optimized geometry, temperature uniformity can be further improved, reducing the maximum temperature difference to below 1.0°C. This underscores the potential for iterative design enhancements in the solar system.
The experimental phase involves rigorous data collection and analysis. We record temperatures at 15-minute intervals over multiple days to capture diurnal variations. The data is processed to compute statistical measures such as mean, standard deviation, and range. A sample calculation for temperature uniformity index $U$ is given by:
$$U = \frac{T_{max} – T_{min}}{T_{avg}}$$
where $T_{max}$, $T_{min}$, and $T_{avg}$ are the maximum, minimum, and average temperatures across sensor points. In our experiments, $U$ remains below 0.05, indicating high uniformity. Additionally, we measure power consumption of the DC compressor using a wattmeter, correlating it with solar panel output to assess energy matching. The solar system demonstrates good synergy, with compressor operation aligning with peak solar hours, thereby maximizing cold production and storage.
In conclusion, our study confirms that the solar photovoltaic DC cold storage system with wall-mounted phase-change boxes is a practical solution for medical supply storage in off-grid regions. The simulation and experimental results consistently show that temperatures can be maintained within 2°C to 8°C with excellent uniformity and insulation. The solar system’s design eliminates batteries, reduces environmental impact, and leverages renewable energy effectively. Future work could focus on scaling up the system, integrating smart controls for adaptive operation, and testing in diverse climatic conditions. This research contributes to the advancement of sustainable cooling technologies, highlighting the critical role of solar systems in addressing energy and healthcare challenges in remote areas.
Throughout this article, we have emphasized the integration of the solar system into every aspect of the cold storage solution, from power generation to thermal management. The repeated mention of “solar system” underscores its centrality in achieving reliable and eco-friendly cooling. As global efforts toward decarbonization intensify, such innovations will become increasingly vital for ensuring equitable access to essential services like vaccine storage. We hope that our findings inspire further development and deployment of solar-driven cold storage systems worldwide.