In recent years, research communities have shown significant interest in solar energy systems and their cooling. While using cells to generate power, cooling systems are often used for solar cells (SCs) to enhance their efficiency and lifespan. However, during this conversion process, they can generate heat. This heat can affect the performance of solar cells in both advantageous and detrimental ways. Cooling cells and coordinating their use are vital to energy efficiency and longevity, which can help save energy, reduce energy costs, and achieve global emission targets. The primary objective of this review is to provide a thorough and comparative analysis of recent developments in solar cell cooling. In addition, the research discussed here reviews and compares various cooling systems that can be used to improve cell performance, including active cooling and passive cooling. The outcomes reveal that phase-change materials (PCMs) help address critical economic goals, such as reducing the cost of PV degradation, while enhancing the lifespan of solar cells and improving their efficiency, reliability, and quality. Active PCMs offer precise control, while passive PCMs are simpler and more efficient in terms of energy use, but they offer less control over temperature. Moreover, an innovative review of advanced cooling methods is presented, highlighting their potential to improve the efficiency of solar cells.

This study presents an innovative integrated control system to enhance photovoltaic (PV) efficiency in arid regions by addressing two critical challenges: temperature-induced performance degradation and dust accumulation. Focusing on Kirkuk, Iraq, the proposed system integrates two distinct intelligent subsystems powered by IoT technology: an activated water-based cooling mechanism and an activated water-driven dust removal system. Both subsystems employ real-time data from IoT sensors (temperature, humidity, dust density, irradiance) to autonomously optimize operations through a centralized cloud platform. The cooling subsystem utilizes activated water circulated through microchannel networks embedded in PV panels, dynamically triggered by AI algorithms to maintain optimal temperatures. Simultaneously, the dust removal subsystem employs pressurized activated water sprays, activated during the night periods to minimize energy loss, with computer vision algorithms identifying dust distribution patterns for targeted cleaning. This research highlights the synergy between IoT-driven automation, activated water technologies, and dual-control optimization, offering a scalable model for renewable energy systems in arid climates. The framework aligns with sustainable development goals by balancing energy efficiency, water conservation, and cost-effectiveness. Field experiments in Kirkuk demonstrated a 27% increase in energy output and a 40% reduction in maintenance downtime compared to conventional systems. The intelligent scheduling of activated water usage reduced overall water consumption by 30% while achieving 95% dust removal efficiency. Economic analysis confirmed a 22% reduction in operational costs due to adaptive resource management and prolonged PV lifespan.

Increasing demand for cooling operations in the oil and other sectors, this has led to an increase in electrical energy consumption. The most sustainable solution is to use absorption cooling technology by utilizing solar heat as driving energy instead of electricity. The primary advantage of absorptive cooling is lower electricity costs. In this study, the effect of changing the thermal storage capacities of hot and cold storage tanks and the solar collector area on the performance of the absorption air conditioning cycle was investigated. The optimum operating conditions, the maximum number of processing hours, and the optimum performance coefficient of the absorption conditioning cycle system were selected. The water-lithium bromide solution was used as a fluid in the sorption cycle, and glycerin was used in the hot and cold tank cycle and in the solar collector because it can with stands both high and low temperatures. The simulation process was carried out using (Fortran 90) program with the help of (Port log) program, (Carrier HAP420) program and (Curve Expert) program. The absorption conditioning cycle was simulated during the day to choose the best capacity for hot and cold storage tanks, as well as to choose the solar collector with the best performance factor. Changing the area of the solar collector (from 9.6 m² to 16.7 m²), and the volume of the hot tank (from 0.55 m3 to 1.4 m3) have been done to provide the maximum temperature that the hot tank can reach with varying expected cooling load per hour, as well as the size of the tank cold (from 0.9 m3 to 1.6 m3) which gets additional cooling capacity, since the effect of these variables was tested separately. According to the research results, the best and most suitable volume for the hot tank is (0.55 m3), and for the cold tank is (1.5 m3), and the best and appropriate area for a solar concentric collector is (11.7 m²), which can provide longer running hours. Finally, the higher the generator's temperature, the higher the system's coefficient of performance (COP). The lowest COP value (0.68) is used to guarantee that the system runs for longer periods of time.