https://jser.ut.ac.ir/ Journal of Solar Energy Research en daily 1 Wed, 01 Jul 2026 00:00:00 +0330 Wed, 01 Jul 2026 00:00:00 +0330 https://jser.ut.ac.ir/article_107933.html The use of renewable energy, especially solar photovoltaic power, is essential for energy efficiency and reduces emissions that harm the environment and human health. In this study, a 150 kW on-grid photovoltaic system was designed and analysed by PV-sys software. The work's location near the river keeps the site cooler. The modules use a bifacial design, which offers high efficiency and a low annual degradation rate of about 1%. The optimum tilt angle, spacing between modules, and module height above the ground are 30°, 6m, and 1.5m, respectively. The rooftop and ceiling areas of the garage are sufficient for installing the system. The annual incident irradiance, output power, and PR are 2033.9 kWh/m2, 268.169 MWh, and 85.89%, respectively. The total CO2 emission is 5697.1 t. The cost of the system is 150,000,000 $. At the local tariff of $0.0066-$0.023/kWh, the payback period is 6.6 years. The realized profits exceed 200% of the cost price in just twenty years. Installing the current system, providing heat insulation for the building's rooftop and garage ceiling. Also, free energy without gas emission, and new jobs. Compared to a hybrid system of the same capacity. https://jser.ut.ac.ir/article_107735.html This research conducted an experimental study by looking at a solar-powered single-effect absorption cooling system with 1 kW power under hot climate conditions in Nasiriyah, Iraq. The working fluid is a 55% solution of lithium bromide-water and the thermal energy is supplied by an evacuated tube solar collector. The developed system is assessed by measuring the correlation between solar radiation, ambient temperature, and component temperature tested in August 2024 while the solar radiation is at its peak intensity of 945 W/m2. The outcomes indicate that an increase in solar radiation can result in an increase in the temperature of the generator that boosts the evaporation of refrigerant and the overall performance of the system. The best operational efficiency can be attained when the generator operates at 94 oC and evaporator at 28 oC. The results verify that solar-driven absorption cooling is a technical and a sustainable alternative to traditional cooling systems in highly solar-irradiated regions, which has great potential of cutting down on the reliance on fossil fuels and limiting environmental impact. https://jser.ut.ac.ir/article_107928.html This investigation evaluates the influence of rooftop reflectance on the performance of mono- and bifacial photovoltaic systems using a PVsyst-based simulation of a 125 kWp rooftop installation under tropical climatic conditions in southern India. Both photovoltaic technologies were analysed using identical electrical and geometric configurations so that rooftop albedo remained the only varying parameter. A reference albedo of 0.30 was considered for both technologies, while enhanced albedo scenarios of 0.50, 0.60, and 0.85 were evaluated for bifacial modules. Simulation results show that the monofacial system operating at an albedo of 0.30 generated 188.45 MWh/year with a performance ratio (PR) of 83.76%, whereas the bifacial configuration under identical conditions produced 187.11 MWh/year. As the rooftop albedo increased, the annual energy yield of the bifacial system increased to 187.86, 188.23, and 189.16 MWh/year for albedo values of 0.50, 0.60, and 0.85, respectively. This improvement was accompanied by a marginal reduction in PR from 83.17% to 82.83%, primarily due to higher operating temperatures associated with increased rear-side irradiance. The analysis further identifies an albedo-dependent performance transition threshold between 0.60 and 0.85, beyond which bifacial modules provide superior annual energy performance compared with monofacial modules. https://jser.ut.ac.ir/article_108057.html This research develops a theoretical framework for a solar chimney system comprising a collector, turbine, and vertical chimney. Global solar radiation and air temperature were calculated for midday on June 21st. The constructed model was utilized to simulate conditions using meteorological data from a specific summer day in Khenchela under realistic local climatic and operating conditions throughout summer while the physical proportions of Spain's Manzanares plant were reduced to one-tenth scale to project the facility's potential electricity yield. The effect of guides surrounding the collector on the electricity generated was simulated to determine the most effective SCPP for fulfilling the electricity demands of the agricultural area in Khenchela. The simulations revealed that an optimal configuration of nine guides could produce 72 W of electrical power. Results indicated that the efficiency of an SCPP is largely determined by its design dimensions, the surrounding air temperature, and the level of solar radiation. https://jser.ut.ac.ir/article_108223.html Grid-connected photovoltaic (PV) systems require accurate maximum power point tracking (MPPT), stable direct-current (DC)-link voltage regulation, and improved grid power quality under variable irradiance and temperature. Conventional MPPT methods often exhibit tracking delays and steady-state oscillations and have a limited ability to maintain low harmonic distortion in the grid current under dynamic operating conditions. This simulation-based work develops an artificial neural network (ANN)-based MPPT control strategy for improving power extraction, DC-link stability, and grid-current quality in a single-phase grid-connected PV system. The ANN controller uses irradiance, cell temperature, PV voltage, current, and power as input variables to estimate the voltage reference corresponding to the maximum power point. The error between the predicted reference voltage and the measured PV voltage is used to adjust the duty cycle of the DC–DC boost converter, while the regulated DC-link supports synchronized inverter operation. Under the simulated operating conditions, the system attained a PV voltage of 192 V, a PV current of 0.308 A, and an output power of 59.17 W, a duty cycle of 0.55, a DC-link voltage of 426 V, a switching frequency of 25 kHz, an RMS grid voltage of 230 V, and a grid-current THD of 3.42%. https://jser.ut.ac.ir/article_108165.html Solar stills represent a promising technology for decentralized freshwater production in arid and semi-arid regions. Nevertheless, their large-scale utilization remains limited by their relatively low distillate productivity and thermal efficiency. To address this limitation, the present study numerically investigates the influence of basin geometry on the thermal performance and productivity of a single-slope solar still. The analysis compares a conventional flat basin with a square-corrugated basin under identical operating conditions in Basra, Iraq, on 28 October 2025. A transient two-dimensional CFD model was developed in ANSYS Fluent, and the predicted basin water and glass cover temperatures were coupled with Dunkle correlations to estimate the hourly and daily distillate yield. The square-corrugated basin showed a clear improvement over the flat basin, with peak hourly productivity increasing from 0.72 to 0.89 kg/m²·h and cumulative daily yield increasing from 2.97 to 3.9 kg/m²·day. The average daily thermal efficiency also improved from 44.7% to 67.3%. Overall, this geometric modification achieved a 31.12% improvement in freshwater production. These results indicate that increasing the effective heat-transfer area by modifying the basin geometry improved the thermal behavior of the solar still and significantly enhanced its productivity under identical climatic conditions. https://jser.ut.ac.ir/article_108189.html This study experimentally investigates the effect of TiO₂ and SiO₂ nanocoatings on the photovoltaic (PV) modules performance under Baghdad, Iraq, climatic conditions. Three identical monocrystalline PV modules; an uncoated reference module and two nanocoated modules, were tested under real outdoor conditions during three separate experimental days. The effects of solar irradiance, ambient temperatures, and dust accumulation on the electrical, thermal, energy, and exergy performances of the investigated modules were evaluated. The results showed that the nanocoated PV modules performed better than the reference module and the difference in performance increased with the dust accumulation. The maximum power output of the reference module decreased to 29.50 W, whereas the TiO2- and SiO2-coated modules generated 35.90 W and 37.90 W, respectively, on the third day of testing. The electrical efficiency of the reference module decreased to around 10%, while the TiO2- and SiO2-coated modules kept efficiencies around 13% and 14%, respectively. The exergy efficiency remained higher for the coated modules throughout the experimental period. These results demonstrate that SiO2 nanocoating is a practical, low-cost, and effective way to reduce the dust-induced performance degradation and improve the operation of the PV systems in the dusty environments. https://jser.ut.ac.ir/article_108247.html This experiment investigates the performance optimization of a stand-alone photovoltaic water pumping system (PVWPS) in the tropical region of Yogyakarta, Indonesia (7°S latitude), specifically during the December Solstice. While conventional designs often utilize fixed latitude-based tilt angles, this research proposes a seasonal micro-adjustment strategy to address the sun's extreme Southern position during the rainy season. An experimental comparison was conducted between two low-tilt configurations (5° vs. 10°) on a 1.65 kWp off-grid system powering a 290 W surface pump. Data were collected under real operating conditions (10:00–14:00) and filtered to exclude cloud-edge anomalies. The results reveal that the 5° tilt angle outperforms the 10° configuration, achieving an average electrical efficiency of 17.5% compared to 16.6%. The near-flat orientation minimizes cosine losses and maximizes direct irradiance capture when the sun is at the Tropic of Capricorn. This study recommends a seasonal manual adjustment to 5° during the December planting season to enhance water discharge reliability in remote agricultural areas. https://jser.ut.ac.ir/article_105749.html Active cooling typically provides higher thermal management efficiency than passive methods. However, its continuous power consumption reduces the net energy output of photovoltaic (PV) systems. To address the limitations of traditional fixed-threshold cooling approaches, this work introduces an adaptive ANN-based hybrid cooling strategy capable of autonomously selecting the optimal cooling mode in real time. A hybrid PV cooling system integrated with Internet of Things (IoT) monitoring is developed, where a Feed Forward Neural Network Cooling System (FNNCS) is trained using real-time environmental and operational data to predict the required cooling power and intelligently choose between water- and air-based cooling. Experimental results show that the proposed FNNCS improves PV electrical performance by an average of 3.0% compared to an uncooled panel. The system achieves a maximum reduction of 14.1 °C in the backside temperature of the PV module. In addition, by dynamically adjusting cooling activation based on irradiance and temperature conditions, the FNNCS decreases cooling power consumption by 35.7% relative to a fixed cooling strategy. These findings demonstrate the effectiveness of the ANN-based hybrid cooling approach in enhancing PV performance while reducing auxiliary energy usage. https://jser.ut.ac.ir/article_106561.html The growing integration of photovoltaic (PV) systems into conventional distribution networks has intensified major power quality challenges such as 18–25% harmonic distortion, power factor deviation between 0.92 and 0.95, frequent voltage fluctuations, and load imbalance exceeding 8%. This study proposes a Hybrid Deep Reinforcement Learning (DRL) with Leaky LMS-ANN controlled Unified Power Quality Conditioner (UPQC) to achieve enhanced active power filtering in PV-integrated systems. The hybrid controller leverages the decision-making capability of DRL alongside the adaptive parameter tuning of the Leaky LMS-ANN algorithm, enabling real-time optimization under variable irradiance, nonlinear loads, and load-switching conditions. MATLAB/Simulink validation demonstrates substantial performance gains: total harmonic distortion is reduced from 18.4% to 2.97% (84% reduction), reactive power compensation improves by 55.6%, and voltage imbalance declines from 8.5% to 1.2%. The DC-link voltage stability increases by 23%, while the power factor is maintained near unity at 0.998. Compared with conventional ANN, LMS, and MPC controllers, the proposed approach delivers superior harmonic mitigation, voltage regulation, and system reliability, making it well suited for advanced smart grid applications. https://jser.ut.ac.ir/article_107929.html A key difficulty is maintaining consistent power output in a solar photovoltaic system during partial shading. Transient clouds, nearby buildings and trees, dust particles, and various elements partially obscure the PV modules. PV arrays subjected to uneven irradiation display inconsistent PV characteristics and experience mismatch losses in their modules. The resolution to these issues is to adjust panels to achieve improved results when dimmed. Therefore, using MATLAB/SIMULINK, analyze, compare, and explore several configurations, including Sudoku, Honeycomb, Series Parallel, Total Cross Tied, & Hyper Sudoku (HS). Through a simulation method, every configuration is evaluated and its functioning articulated. Every configuration is assessed, and its functionality is explained through a simulation method. The data indicated that the HS method yielded the highest output power at 14219W and achieved the peak efficiency at 10.12%. In the diagonal design, it outperformed all other configurations, achieving a fill factor of 0.455, while SP topology at 8160W had the highest ML and the lowest FF of 0.261. https://jser.ut.ac.ir/article_108149.html Partial shading caused by dust accumulation, surface contaminants, and nearby obstructions reduces the incident irradiance on photovoltaic (PV) modules, leading to significant performance degradation. Conventional approaches for assessing shading effects rely on electrical measurements, irradiance sensors, or model-based calibration, increasing system complexity and limiting scalability. Although image-processing techniques have been widely investigated for PV inspection, most existing studies emphasize qualitative fault identification rather than quantitative attenuation assessment. This paper presents a non-intrusive image-processing framework that interprets PV panel images as two-dimensional illumination fields and introduces an Illumination Non-Uniformity Index (INUI) derived from physically interpretable spatial and frequency-domain descriptors. The proposed index integrates global intensity variation, spatial discontinuity, and low-frequency illumination distortion to characterize diverse shading patterns. An image-derived attenuation metric is subsequently established to quantify attenuation severity, demonstrating a monotonic relationship with illumination non-uniformity without requiring learning-based models, electrical measurements, or irradiance sensors. Experimental evaluation under diverse shading conditions confirms consistent monotonic behaviour, robustness against imaging variations, and computational efficiency suitable for large-scale visual inspection. The proposed framework provides an explainable, lightweight, and scalable methodology for quantitative image-based assessment of shading-induced attenuation in photovoltaic modules, offering a practical alternative for visual condition monitoring and supporting future intelligent PV inspection systems. https://jser.ut.ac.ir/article_108188.html A new fluid called nanofluid has the potential to greatly enhance the efficiency of traditional fluids in heat transport. Using (CuO/water, MWCNT/water, and CuO+MWCNT/water (80:20%)) nanofluids. This numerical study used six volume fractions of different nanoparticles (0, 0.01, 0.02, 0.03, 0.04, and 0.05%) and six different volumetric flow rates (0.25, 0.5, 0.75, 1, 2 and 3 L/min) for each of these concentrations. Using (MWCNT/water) as a nanofluid yielded the maximum efficiency (76.8%, 78.3%, and 80.4%) for volume fraction of (0.03, 0.04 and 0.05) respectively, at a volumetric flowrate of (3 L/min). At the same volumetric flow, however, the base fluid (water) had a lower efficiency of (53.4%). At volumetric flowrate (3 L/min), (CuO/water) attained median efficiency (61.1%, 62.6%, and 64.2%) for volume fractions (0.03,0.04, and 0.05%), respectively. At a volumetric flowrate of (3 L/min), the hybrid nanofluid (CuO+MWCNT/water) (80:20%) had efficiencies of (77.7%, 79.1%, and 79.5%) for volume fractions of (0.03, 0.04 and 0.05%), respectively. The use of hybrid nanocoating technology improves the system efficiency in three nanofluids (CuO/water, MWCNT/water and CuO+MWCNT/water), the highest efficiency was recorded at a concentration of (0.05%) and a volumetric flow rate of (3 L/min) where were (70.4%, 88.4% and 86.1%), respectively. https://jser.ut.ac.ir/article_108224.html Reliable fault diagnosis in photovoltaic systems is compromised when measurement data are corrupted by noise. This study assesses the robustness of Support Vector Machine-based hybrid classifiers SVM+KNN, SVM+LR, SVM+MLP, SVM+DT, and SVM+RF subjected to controlled Gaussian noise injection. A dataset of 13,767 records collected at the Ngaoundéré weather station was used, partitioned 80%/20% for training and testing. The hybridization strategy relies on a parallel probabilistic fusion scheme in which prediction probabilities from each base classifier are averaged. Model performance was evaluated along three complementary axes: F1-score, empirical error rate, and temporal stability of the classification rate. Results show that the SVM+RF hybrid achieves the best overall accuracy (91.7%) and AUC (0.991), with the greatest resilience to noise, while SVM+KNN exhibits the weakest robustness. Importantly, probabilistic fusion does not consistently outperform the strongest individual model; it mainly moderates instability when the base classifiers offer genuine complementarity. One-way ANOVA confirms that the performance differences between individual and hybrid configurations are statistically significant. Temporal analysis further reveals that fused models maintain a more regular classification rate across samples, a key advantage in unstable PV operating environments. This work contributes to the development of robust and reliable hybrid systems for real-world diagnostics. https://jser.ut.ac.ir/article_108242.html Water scarcity is a global issue. Solar desalination systems, particularly double-slope solar stills (DSSS), offer an efficient, affordable approach to produce fresh water. This study systematically investigates the influence of fin geometry (thin vs. twisted) and fin number on the thermo-fluid behavior and productivity of DSSS under hot climatic conditions. Using ANSYS Fluent 2019 R1, the mass, momentum, and energy equations were discretised via the finite volume method to examine simultaneous heat, mass, and fluid flow inside the basin. Results show that using fins significantly enhances system performance. At peak time (12:00 PM), productivity improved from 0.8206 L/h (conventional) to 1.4928 L/h for thin fins (81.91% enhancement) and 1.9535 L/h for twisted fins (138.13% enhancement). Efficiency likewise improved from 28.543% to 59.810% and 80.500%, respectively. On a daily basis, productivity and efficiency increased from 3.514 to 8.761 L/m²·day and from 25.87% to 74.97% using 49 twisted fins, representing improvements of 149.32% and 189.68%. Twisted fins exhibit superior performance by enhancing internal mixing, reducing thermal boundary layer thickness, and improving vapor distribution. Ultimately, the best results were obtained with 49 twisted fins, demonstrating that sophisticated geometric modifications are essential to maximize DSSS productivity and efficiency.