Search Results (11,208)

In recent years, solar energy has become popular because of its clean and renewable properties. Meanwhile, two-dimensional materials have become a new favorite in scientific research due to their unique physicochemical properties. Among them, monolayer molybdenum disulfide (MoS₂), as an outstanding representative of transition metal sulfides, is a hot research topic after graphene. Therefore, we have conducted an in-depth theoretical study and design simulation using the finite-difference method in time domain (FDTD) for a solar absorber based on the two-dimensional material MoS₂. In this paper, a broadband solar absorber and thermal emitter based on a single layer of molybdenum disulfide is designed. It is shown that the broadband absorption of the absorber is mainly due to the propagating plasma resonance on the metal surface of the patterned layer and the localized surface plasma resonance excited in the adjacent patterned air cavity. The research results show that the designed structure boasts an exceptional broadband performance, achieving an ultra-wide spectral range spanning 2040 nm, with an overall absorption efficiency exceeding 90%. Notably, it maintains an average absorption rate of 94.61% across its spectrum, and in a narrow bandwidth centered at 303 nm, it demonstrates a near-unity absorption rate, surpassing 99%, underscoring its remarkable absorptive capabilities. The weighted average absorption rate of the whole wavelength range (280 nm–2500 nm) at AM1.5 is above 95.03%, and even at the extreme temperature of up to 1500 K, its heat radiation efficiency is high. Furthermore, the solar absorber in question exhibits polarization insensitivity, ensuring its performance is not influenced by the orientation of incident light. These advantages can enable our absorber to be widely used in solar thermal photovoltaics and other fields and provide new ideas for broadband absorbers based on two-dimensional materials. Full article

Multi-junction solar cells are vital in developing reliable, green, sustainable solar cells. Consequently, the computational optimization of solar cell architecture has the potential to profoundly expedite the process of discovering high-efficiency solar cells. Copper indium gallium selenide (CIGS)-based solar cells exhibit substantial performance compared to those utilizing cadmium sulfide (CdS). Likewise, CIGS-based devices are more efficient according to their device performance, environmentally benign nature, and thus, reduced cost. Therefore, the paper introduces an optimization process of three-layered n-CdS/p-CIGS/p-GaAs (NPP)) solar cell architecture based on thickness and carrier charge density. An in-depth investigation of the numerical analysis for homojunction PPN-junction with the ’GaAs’ layer structure along with n-ZnO front contact was simulated using the Solar Cells Capacitance Simulator (SCAPS-1D) software. Subsequently, various computational optimization techniques for evaluating the effect of the thickness and the carrier density on the performance of the PPN layer on solar cell architecture were examined. The electronic characteristics by adding the GaAs layer on the top of the conventional (PN) junction further led to optimized values of the power conversion efficiency (PCE), open-circuit voltage (VOC), fill factor (FF), and short-circuit current density (JSC) of the solar cell. Lastly, the paper concludes by highlighting the most promising results of our study, showcasing the impact of adding the GaAs layer. Hence, using the optimized values from the analysis, thickness of 5 ($\mathsf{\mu }$m) and carrier density of $1\times {10}^{20}$ (1/cm) resulted in the maximum PCE, VOC, FF, and JSC of 45.7%, 1.16 V, 89.52%, and 43.88 $\left({\mathrm{mA}/\mathrm{m}}^2\right)$, respectively, for the proposed solar cell architecture. The outcomes of the study aim to pave the path for highly efficient, optimized, and robust multi-junction solar cells. Full article

Perovskite-type structures have unique crystal architecture and chemical composition, which make them highly attractive for the design of solar cells. For instance, perovskite-based solar cells have been shown to perform better than silicon cells, capable of adsorbing a wide range of light wavelengths, and they can be relatively easily manufactured at a low cost. Importantly, the perovskite-based structures can also adsorb a significant amount of hydrogen atoms into their own structure; therefore, perovskite holds promise in the solid-state storage of hydrogen. It is widely expected by the scientific community that the controlled adsorption/desorption of the hydrogen atoms into/from perovskite-based structures can help to overcome the main hydrogen storage issues such as a low volumetric density and the safety concerns (i.e., the hydrogen embrittlement affects strongly the mechanical properties of metals and, as such, the storage or transport of the gaseous hydrogen in the vessels is, especially for large vessel volumes, challenging). The purpose of this review is to provide an updated overview of the recent results and studies focusing on the perovskite materials used for both solar cells and hydrogen storage applications. Particular attention is given to (i) the preparation and the achievable efficiency and stability of the perovskite solar cells and (ii) the structural, thermodynamic, and storage properties of perovskite hydrides and oxides. We show that the perovskite materials can not only reach the efficiency above current Si-based solar cells but also, due to good stability and reasonable price, can be preferable in the solid-state storage of hydrogen. Then, the future trends and directions in the research and application of perovskite in both solar cells and hydrogen storage are also highlighted. Full article

This research project envisions using a lunar observation platform to measure the full-wave (0.2~100 μm) and shortwave (0.2~4.3 μm) radiation of the Earth, achieving an accurate estimation of the overall radiation budget of the Earth. Based on the lunar platform, the system analyzes Earth’s radiation characteristics and geometric attributes, as well as the sampling properties of observation times. Informed by these analyses, an Earth-facing optical radiation measurement system tailored to these specifications is designed. The optical system adopts an off-axis three-mirror configuration with a secondary image plane, incorporating a field stop at the primary image plane to effectively suppress solar stray light, scattered lunar surface light, and background radiation from the instrument itself, ensuring the satisfactory signal-to-noise ratio, detection sensitivity, and observation duration of the instrument. At the same time, stringent requirements are imposed for the surface treatments of instrument components and temperature control accuracy to further ensure accuracy. Simulation analyses confirm that the design satisfies requirements, achieving a measurement accuracy of better than 1% across the entire optical system. This Moon-based Earth-radiation measurement system, with capabilities for Earth-pointing tracking, radiation energy detection, and stray-light suppression, furnishes a more comprehensive dataset, helping to advance our understanding of the mechanisms driving global climate change Full article

The Inconel 718 superalloy, a precipitation-hardenable material, is of particular interest for applications involving components operating under extreme conditions due to its excellent mechanical properties, high corrosion resistance at temperatures up to 700 °C, and good workability. At high temperatures, thermal transfer processes are crucial for temperature distribution across the component’s section, structural transformations, and variations in the alloy’s properties. The history of accidental overheating events is critical for the microstructure and properties of the alloy. Studies on thermal transfer in the Inconel 718 alloy available in the literature typically focus on the alloy in its as-delivered state. The experimental research presented in this paper examines the influence of repeated overheating history on the thermal diffusivity of the alloy. Full article

This research aims to optimize the solar–hydrogen energy system at Kangwon National University’s Samcheok campus by leveraging the integration of artificial intelligence (AI), the Internet of Things (IoT), and machine learning. The primary objective is to enhance the efficiency and reliability of the renewable energy system through predictive modeling and advanced fault detection techniques. Key elements of the methodology include data collection from solar energy production and fault detection systems, energy potential analysis using Transformer models, and fault identification in solar panels using CNN and ResNet-50 architectures. The Transformer model was evaluated using metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and an additional variation of MAE (MAE2). Known for its ability to detect intricate time series patterns, the Transformer model exhibited solid predictive performance, with the MAE and MAE2 results reflecting consistent average errors, while the MSE pointed to areas with larger deviations requiring improvement. In fault detection, the ResNet-50 model outperformed VGG-16, achieving 85% accuracy and a 42% loss, as opposed to VGG-16’s 80% accuracy and 78% loss. This indicates that ResNet-50 is more adept at detecting and classifying complex faults in solar panels, although further refinement is needed to reduce error rates. This study demonstrates the potential for AI and IoT integration in renewable energy systems, particularly within academic institutions, to improve energy management and system reliability. Results suggest that the ResNet-50 model enhances fault detection accuracy, while the Transformer model provides valuable insights for strategic energy output forecasting. Future research could focus on incorporating real-time environmental data to improve prediction accuracy and developing automated AIoT-based monitoring systems to reduce the need for human intervention. This study provides critical insights into advancing the efficiency and sustainability of solar–hydrogen systems, supporting the growth of AI-driven renewable energy solutions in university settings. Full article

This study investigates three methods for sizing behind-the-meter (BTM) solar PV systems for pumped water distribution networks (WDNs). The three methods are (1) the industry method based on current industry practices, (2) the minimum total life cycle cost (TLCC) method to minimize TLCC through the life of solar PV systems, and (3) the minimum payback method to minimize the time to pay off the capital investment in solar PV systems. The industry method risks over-sizing, while the minimum payback method risks under-sizing. The minimum TLCC method leads to systems with balanced performance. The findings offer decision-makers insights when selecting solar PV systems for WDNs. Full article

In the process of wireless energy transmission from a Space Solar Power Station (SSPS) to a satellite, the efficiency of energy transmission is closely related to the accuracy of beam control. The existing methods commonly ignore the impact of array position, structural deviation of the transmitting antenna, and modulation errors, which leads to the deviation error in actual energy transmission beams and the reduction of energy transmission efficiency. This paper innovatively proposes a high-precision bi-directional beam-pointing measurement method, which provides a technical basis for advancing the beam-pointing control accuracy from the perspective of improving the beam-pointing measurement accuracy. The method consists of (1) the interferometer goniometry method to realize high-precision guiding beam pointing measurement; and (2) the power field reconstruction method to realize offset angle measurement of the energy-transmitting beam. Simulation results demonstrate that under dynamic conditions, the guiding beam-pointing measurement accuracy of this method reaches 0.05°, which is better than the traditional 0.1° measurement accuracy based on the guiding beam. The measurement accuracy of the offset distance of the energy center is better than 0.11 m, and the measurement accuracy of the offset angle is better than 0.012°. Full article

This research investigates the use of municipal solid waste cremated fly ash as a viable substitute for natural sand in building methodologies, with a focus on sustainability. The waste material is used in the manufacturing of concrete roof tiles that are combined with solar PV systems, providing advantages in terms of both thermal comfort and improved energy efficiency. These tiles exhibit thermal insulation prowess by effectively preserving a 2-degree temperature differential and collecting heat from solar panels to enhance their energy-production efficiency. In order to enhance performance even further, aluminium foil is strategically placed on all four sides of the roof walls. The foil acts as a reflector, redirecting solar energy towards the tiles, which leads to a 5% boost in power generation. Particular alignments, such as positioning in an east-west or north-south direction, result in further enhancements in performance of 4% and 3%, respectively. This comprehensive approach not only confirms the use of waste materials for environmentally friendly construction but also emphasizes their crucial role in promoting energy-efficient building methods. Full article

This article presents the evaluation of the performance of the distance relay (ANSI function 21) when integrating Distributed Energy Resources (DERs) in a Local Distribution System (LDS). The aim is to understand the impacts of and the necessary modifications required in the operation of distance relays, considering different levels of DER aggregation, and identifying any threshold levels before issues arise. To achieve this, first, a comprehensive review was carried out to analyze the impacts generated in the protection systems. Second, by using the DigSilent Power Factory software, the implementation of the distance relay using a IEEE 13 Node Test Feeder was validated. The aggregation of the three fundamental types of DG, synchronous machines, solar panels, and wind turbines, was evaluated. The threshold at which distributed generation power injection begins to compromise distance protection performance was identified. This study compares the outcomes of using mho and quadrilateral protection schemes. Full article

The optimization of solar photovoltaic (PV) cells and modules is crucial for enhancing solar energy conversion efficiency, a significant barrier to the widespread adoption of solar energy. Accurate modeling and estimation of PV parameters are essential for the optimal design, control, and simulation of PV systems. Traditional optimization methods often suffer from limitations such as entrapment in local optima when addressing this complex problem. This study introduces the Material Generation Algorithm (MGA), inspired by the principles of material chemistry, to estimate PV parameters effectively. The MGA simulates the creation and stabilization of chemical compounds to explore and optimize the parameter space. The algorithm mimics the formation of ionic and covalent bonds to generate new candidate solutions and assesses their stability to ensure convergence to optimal parameters. The MGA is applied to estimate parameters for two different PV modules, RTC France and Kyocera KC200GT, considering their manufacturing technologies and solar cell models. The significant nature of the MGA in comparison to other algorithms is further demonstrated by experimental and statistical findings. A comparative analysis of the results indicates that the MGA outperforms the other optimization strategies that previous researchers have examined for parameter estimation of solar PV systems in terms of both effectiveness and robustness. Moreover, simulation results demonstrate that MGA enhances the electrical properties of PV systems by accurately identifying PV parameters under varying operating conditions of temperature and irradiance. In comparison to other reported methods, considering the Kyocera KC200GT module, the MGA consistently performs better in decreasing RMSE across a variety of weather situations; for SD and DD models, the percentage improvements vary from 8.07% to 90.29%. Full article

This article is devoted to increasing the efficiency of ecological solar panels with their combination with the house’s roof. A solar panel construction that combines both the solar collector and the building cover is considered. This work investigates the efficiency of solar panels depending on the type of coating, heat-carrying medium mass flow rate, tube diameter, and the distance between the tubes. Among the coatings, Grafplast PDA roofing material is the most effective. Prandelli/Tuborama tubes with a diameter of 16 mm are recommended. The diameter of the tubes significantly affects the efficiency of the solar panel only at low intensity of solar radiation. Full article

Along with the rapid development of society, freshwater shortages have become a global concern. Although existing desalination technologies have alleviated this pressure to some extent, their long-term environmental impact and energy consumption are still questionable. Therefore, it is necessary to find a new effective way for seawater desalination with cleaner energy. Solar-driven interfacial water evaporation technology has the advantages of environmental protection, energy saving, high evaporation efficiency, low cost, and strong sustainability, and is considered one of the most effective technologies to relieve water resource stress. This review summarized the recent advances in carbon-based interfacial photothermal converters focused on the preparation methods of 2D and 3D photothermal absorbers, the potential ways to enhance the efficiency of photothermal conversion. Finally, this paper proposed the challenges and future trends of interfacial photothermal converters. Full article

Facility agriculture, which involves agricultural production in controlled environments such as greenhouses, indoor farms, and vertical farms, aims to maximize efficiency, yield, and quality while minimizing resource consumption and environmental impact. Energy-saving technologies are essential to the green and low-carbon development of facility agriculture. Recently, phase change heat storage (PCHS) systems using phase change materials (PCMs) have gained significant attention due to their high thermal storage density and excellent thermal regulation performance. These systems are particularly promising for applications in facility agriculture and related buildings, such as solar thermal utilization, greenhouse walls, and soil insulation. However, the low thermal conductivity of PCMs presents a challenge for applications requiring rapid heat transfer. This study aims to provide a comprehensive review of the types, thermophysical properties, and various forms of PCMs, including macro-encapsulated PCMs, shape-stabilized PCMs, and phase change capsules (PCCs), as well as their preparation methods. The research methodology involves an in-depth analysis of these PCMs and their applications in active and passive PCHS systems within facility agriculture and related buildings. The major conclusion of this study highlights the critical role of PCMs in advancing energy-saving technologies in facility agriculture. By enhancing PCM performance, optimizing latent heat storage systems, and integrating intelligent environmental control, this work provides essential guidelines for designing more efficient and sustainable agricultural structures. The article will serve as the fundamental guideline to design more robust structures for facility agriculture and related buildings. Full article

This paper deals with the problem of determining the optimal capacity of concentrated solar power (CSP) plants, especially in the context of hybrid solar power plants. This work presents an innovative analytical approach to optimizing the capacity of concentrated solar plants. The proposed method is based on the use of additional non-dimensional parameters, in particular, the design factor and the solar multiple factor. This paper presents a mathematical optimization model that focuses on the capacity of concentrated solar power plants where thermal storage plays a key role in the energy source. The analytical approach provides a more complete understanding of the design process for hybrid power plants. In addition, the use of additional factors and the combination of the proposed method with existing numerical methods allows for more refined optimization, which allows for the more accurate selection of the capacity for specific geographical conditions. Importantly, the proposed method significantly increases the speed of computation compared to that of traditional numerical methods. Finally, the authors present the results of the analysis of the proposed system of equations for calculating the levelized cost of electricity (LCOE) for hybrid solar power plants. The nonlinearity of the LCOE on the main calculation parameters is shown. Full article