Solar Thermal Energy and Photovoltaic Systems

The precise measurement for irradiance is important for the performance evaluations of solar systems, because both beam and diffuse radiation measurements must be known to calculate the efficiency of a solar system. One of the widely used instruments for diffuse radiation measurement is a pyranometer with a ring. Hence, investigations on shadow band correction factors are necessary. The factors are normally calculated by the expressions of Drummond and Burek et al. under isotropic conditions. However, their calculation results are approximate. While the latitude $\phi$, the inclination angle $\beta$ and the declination $\delta$ are satisfied with the condition of $\left|-\tan \left(\phi -\beta \right)\tan \delta \right|>1$, the factors cannot be calculated by their expressions. In this paper, the expressions for the factors under isotropic conditions were obtained by coordinate transformations and discussed in two different coordinate systems without approximation. Our expressions can give precise correction factors in any case and overcome the disadvantages of their expressions. While the sensor is placed horizontally, the maximum relative deviation between the results by the expression in Drummond’s paper and by our expressions is less than 2.3%. When the sensor is placed on a sloped surface, the results by the expressions in Burek’s paper and by our expressions will have considerable differences in some ranges of slope angles and latitudes. The maximum relative deviation is more than 22%. Full article

In this work, we study the thermal stability of a hydrothermally treated stainless steel (SS) selective solar absorber by annealing in air in a temperature range between 300 °C and 700 °C for a soaking time of 2 h. Thermal stability testing in the presence of air is critical if the vacuum is breached. Therefore, the SS was characterized by X-ray diffraction (XRD), mechanical, and optical techniques. The XRD analysis shows that the grain size of the as-treated absorber is 67 nm, whereas those of the annealed absorbers were found to be in the range between 66 and 38 nm. The phase of the as-treated and annealed SS was further identified by XRD as Fe₂O₃. The EDS result shows that the elemental components of the SS were C, Cr, Fe, and O. The strain (ε) and stress (σ) calculated for the as-treated absorber are 1.2 × 10⁻¹ and −2.9 GPa, whereas the annealed absorbers are found in the range of 4.4 × 10⁻¹ to 5.2 × 10⁻¹ and −121.6 to −103.2 GPa, respectively, at 300–700 °C. The as-treated SS absorbers exhibit a good spectra selectivity of 0.938/0.431 = 2.176, which compares with 0.941/0.403 = 2.335 after being annealed at 300 °C and 0.884/0.179 = 4.939 after being annealed at 700 °C. These results indicate a small improvement in absorptivity (0.941) and emissivity (0.403) after annealing at 300 °C, followed by a significant decrease after annealing at 700 °C. The obtained analysis confirms that the annealed SS absorber exhibits excellent selectivity and is suitable to withstand any thermal condition (≤700 °C) in air. Thus, using a cost-effective approach as demonstrated in this study, the as-treated and annealed SS absorber could be used for photo-thermal conversion applications. Full article

The current geometric increase in the global deployment of solar photovoltaic (PV) modules, both at utility-scale and residential roof-top systems, is majorly attributed to its affordability, scalability, long-term warranty and, most importantly, the continuous reduction in the levelized cost of electricity (LCOE) of solar PV in numerous countries. In addition, PV deployment is expected to continue this growth trend as energy portfolio globally shifts towards cleaner energy technologies. However, irrespective of the PV module type/material and component technology, the modules are exposed to a wide range of environmental conditions during outdoor deployment. Oftentimes, these environmental conditions are extreme for the modules and subject them to harsh chemical, photo-chemical and thermo-mechanical stress. Asides from manufacturing defects, these conditions contribute immensely to PV module’s aging rate, defects and degradation. Therefore, in recent times, there has been various investigations into PV reliability and degradation mechanisms. These studies do not only provide insight on how PV module’s performance degrades over time, but more importantly, they serve as meaningful input information for future developments in PV technologies, as well as performance prediction for better financial modelling. In view of this, prompt and efficient detection and classification of degradation modes and mechanisms due to manufacturing imperfections and field conditions are of great importance towards minimizing potential failure and associated risks. In the literature, several methods, ranging from visual inspection, electrical parameter measurements (EPM), imaging methods, and most recently data-driven techniques have been proposed and utilized to measure or characterize PV module degradation signatures and mechanisms/pathways. In this paper, we present a critical review of recent studies whereby solar PV systems performance reliability and degradation were analyzed. The aim is to make cogent contributions to the state-of-the-art, identify various critical issues and propose thoughtful ideas for future studies particularly in the area of data-driven analytics. In contrast with statistical and visual inspection approaches that tend to be time consuming and require huge human expertise, data-driven analytic methods including machine learning (ML) and deep learning (DL) models have impressive computational capacities to process voluminous data, with vast features, with reduced computation time. Thus, they can be deployed for assessing module performance in laboratories, manufacturing, and field deployments. With the huge size of PV modules’ installations especially in utility scale systems, coupled with the voluminous datasets generated in terms of EPM and imaging data features, ML and DL can learn irregular patterns and make conclusions in the prediction, diagnosis and classification of PV degradation signatures, with reduced computation time. Analysis and comparison of different models proposed for solar PV degradation are critically reviewed, in terms of the methodologies, characterization techniques, datasets, feature extraction mechanisms, accelerated testing procedures and classification procedures. Finally, we briefly highlight research gaps and summarize some recommendations for the future studies. Full article

Photovoltaic (PV) solar energy is a very promising renewable energy technology, as solar PV systems are less efficient because of climate conditions, temperature, and irradiance change. So, to resolve this problem, two PV topologies are used, i.e., centralized and distributed PV systems. The centralized technique is quicker than the distributed technique in terms of convergence speed and a faster power tracking approach. In the event of uniform irradiance, the centralized system also has the benefit of supplying superior energy, but in PS scenarios, a huge amount of energy is lost. However, the distributed approach requires current and voltage measurements at each panel, resulting in a massive data set. Nevertheless, in the event of shading circumstances, the distributed technique is highly effective because a modular level power electronics (MLPE) converter is used. While in a centralized PV system, there is only a single DC-DC converter for the whole PV system. In this research work, a DFO-based DC-DC converter is designed for modular level, with an ability to perform a rapid shutdown of the module under fire hazard conditions, troubleshooting, and monitoring of a module in a very efficient way. The robustness of the proposed MPPT DFO algorithm is tested with different techniques such as Cuckoo Search (CS), Fruit Fly Optimization (FFO), Particle swarm optimization (PSO), Incremental conductance (InC), and Perturb and observe(P&O) techniques. The proposed technique shows better results in terms of MPPT efficiency, dynamic responsiveness, and harmonics. Furthermore, the result of MLPE and the centralized system is verified by using the Helioscope with different inverter companies like SMA, Tigo, Enphase, Solar edge, and Huawei. The results prove that MLPE is a better option in the case of shading region for attaining the maximum power point. Full article

Heliothermic technologies are affected by their low density, intermittence and low economic competitiveness. Hybrid solar–waste heat power systems can increase plant conversion efficiency and power generation while reducing intermittence. This study focused on the development of software (AERES) to economically optimize hybrid solar–waste heat power systems in terms of technology selection, sizing, operating conditions and power block characteristics. The technologies considered for algorithm selection were (i) heat exchangers that recover a wide range of waste heat sources, (ii) non-concentrating and concentrating solar collectors (a flat plate, an evacuated tube, a linear Fresnel and a parabolic trough), (iii) organic Rankine cycle power blocks and (iv) storage tanks (direct thermal storage systems). The last two technologies were represented by surrogate models so that a large number of decision variables could be optimized simultaneously. The optimization considered local climate conditions hourly to provide irradiation, local temperature and wind speed. The case studies indicated that optimized ORCs for waste heat recovery are economically competitive, reaching internal rates of return (IRRs) of 44%, 39% and 34% for a waste heat of 50 MWt at 350 °C, 300 °C and 250 °C, respectively. On the other hand, heliothermic technologies were not selected by the algorithm and provided non-competitive results for the analyzed cases. Full article

This study experimentally investigated the performance of a PVT air collector coupled with a triangular block. The triangular block, newly suggested by the authors, is a triangular-shaped obstacle and was inserted at the bottom of the PVT air collector to enhance the heat transfer performance of the collector. The experiment was carried out in actual climate conditions in Korea with two air mass flow rate conditions: 0.03606 kg/m² s and 0.06948 kg/m² s. Results show the average values of electrical efficiency of the collector during the test period to be 16.15% and 16.43% for each air mass flow rate, while thermal efficiencies were 28.83% and 38.36%, respectively. The average values of total energy efficiencies were found to be 44.99% and 54.79%, respectively. The results show that air mass flow rate has a large impact on thermal and total energy efficiency, while it has a small impact on electrical efficiency. Furthermore, it was confirmed that the PVT air collector coupled with a triangular block can enhance the utilization of solar energy since the thermal performance was higher than that of the collector without a triangular block. Full article

Climate change is one of the biggest environmental, political, economic, technological, and social challenges of the 21st century. Due to ever-increasing fossil fuels costs. The world energy system should be transitioned to renewable energy sources to mitigate greenhouse gas emissions. Solar energy is one of the suitable alternatives to fossil fuel usage. Currently, the most widely available solar technologies are solar photovoltaic (PV) and solar thermal. The integration of these two techniques enables the exploitation of the most significant amount of solar radiation. This combination has led to a hybrid photovoltaic/thermal system (PV/T). Concentrated solar radiation on PV cells, known as concentrated photovoltaic (CPV), effectively decreases PV receivers’ area and harnesses the same quantity of solar radiation. However, the main problem with CPV is the elevated PV surface temperature, which often requires active cooling. This issue can be solved by introducing a Concentrating Photovoltaic Thermal (CPVT) system. In this article, a new CPVT hybrid system based on Point Focus Fresnel Lens (PFFL) and embedded Multi Junction Photovoltaic (MJPV) (GaInP/InGaAs/Ge) cells has been experimentally investigated and numerically modelled under indoor conditions. Experiments and simulations were carried out at different heat transfer fluid (HTF) flow rates and under constant irradiation emitted from a sun simulator. The results indicate that the thermal and electrical performance of the CPVT system improves under the testing conditions, where the total efficiency was 68.7% and 73.5% for the experimental and CFD models, respectively. At the same time, the highest thermal efficiency of the experimental and CFD models was 49.5% and 55.4%, respectively. In contrast, the highest electrical efficiency was 36.5% and 37.1%. Therefore, the CPVT system has an excellent possibility of being competitive with conventional power generation systems. Full article

With the increasing installed capacity of photovoltaic (PV) power generation, it has become a significant challenge to detect abnormalities and faults of PV modules in a timely manner. Considering that all the fault information of the PV module is contained in the current-voltage (I-V) curve, this pioneering study takes the I-V curve as the input and proposes a PV-fault identification method based on improved deep residual shrinkage networks (DRSN). This method can not only identify single faults (e.g., short-circuit, partial-shading, and abnormal aging), but also effectively identify the simultaneous existence of hybrid faults. Moreover, it can achieve end-to-end fault diagnosis. The diagnostic accuracy of the proposed method on the measured data reaches 97.73%, is better than the convolutional neural network (CNN), the support vector machine (SVM), the deep residual network (ResNet), and the stage-wise additive modeling using multi-class exponential loss function based on the classification and regression tree (SAMME-CART). In addition, the possibility of the aforementioned method running on the Raspberry Pi has been verified in this study, which is of great significance for realizing the edge diagnosis of PV fault. Full article

Photovoltaic technology mainly uses beam, diffused, and reflected solar radiation to produce power. To increase the photovoltaic power output, the surface of the solar panel must be at the optimal tilt angle. In this paper, a numerical study is carried out to investigate the optimal tilt angle for a 1 MW PV system installed at Sukkur IBA University (latitude = 27.7268° N, longitude = 68.8191° E). Moreover, power output, efficiency, and fill factor are calculated for polycrystalline and monocrystalline solar panels. Results obtained at different tilt angles are used to compare the solar gain from photovoltaic modules installed at the university. In conclusion, an optimal tilt angle is decided for both polycrystalline and monocrystalline solar panels used at Sukkur IBA University. It was found that the optimal tilt angle for the installed 1 MW systems is 29.5 degrees. Full article

One effect of moisture ingress on solar panels is potential induced degradation (PID). Solar panels affected by PID experience large leakage currents between the solar cells and the module’s frame, which leads to substantial power degradation. In the present work, the temperature coefficients of 3 old PV panels affected by PID were investigated. In the electroluminescence images, solar cells nearer to the edge of the modules appear darker due to ohmic shunting. IR thermal images acquired under clear sky outdoor conditions show that the majority of the warmer cells (hotspots) were located closer to the edge of the modules. The difference in cell temperature (∆T) due to PID effect ranges from 7 °C to 15 °C for the 3 field-aged modules. The average temperature coefficient of efficiency (β_ηm) was found to be −0.5%/°C. Also, it was observed that the temperature coefficients of open circuit voltage (β_Voc = −0.4%/°C), maximum power point voltage (β_Vmpp = −0.5%/°C), and fill factor (β_FF = −0.2%/°C), were the underlying factors for the degradation in the P_max of the old solar panels affected by PID. This accounted for an average 1.2%/year overall degradation in the efficiency of these modules. Most notably, it was discovered that the PV modules affected by PID show negative temperature coefficients of maximum power point current (β_Jmpp) due to large leakage currents. This observed negative β_Jmpp we believe is characteristic of PV panels affected by PID. Full article

DC series arc fault detection is essential for improving the productivity of photovoltaic (PV) stations. The DC series arc fault also poses severe fire hazards to the solar equipment and surrounding building. DC series arc faults must be detected early to provide reliable and safe power delivery while preventing fire hazards. However, it is challenging to detect DC series arc faults using conventional overcurrent and current differential methods because these faults produce only minor current variations. Furthermore, it is hard to define their characteristics for detection due to the randomness of DC arc faults and other arc-like transients. This paper focuses on investigating a novel method to extract arc characteristics for reliably detecting DC series arc faults in PV systems. This methodology first uses an adaptive local mean decomposition (ALMD) algorithm to decompose the current samples into production functions (PFs) representing information from different frequency bands, then selects the PFs that best characterize the arc fault, and then calculates its multiscale fuzzy entropies (MFEs). Eventually, MFE values are inputted to the trained SVM algorithm to identify the series arc fault accurately. Furthermore, the proposed technique is compared to the logistic regression algorithm and naive Bayes algorithm in terms of several metrics assessing algorithms’ validity for detecting arc faults in PV systems. Arc fault data acquired from a PV arc-generating experiment platform are utilized to authenticate the effectiveness and feasibility of the proposed method. The experimental results indicated that the proposed technique could efficiently classify the arc fault data and normal data and detect the DC series arc faults in less than 1 ms with an accuracy rate of 98.75%. Full article

In recent years, concentrating solar collectors have been integrated with several district heating systems with the aim of taking advantage of their low heat losses. The present study investigates the Brønderslev combined heat and power plant, which consists of a 16.6 MW parabolic trough collector field, two biomass boilers, and an organic Rankine cycle system. The study focuses on the solar collector field performance and integration with the district heating network. An in situ characterization of the parabolic solar collector field using the quasi-dynamic test method found that the field had a peak efficiency of 72.7%. Furthermore, a control strategy for supplying a constant outlet temperature to the district heating network was presented and implemented in a TRNSYS simulation model of the solar collector field. The developed simulation model was validated by comparison to measurement data. Subsequently, the simulation model was used to conduct a sensitivity analysis of the influence of the collector row spacing and tracking axis orientation. The results showed that the current suboptimal tracking axis rotation, made necessary by the geography of the location, only reduced the annual power output by 1% compared to the optimal configuration. Additionally, there were only minor improvements in the annual heat output when the row spacing was increased past 15 m (ground cover ratio of 0.38). Full article

Renewable energy sources and sustainability have been attracting increased focus and development worldwide. Qatar is no exception, as it has ambitious plans to deploy renewable energy sources on a mass scale. Qatar may also investigate initiating and permitting the deployment of rooftop photovoltaic (PV) systems for residential households. Therefore, a research gap has been introduced regarding the system design, grid compatibility, economic viability, and energy consumption produced from household rooftop PV systems. Additionally, the lack of supporting policies and a feed-in tariff creates further research and development topics. Therefore, using collected data regarding household power consumption and rooftop PV generation, the purposes of this research study are as follows: (1) determining the economic aspects and practicality of using energy storage systems for self-consumption values; and (2) evaluating the economic viability of rooftop PV systems under different policies and electricity rate schemes. The insights of the results of this study can serve as a stepping stone for decisions and policymakers regarding the application of rooftop PV systems in Qatar. This study utilizes empirical evidence and an economic model to evaluate rooftop PV systems in Qatar and can also be applicable in the middle east region. A few studies in the region produce complementary results, which further supports our findings; however, what makes this paper unique is the use of different economic tools and real collected data while investigating multiple economic and energy policy scenarios. Full article

The power-generation capacity of grid-connected photovoltaic (PV) power systems is increasing. As output power forecasting is required by electricity market participants and utility operators for the stable operation of power systems, several methods have been proposed using physical and statistical approaches for various time ranges. A short-term (30 min ahead) forecasting method had been proposed previously for multiple PV systems using motion estimation. This method forecasts the short time ahead PV power generation by estimating the motion between two geographical images of the distributed PV power systems. In this method, the parameter $\lambda$, which relates the smoothness of the resulting motion vector field and affects the accuracy of the forecasting, is important. This study focuses on the parameter $\lambda$ and evaluates the effect of changing this parameter on forecasting accuracy. In the periods with drastic power output changes, the forecasting was conducted on 101 PV systems. The results indicate that the absolute mean error of the proposed method with the best parameter is 10.3%, whereas that of the persistence forecasting method is 23.7%. Therefore, the proposed method is effective in forecasting periods when PV output changes drastically within a short time interval. Full article

This study examines the sources of energy related carbon dioxide (CO₂) emissions, the hazards of climate change and greenhouse gas (GHG) emissions, the global solar energy potential, renewable energy sustainability indicators, impediments, and the environmental implications of fossil fuels. The purpose of this study is to investigate viewpoints on solar energy technologies for sustainable development, with a particular emphasis on photovoltaic (PV), as well as the literature on solar energy technology performance, in order to ascertain worldwide solar energy adoption trends. The discussions address the solar industry’s fundamental ideas, the global energy scenario, the highlights of research conducted to improve the solar industry, prospective applications and future challenges for a more efficient solar industry that may help alleviate the energy crisis. A review of the framework and development of Renewable Energy Sources (RES) and Renewable Energy Laws (REL) on a global scale was conducted. Full article

Understanding the implications of introducing increasing shares of low-carbon technologies such as heat pumps and electric vehicles on the electricity network demand patterns is essential in today’s fast changing energy mixture. Application of heat pumps for heating and cooling, combined with the rooftop installation of photovoltaic panels, is already considered as a convenient retrofitting strategy towards building electrification. This may further profit from the parallel, rapid electrification of the automotive powertrain, as demonstrated in the present study. Exploitation of the combined battery storage of the house owners’ electric car(s) may help cover, to a significant degree, the building’s and cars’ electricity needs. To this end, an efficient single family house’s energy system with an optimized rooftop PV installation, heat pump heating and cooling, and two high efficiency electric cars is studied by transient simulation. The use of TRNSYS simulation environment makes clear the interaction of the house’s heating, ventilation, and air conditioning (HVAC) system, the house’s and cars’ batteries, and the rooftop PV system in transient operation. The building’s and EV’s energy performance on a daily, monthly, and seasonal level is compared with the respective demand curves and energy sources of the Greek electricity network. The specific design of the house’s energy system makes it a net exporter of electricity to the grid, to an annual amount of 5000 kWh. On the other hand, electricity imports are slightly exceeding 400 kWh and limited to the first two months of the year. In addition to the self-sufficiency of the household, the impact to the electricity grid becomes favorable due to the phase shift of the electricity export towards the late afternoon hours, thus assisting the evening ramp-up and adding to the grid’s stability and resilience. Based on the results of this study, the possibility of combining the financial incentives for the purchase of an EV with those for the installation of rooftop PV in the owners’ house is very promising and worth considering, due to the demonstrated synergy of electrical storage with the rooftop photovoltaic installations. Full article

The current investigation shows a possible new pathway for more efficient and cost-effective energy-harvesting photovoltaic devices. Our approach could permit all emerging technologies that are currently used for indoors and smart buildings to go a step forward and could be used for outdoor applications. The investigated architecture is a very promising geometry especially for Dye-Sensitized Solar Cells (DSSCs). It turns their main drawback, the lowering of their efficiency and lifetime when operating at high solar irradiation density, into an asset by increasing the total active area per horizontal unit area for light harvesting, while preserving the active elements from degradation and extending durable lifetime. The investigated architecture is based on a symmetric “U” type geometry, which is constructed by a highly reflective material on the inner surface. Solar irradiation is reflected internally at the bottom of the construction and splits towards two opposite sided solar cells; the two cells form a cavity where the solar light multiplies and is successively absorbed. Consequently, the vertically incoming irradiation is reduced when reaching the vertical internal sides on which the DSSCs are mounted. Thus, the solar cells operate at low light intensities, which provide significant lifetime extension and efficiency enhancement. Interestingly, the electrical energy per effective surface unit, which is produced by the two vertical DSSCs, is at least equal to that of a standalone, vertically irradiated cell. The advantage of the new architecture is that protects DSSCs from their degradation and deterioration, although the entire system operates under high illumination. This makes the cells more efficient outdoors, with a comparable performance to indoor conditions. Full article

Colloidal semiconductor nanocrystals have generated tremendous interest because of their solution processability and robust tunability. Among such nanocrystals, the colloidal quantum dot (CQD) draws the most attention for its well-known quantum size effects. In the last decade, applications of CQDs have been booming in electronics and optoelectronics, especially in photovoltaics. Electronically doped semiconductors are critical in the fabrication of solar cells, because carefully designed band structures are able to promote efficient charge extraction. Unlike conventional semiconductors, diffusion and ion implantation technologies are not suitable for doping CQDs. Therefore, researchers have creatively developed alternative doping methods for CQD materials and devices. In order to provide a state-of-the-art summary and comprehensive understanding to this research community, we focused on various doping techniques and their applications for photovoltaics and demystify them from different perspectives. By analyzing two classes of CQDs, lead chalcogenide CQDs and perovskite CQDs, we compared different working scenarios of each technique, summarized the development in this field, and raised our own future perspectives. Full article

The use of renewable energies, such as Photovoltaic (PV) solar power, is necessary to meet the growing energy consumption. PV solar power generation has intrinsic characteristics related to the climatic variables that cause intermittence during the generation process, promoting instabilities and insecurity in the electrical system. One of the solutions for this problem uses methods for the Prediction of Solar Photovoltaic Power Generation (PSPPG). In this context, the aim of this study is to develop and compare the prediction accuracy of solar irradiance between Artificial Neural Network (ANN) and Long-Term Short Memory (LSTM) network models, from a comprehensive analysis that simultaneously considers two distinct sets of exogenous meteorological input variables and three short-term prediction horizons (1, 15 and 60 min), in a controlled experimental environment. The results indicate that there is a significant difference (p < 0.001) in the prediction accuracy between the ANN and LSTM models, with better overall prediction accuracy skill for the LSTM models (MAPE = 19.5%), except for the 60 min prediction horizon. Furthermore, the accuracy difference between the ANN and LSTM models decreased as the prediction horizon increased, and no significant influence was observed on the accuracy of the prediction with both sets of evaluated meteorological input variables. Full article

The receiver serves as a critical component in tower-type concentrated solar power plants. Responsible for light-heat conversion, the efficiency of the receiver significantly affects the overall performance of the power plant. In the current study, the thermal performance of external receivers was investigated. An experiment was set up similarly using the solar simulator to experimentally investigate the heat losses of a billboard receiver. A billboard-type external receiver was designed, fabricated, and experimented with. A solar simulator having seven xenon lamps characteristics similar to the sunlight spectrum was used to obtain heat flux at the surface of the receiver. Convection losses in the head-on wind direction were evaluated, along with the radiation losses. The thermal efficiency of the billboard receiver calculated experimentally was around 83.9%. Numerical simulations were also carried out to compare the results against the experimental data. A variation of ±5% observed between both results validate the model proposed in the current study. Full article

Variability in solar irradiance has an impact on the stability of solar systems and the grid’s safety. With the decreasing cost of solar panels and recent advancements in energy conversion technology, precise solar energy forecasting is critical for energy system integration. Despite extensive research, there is still potential for advancement of solar irradiance prediction accuracy, especially global horizontal irradiance. Global Horizontal Irradiance (GHI) (unit: KWh/m²) and the Plane Of Array (POA) irradiance (unit: W/m²) were used as the forecasting objectives in this research, and a hybrid short-term solar irradiance prediction model called modified multi-step Convolutional Neural Network (CNN)-stacked Long-Short-Term-Memory network (LSTM) with drop-out was proposed. The real solar data from Sweihan Photovoltaic Independent Power Project in Abu Dhabi, UAE is preprocessed, and features were extracted using modified CNN layers. The output result from CNN is used to predict the targets using a stacked LSTM network and the efficiency is proved by comparing statistical performance measures in terms of Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Squared Error (MAE), and R² scores, with other contemporary machine learning and deep-learning-based models. The proposed model offered the best RMSE and R² values of 0.36 and 0.98 for solar irradiance prediction and 61.24 with R² 0.96 for POA prediction, which also showed better performance as compared to the published works in the literature. Full article

In the last few years, renewable energies became more socially and economically relevant, and among them, photovoltaic systems stand out. Residential self-consumption of electricity is a field with great potential, and implementation of grid-connected photovoltaic systems (GCPS) is in full rise. The installation of distributed generation systems in residential environments could alter the performance of low-voltage distribution networks, since these are designed for unidirectional power flow and adding these generators means fluctuations in power-flows. For these reasons, a study of the fundamental magnitudes of three low-voltage distribution networks located in Madrid was made for various photovoltaic penetration rates, making use of simulations via the software OpenDSS and subsequent analysis of results. The research concludes that, among other aspects, GCPS produce load flow variations that are dependent on: the penetration rates; the distance from the point of interest and the distribution transformer, increasing the voltage variation between the most productive hours and the night hours with that distance; and on the rate between consumption and generation, so that when it diminishes, the self-sufficiency of the system increases, and with it the voltage of all the buses that tend to the rated voltage. Moreover, there are wide seasonal fluctuations: specifically, in summer months, generation profiles override consumption fluctuations, while in winter months consumption guides voltage and power profiles. Both the code implemented and the results of the analysis were published in an open source website using a free software license. Full article

Bifacial photovoltaic modules combined with horizontal single-axis tracker are widely used to achieve the lowest levelized cost of energy (LCOE). In this study, to further increase the power production of photovoltaic systems, the bifacial companion method is proposed for light supplementation and the efficiency enhancement of tilted bifacial modules with a horizontal single-axis tracker. Specifically, a solar reflector is added to the rear end of the tilted bifacial photovoltaic module to guide the sunlight and promote power generation on the rear end. The technical feasibility of the proposed method is verified through optimal calculation and prototype experimental test. The theoretical calculation results suggest that the bifacial companion system is particularly suitable for mid-to-high latitude areas. The higher the latitude, the higher the gain ratio of generated power in the system; there is an optimal module tilt angle that maximizes the efficiency at different latitudes. The closer the module tilt angle to the optimal tilt angle, the higher the power generation efficiency of the system. Meanwhile, compared to the fixed solar reflector, the use of tracking solar reflector is more conducive to improving the power generation efficiency of the system. For the 37.5° latitude area, the annual average power generation gain ratio of the bifacial companion system with tracking solar reflector and fixed solar reflector can reach up to 30% and 17%, respectively. Additionally, the test results for the three sets of bifacial companion prototypes (module tilt angles of 10°, 20°, and 30°) with a fixed solar reflector show that the maximum gain ratio of daily power generation in August 2021 are 8.2%, 13%, and 18.1%, and that in September 2021 are 7%, 8.7% and 13.7%, respectively, which are consistent with the theoretical results. Full article

In recent years, phase change materials (PCMs) have been presented as a suitable alternative for thermal energy storage (TES) systems for solar water heater (SWH) applications. However, PCMs’ low thermal conductivity and the high dependence on external conditions are the main challenges during the design of TES systems with PCMs. Design actions to improve the performance of the TES systems are crucial to achieve the necessary stored/released thermal energy and guarantee the all-day operation of SWHs under specific system requirements. In this study, a TES with PCM in the configuration of a heat exchanger was redesigned, focused on achieving two main targets: an outlet water temperature over 43 °C during discharging time (15 h) and efficiency over 60% to supply the hot water demand of two families (400 L). A four-step redesign methodology was proposed and implemented through numerical simulations to address this aim. It was concluded that the type, encapsulation shape, and amount of PCM slightly impacted the system’s performance; however, selecting a suitable sensible heat storage material had the highest impact on meeting the system’s targets. The redesigned TES reached 15 operating hours with a minimum outlet water temperature of 45.30 °C and efficiency of 76.08%. Full article

This paper investigates double-pass solar air thermal collectors with lava rock as the porous media. The addition of lava rock serves as short-term sensible thermal storage for a solar drying system. It also enhances the convective heat transfer rate to the airflow due to an increased heat transfer area and increased turbulence in the air channel. A mathematical model was developed based on energy balance equations and was numerically solved in MATLAB. The collector’s thermal performance was studied at various levels of solar intensity and at different wind speeds for different design parameters: collector size, air mass flow rate, and lava rock volume. From the study, the optimum efficiencies that were obtained in the range between the intensities of 500 W/m² and 800 W/m² were 62% to 64%, respectively, with an optimum flow rate of 0.035 kg/s. The optimum porosity of about 89% was selected for the collector by considering the pressure drop and thermal efficiency. An optimal temperature output range between 41.7 °C and 48.3 °C could be achieved and was suitable for agricultural and food drying applications. Meanwhile, compared to conventional DPSAHs, the average percentage increase in the output temperature of the DPSAH with lava rock was found to be higher by 17.5%. Full article

Solar photovoltaic energy has experienced significant growth in the last decade, as well as the challenges related to the intermittency of power generation inherent to this process. In this paper we propose to perform short-term forecasting of solar PV generation using fuzzy time series (FTS). Two FTS methods are proposed and evaluated to obtain a global horizontal irradiance (GHI) value. The first is the weighted method and the second is the fuzzy information granular method. Using the direct proportionality of the power with the GHI, the spatial smoothing process was applied, obtaining spatial irradiance on which a first-order low pass filter was applied to simulated power photovoltaic system generation. Thus, this study proposed indirect and direct forecasting of solar photovoltaic generation which was statistically evaluated and the results showed that the indirect prediction showed better performance with GHI than the power simulation. Error statistics, such as RMSE and MBE, show that the fuzzy information granular method performs better than the weighted method in GHI forecasting. Full article

The cavity receiver’s thermal conversion performance is critical for parabolic dish and tower Concentrated Solar Power (CSP) systems. Distinct from precedent research aiming to increase the receiver’s absorption through cavity geometry optimization, the objective of this work was to investigate the thermal conversion performance of a novel, positive conical cavity receiver design, following the heat loss reduction approach with simplified pipe forming, to stress the effectiveness of this approach in cavity receiver design, and to provide data for future optimization of the proposed design. To accomplish these goals, the novel receiver and existing designs’ heat flux absorption and heat loss are compared numerically. The resulting conversion power is also experimentally validated. The concept is inspired by analysis of formulas, suggesting the novel design may realize a thermal conversion improvement of 8.6%, at 650 K, and increases with the rise in temperature. The comprehensive numerical investigation combines ray tracing of identical incoming radiation to investigate the receiver absorption and CFD methods to investigate the cavities’ heat loss at identical temperatures. The absorption acquired is unoptimized. The novel design can reduce the heat loss by as much as 91.8% when compared with a negative conical design at 650 K, resulting in a 12.3% improvement in conversion power. The experimental investigation measures the energy conversion to the working fluid in different cavities under identical incoming radiation. The novel receiver outperforms by over 5.6% in the setup. After correcting boundary conditions using experiment measurements, the experimental and numerical results are comparable. This research proves that the novel positive conical receiver has a better thermal conversion performance over 650 K; thus, the heat loss reduction approach is effective and feasible in receiver designs within this temperature range. Full article

This review uses a more holistic approach to provide comprehensive information and up-to-date knowledge on solar energy development in India and scientific and technological advancement. This review describes the types of solar photovoltaic (PV) systems, existing solar technologies, and the structure of PV systems. Substantial emphasis has been given to understanding the potential impacts of COVID-19 on the solar energy installed capacity. In addition, we evaluated the prospects of solar energy and the revival of growth in solar energy installation post-COVID-19. Further, we described the challenges caused by transitions and cloud enhancement on smaller and larger PV systems on the solar power amended grid-system. While the review is focused on evaluating the solar energy growth in India, we used a broader approach to compare the existing solar technologies available across the world. The need for recycling waste from solar energy systems has been emphasized. Improved PV cell efficiencies and trends in cost reductions have been provided to understand the overall growth of solar-based energy production. Further, to understand the existing technologies used in PV cell production, we have reviewed monocrystalline and polycrystalline cell structures and their limitations. In terms of solar energy production and the application of various solar technologies, we have used the latest available literature to cover stand-alone PV and on-grid PV systems. More than 5000 trillion kWh/year solar energy incidents over India are estimated, with most parts receiving 4–7 kWh/m². Currently, energy consumption in India is about 1.13 trillion kWh/year, and production is about 1.38 trillion kWh/year, which indicates production capacities are slightly higher than actual demand. Out of a total of 100 GW of installed renewable energy capacity, the existing solar capacity in India is about 40 GW. Over the past ten years, the solar energy production capacity has increased by over 24,000%. By 2030, the total renewable energy capacity is expected to be 450 GW, and solar energy is likely to play a crucial role (over 60%). In the wake of the increased emphasis on solar energy and the substantial impacts of COVID-19 on solar energy installations, this review provides the most updated and comprehensive information on the current solar energy systems, available technologies, growth potential, prospect of solar energy, and need for growth in the solar waste recycling industry. We expect the analysis and evaluation of technologies provided here will add to the existing literature to benefit stakeholders, scientists, and policymakers. Full article

In the present study, the evaluation of potential improvement of the overall efficiency of a common PV panel, valorizing the heat extracted by a heat exchanger that is integrated on its back side, either into work using an endoreversible Carnot engine or into cold by using an endoreversible tri-thermal machine consisting of a heat-driven refrigeration machine operating between three temperature sources and sink (such as a liquid/gas absorption machine), was carried out. A simplified thermodynamic analysis of the PV/thermal collector shows that there are two optimal operating temperatures ${\tilde{T}}_h$ and $T_h^{*}$ of the panels, which maximize either the thermal exergy or the overall exergy of the PV panel, respectively. The cold produced by the endoreversible tri-thermal machine during the operating conditions of the PV/thermal collector at ${\tilde{T}}_h$ is higher with a coefficient of performance (COP) of 0.24 thanks to the higher heat recovery potential. In the case of using the cold produced by a tri-thermal machine to actively cool of an additional PV panel in order to increase its electrical performances, the operating conditions at the optimal temperature $T_h^{*}$ provide a larger and more stable gain: the gain is about 12.2% compared with the conventional PV panel when the operating temperature of the second cooled panel varies from 15 to 35 °C. Full article

Renewable energy sources are becoming more relevant in recent decades in power generation, leading to investment in developing efficient systems. Specifically, in photovoltaic energy, modular converters are attracting interest since their characteristics enable them to work at high voltage and optimize the generated energy. However, the control strategies found the literature limit the scalability potential of modular converters. The main aim of this paper is to propose a scalable control strategy for a grid-tied CHB (Cascaded H-Bridge) converter for large-scale photovoltaic power plants. The control proposed is able to take full advantage of converter scalability and modularity, being based on the parameters needed for bipolar sinusoidal PWM (Pulse Width Modulation), and thus reducing the calculus required and simplifying its implementation. Power imbalances are overcome including the zero-sequence vector injection to allow power exchange between phases. Furthermore, the parameter used for power factor control has been discretized and discretization time analysis shows that the control strategy is stable and does not require a high-speed communication channel. For validation purposes, simulations are conducted on a downsized 12 H-bridge model. Full article

As low-cost, widely distributed and easily accessible renewable clean energy, solar energy has attracted more and more attention. Direct absorption solar collectors can convert solar energy into heat, but their efficiency is closely related to the absorption performance of the working fluid. In order to improve the absorption efficiency of direct absorption solar collectors, an experimental study on the selective absorption of solar energy by hybrid nanofluids was carried out. Five hybrid nanofluids were prepared and characterized, and the energy transfer advantages of hybrid nanofluid over single nanofluid were carefully studied. Experiments have found that the light-to-heat conversion properties of hybrid nanofluids show no obvious advantages or disadvantages compared with single nanofluid, and their performance is closely related to the types of nanoparticles. In addition, the hybrid nanofluid generally has two peaks, exactly the same as the single nanofluid in the mixed component, but the absorption curve is flatter than that of the single nanofluid. Further research of more types of hybrid nanofluids can provide new insights into the use of solar energy. Full article

The installation of photovoltaic (PV) systems in the Maltese Islands plays an important role in allowing Malta to increase its share in renewable energy to meet the set European Union targets. In the Maltese residential sector, PV systems are generally installed on rooftops of households with a south-facing orientation and a 30° inclination angle. The scope of this study is to present a methodology to maximise the income for residents from electricity generated, by comparing the output of electricity generation with the electricity consumption patterns of different household types and consequently identifying the most favourable installation configurations of these PV systems. The research was carried out by simulating the monthly electricity generation of a 3 kilowatt-peak PV system for a year, as well as the hourly electricity generation for a day in each season of the year using the PVsyst software package. A total of 21 configurations were studied by altering the orientation and inclination angles used to install the PV system. This study confirms that a south-facing PV system inclined at 30° generates the most electricity in a year. However, when compared with electricity consumption patterns of low-, medium- and high-consumption households, it is shown that a south-facing PV system inclined at 40° provides a better income for residents. Full article

In this study, recorded empirical data were applied with a practical approach to investigate the optimal tilt angle of the flat plate collectors facing south for a long period in Tehran, Iran. The data included 20 years of recorded average total radiation on the horizontal plane in Tehran’s meteorological station. Based on the previous studies, the annual optimum tilt angle for Tehran was estimated at 33 degrees annually; however, this estimation does not focus on the energy absorption and effectiveness of changing the tilt angle monthly, seasonally, and bi-annually via measured data. This paper aims to explain this distinction between various radiation receptions with different tilt angle adjustments. This study shows that annual solar cumulative radiation energy gained via a monthly tilt angle can be approximately 7% higher than that achieved with an annual tilt angle setup. Additionally, the seasonal and bi-annual tilt angles have about 6% more annual cumulative radiation absorption than the annual tilt angle setup. Moreover, with consideration of similar monthly received radiation, the results illustrate that the radiation gained with a monthly tilt angle set up was 20% greater in the summer months than an annual tilt angle adjustment. Full article

The design of electron transport layers (ETLs) with good optoelectronic properties is one of the keys to the improvement of the power conversion efficiencies (PCEs) and stability of perovskite solar cells (PSCs). Titanium dioxide (TiO₂), one of the most widely used ETL in PSCs, is characterized by low electrical conductivity that increases the series resistance of PSCs, thus limiting their PCEs. In this work, we incorporated tin oxide (SnO₂) into titanium dioxide (TiO₂) and studied the evolution of its microstructural and optoelectronic properties with SnO₂ loading. The thin films were then integrated as ETLs in a regular planar Formamidinium (FA)-rich mixed lead halide PSCs so as to assess the overall effect of SnO₂ incorporation on their charge transport and Photovoltaic (PV) characteristics. Analysis of the fabricated PSCs devices revealed that the best performing devices; based on the ETL modified with 0.2 proportion of SnO_2; had an average PCE of 17.35 ± 1.39%, which was about 7.16% higher than those with pristine TiO₂ as ETL. The improvement in the PCE of the PSC devices with 0.2 SnO₂ content in the ETL was attributed to the improved electron extraction and transport ability as revealed by the Time Resolved Photoluminescence (TRPL) and Electrochemical Impedance Spectroscopy (EIS) studies. Full article

Microinverters for Building Integrated Photovoltaic (BIPV) systems must have had a small number of components, be efficient, and be reliable. In this context, a single-phase Buck-Boost Single-stage Microinverter (BBSM) for grid-connected BIPV systems is presented. The concept of topology is extracted from the buck-boost converter. The leakage current in the system is kept under control. It uses an optimal number of active and passive components to function at a high-efficiency level. The suggested topology provides a high level of reliability due to the absence of shoot-through problems. To validate the findings, a simulation in combination with an experimental system for a 70 W system is developed with the design approach. The efficiency of the microinverter, total harmonic distortion of the grid current are measured as 96.4% and 4.09% respectively. Finally, a comparison study has indicated the advantages and disadvantages of the suggested inverter. Full article

In the present article, the heat transfer and fluid flow of the air in a compact microchannel gas heater (MCGH) was experimentally quantified. To understand the effect of heat flux value (HFV), and inlet velocity on the heat transfer coefficient (HTC), wall temperature, friction factor, Nusselt number, average pressure-drop value (PDV) and performance index (PI), a microchannel gas heater was constructed and tested with pressurized air. The results showed that the HTC was 20 W/(sqmK) to 70 W/(sqmK), corresponding to inlet velocities 6.7 m/s and 16.7 m/s, respectively within HFV < 1 kW/m². Also, the highest PI was 1.19 meaning that the HT rate can be increased by 19% at u = 15 m/s in comparison with the reference case (at u = 13.3 m/s). Likewise, the HTC was intensified once the inlet velocity is increased. It was also identified that increasing the HFV has a strong effect on wall temperature, however, slightly changes the HTC. By increasing the heat flux value from 200 W/sqm to 1000 W/sqm, the HTC increased only by 4.7% which was associated with the poor thermophysical properties of air flowing inside MCGH. Two main mechanisms of wall slip and viscous heating were identified as main contributors to the heat transfer enhancement in MCGH. Full article

Photovoltaic power plants nowadays play an important role in the context of energy generation based on renewable sources. With the purpose of obtaining maximum efficiency, the PV modules of these power plants are installed in trackers. However, the mobile structure of the trackers is subject to faults, which can compromise the desired perpendicular position between the PV modules and the brightest point in the sky. So, the diagnosis of a fault in the trackers is fundamental to ensure the maximum energy production. Approaches based on sensors and statistical methods have been researched but they are expensive and time consuming. To overcome these problems, a new method is proposed for the fault diagnosis in the trackers of the PV systems based on a machine learning approach. In this type of approach the developed method can be classified into two major categories: supervised and unsupervised. In accordance with this, to implement the desired fault diagnosis, an unsupervised method based on a new image processing algorithm to determine the PV slopes is proposed. The fault detection is obtained comparing the slopes of several modules. This algorithm is based on a new image processing approach in which principal component analysis (PCA) is used. Instead of using the PCA to reduce the data dimension, as is usual, it is proposed to use it to determine the slope of an object. The use of the proposed approach presents several benefits, namely, avoiding the use of a wide range of data and specific sensors, fast detection and reliability even with incomplete images due to reflections and other problems. Based on this algorithm, a deviation index is also proposed that will be used to discriminate the panel(s) under fault. Several test cases are used to test and validate the proposed approach. From the obtained results, it is possible to verify that the PCA can successfully be adapted and used in image processing algorithms to determine the slope of the PV modules and so effectively detect a fault in the tracker, even when there are incomplete parts of an object in the image. Full article

Photo-excited charge carriers play a vital role in photocatalysts and photovoltaics, and their dynamic processes must be understood to improve their efficiencies by controlling them. The photo-excited charge carriers in photocatalytic materials are usually trapped to the defect states in the picosecond time range and are subject to recombination to the nanosecond to microsecond order. When photo-excited charge carrier dynamics are observed via refractive index changes, especially in particulate photocatalytic materials, another response between the trapping and recombination phases is often observed. This response has always provided the gradual increase of the refractive index changes in the nanosecond order, and we propose that the shallowly trapped charge carriers could still diffuse and be trapped to other states during this process. We examined various photocatalytic materials such as TiO₂, SrTiO₃, hematite, BiVO₄, and methylammonium lead iodide for similar rising responses. Based on our assumption of surface trapping with diffusion, the responses were fit with the theoretical model with sufficient accuracy. We propose that these slow charge trapping processes must be included to fully understand the charge carrier dynamics of particulate photocatalytic materials. Full article

In this work, a smart solar still prototype for water desalination is designed. It consists of a basic solar still, a solar preheater and a remote monitoring system based on the Internet of Things (IoT) technique. The monitoring system is developed and integrated into the hybrid solar still in order to control its evolution online, as well the quality of the freshwater provided by checking measured parameters such as pH. Thanks to the IoT technique, parameters collected by the monitoring system (e.g., air temperatures, relative humidity, etc.) are uploaded to the cloud for online remote monitoring. The users are notified by an SMS about the status of the system (e.g., water level in the basin, water in the tank, etc.), using an GSM module. The whole system, including the preheater, water pump, valve, sensors and an electronic board, is powered by a photovoltaic module of 75 Wp. The results showed that by adding a solar preheater system, the evaporation process is accelerated and, consequently, the daily yield is improved and reaches the value of 12.165 L/m²/day. The saline concentration of the tested ground water is 3.9 g/Kg (0.39%), and, after desalination, the salinity is 0.1 g/Kg (0.01%). Full article

Electrification is an efficient way to decarbonize by replacing fossil fuels with low-emission power. In addition, energy efficiency measures can reduce consumption, making it easier to shift to a zero-carbon society. In Québec, upgrades to aging buildings that employ electric resistance heating offer a unique opportunity to free up large amounts of hydroelectricity that can serve to decarbonize heating in other buildings. However, another source of energy would be needed to electrify mobility because efficiency measures free up small amounts of electricity in summer compared to winter. This study reveals how building efficiency measures combined with solar electricity generation provide an energy profile that matches the requirements for decarbonizing both mobility and heating. The TRNSYS software was used to simulate the annual energy performance of an existing house and retrofitted/rebuilt low-energy houses equipped with a photovoltaic (PV) roof in Montreal, Québec, Canada (45.5° N). The electricity that is made available by upgrading the houses is mainly considered for powering battery and fuel cell electric vehicles (BEVs and FCEVs) and electrifying heating in greenhouses. The results indicate that retrofitting 16% or rebuilding 12% of single-detached homes in Québec can provide enough electricity to decarbonize heating energy use in existing greenhouses and to operate the new greenhouses required for growing all fresh vegetables locally. If all the single-detached houses that employ electric resistance heating are upgraded, 33.4 and 21.8 TWh year⁻¹ of electricity would be available for decarbonization, equivalent to a 19% and 12% increase of the province’s electricity supply for the retrofitted or rebuilt houses, respectively. This is enough energy to convert 83–100% of personal vehicles to BEVs or 35–56% to FCEVs. Decarbonization using the electricity that is made available by upgrading to low-energy solar houses could reduce the province’s greenhouse gas (GHG) emissions by approximately 32% (26.5 MtCO_2eq). The time required for the initial embodied GHG emissions to surpass the emissions avoided by electrification ranges from 3.4 to 11.2 years. Building energy efficiency retrofits/rebuilds combined with photovoltaics is a promising approach for Québec to maximize the decarbonization potential of its existing energy resources while providing local energy and food security. Full article

The problem considered in the paper concerns the synthesis process of antennas for autonomous semi-passive RFID transponder/sensors dedicated to active glazing units. Glazing units are frequently used in modern multi-storey buildings to create amazing facades. When they are integrated with photovoltaic (PV) modules, active units are obtained. It is desirable, mainly for economic reasons and in order to ensure the high efficiency of a micro-photovoltaic power plant, that active glazing units are equipped with a system for monitoring their operating parameters. In connection with this, design problems occur that fall within the fields of sensor technology and radio communications. The main purpose of the presented study was to prepare appropriate input data for design tools used in the synthesis of antenna systems in the UHF band. Many important issues are considered including: proximity to structural elements of the building facade and PV cells, which disturbs the shape of the radiation pattern and affects the impedance parameters of the antenna system; the need to ensure easy integration of the RFID sensor and the specified object, without significant interference in the production of glazing units; appropriate shaping of the radiation pattern in order to enable reading and writing of the RFID tag from both inside and outside the building; impedance matching to the selected RFID chip in the broadest possible frequency range, etc. Full article

The trend to reduce CO₂ emissions in cooling processes has made it possible to increase the alternatives for integrating solar energy with thermal equipment whose viability depends on its adaptation to polygeneration schemes. Despite the enormous potential offered by the industry for cooling and heating processes, solar cooling technologies (SCT) have been explored in a limited way in the industrial sector. This work discusses the potential applications of industrial SCTs and classifies hybrid polygeneration schemes based on supplying cold, heat, electricity, and desalination of water; summarizes the leading SCTs, and details the main indicators of polygeneration configurations in terms of reductions on primary energy consumption and payback times. To achieve an energy transition in refrigeration processes, the scenarios with the most significant potential are: the food manufacturing industry (water immersion and crystallization processes), the beverage industry (fermentation and storage processes), and the mining industry (underground air conditioning). Full article

Carbon perovskite solar cells (C-PSCs) are a popular photovoltaic technology currently undergoing extensive development on the global research scene. Whilst their record efficiency now rivals that of silicon PV in small-scale devices, C-PSCs still require considerable development to progress to a commercial-scale product. This study is the first of its kind to use broad beam ion milling for C-PSCs. It investigates how the carbon ink, usually optimised for maximum sheet conductivity, impacts the infiltration of the perovskite into the active layers, which in turn impacts the performance of the cells. Through the use of secondary electron microscopy with energy-dispersive X-ray spectroscopy, infiltration defects were revealed relating to carbon flake orientation. The cross sections imaged showed between a 2% and 100% inactive area within the C-PSCs due to this carbon blocking effect. The impact of these defects on the performance of solar cells is considerable, and by better understanding these defects devices can be improved for mass manufacture. Full article

This study aimed to examine the energy and exergy indices of the rosemary drying process in a hybrid-solar dryer (HSD) and the effects of air-drying parameters on these thermodynamic indices. Drying experiments were carried out at four levels of air temperature (40, 50, 60, and 70 ${}^{\circ }$C) and three levels of air velocity (1, 1.5, and 2 m/s). Energy and exergy were calculated by application of the first and second laws of thermodynamics. Based on the principal laws, energy efficiency, exergy losses, and exergetic improvement potential rate, were evaluated. The results showed that the energy utilization ratio (EUR) ranged from 0.246 to 0.502, and energy utilization (EU) ranged from 0.017 to 0.060 (kJ/s). Exergy loss and efficiency varied from 0.009 to 0.028 (kJ/s) and from 35.08% to 78.5%, respectively, and increased with increased temperature and air velocity. It was found that the exergy loss rate was affected by temperature and air velocity because the overall heat transfer coefficient was different under these conditions. By comparison, with increasing temperature and air velocity, the exergy efficiency increased. Because most energy is used to evaporate moisture, this behavior may be explained by improved energy utilization. The drying chamber sustainability index ranged from 0.0129 to 0.0293. This study provides insights into the optimization process of drying operations and operational parameters in solar hybrid dryers that reduce energy losses and consumption. Full article

The present paper defines and assesses a new simplified method to represent the photovoltaic (PV) modules’ electrical behavior, based on the commonly used one diode and three parameters (1D + 3P) model, addressing two main objectives. The first one is to quantify and assess, at different operating conditions, the PV modules electrical behavior estimations’ accuracy provided by the well-known 1D + 3P, through a comparison based on experimental and theoretical results. The second one concerns the performance assessment of the 1D + 3P model’s suggested approximation, aiming at simplifying the mathematics instead of solving complex iterative equations, which hinges on higher computational time to obtain accurate results. Hence, experimental and theoretical data were considered, aiming at performing a thorough comparison with more than 17,000 PV modules being assessed, which was achieved by using both the California Energy Commission (CEC) database and PVsyst software. The findings show that the already known 1D + 3P model delivers satisfactory power output estimations for crystalline silicon modules and high irradiance conditions. However, its performance worsens when considering Low Irradiance and thin-film technology. In comparison with the original model, accurate results were obtained with the new simplified suggested 1D + 3P for all irradiance conditions and technologies assessed, thus proving its validity and capability of circumventing the aforementioned challenges. Full article