Solar Energy最新文献

The single diode model is one of the most employed to represent the behavior of photovoltaic generators. Nonetheless, the transcendental nature of its characteristic equation requires that some mathematical approach be specifically adopted to allow the determination of its solution. In recent years, the approach via the Lambert W function has gained more and more popularity; however, the calculation of this special function still faces performance issues. That said, the present paper proposes a self-started predictor–corrector method for calculating the Lambert W function in the interval of interest of the single diode model. This method was properly designed to return high-quality solutions at a low and fixed computational cost. In this sense, the moderate complexity of its four equations stands out, as well as its non-conditional and non-iterative nature. The results obtained for appropriate case studies ascertain its elevated level of accuracy. Also, they demonstrate that it is more effective and faster than other state-of-the-art alternatives. Therefore, the paper’s major contribution is this novel method, which proves to be reliable, easy to implement, and useful for making the employment of the single diode model in studies more efficient.

Hole transport materials (HTMs) are pivotal components in perovskite solar cells (PSCs), significantly influencing their power conversion efficiency (PCE). This study explores the potential of various diacetylide-triphenylamine (DATPA) derivatives (HTMs 1–8) to function as hole transporters, employing density functional theory (DFT) and time-dependent density functional theory (TD-DFT) calculations.

The energy levels of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO), as well as the band gap, were computed using the B3LYP/6-311G(d) level of theory. The findings reveal that, with the exception of HTM 8, these compounds exhibit suitable HOMO and LUMO levels relative to the perovskite layer and possess a lower band gap energy compared to the commonly used spiro-OMeTAD.

Additionally, the calculation of hole mobility (Kh) using the Marcus method demonstrated a satisfactory value, substantiating the applicability of these compounds as HTMs. Further calculations of parameters such as hole reorganization energy (λh), absolute hardness (η), ionization potential (IP), electronic affinity (EA), solubility (ΔGsolv), and exciton binding energy (Eb) affirm that these compounds are promising candidates for hole transport in perovskite solar cells. Notably, the compound HTM 2 (NMe2-DATPA) outperforms the others in hole transfer efficiency.

The utilization of data-driven modeling techniques has been extensively employed in the simulation analysis, power prediction, and condition monitoring of photovoltaic power generation systems. However, the absence of interpretability regarding the intrinsic mechanisms in the modeling process has resulted in numerous constraints in practical implementation and subsequent promotion. To this end, we propose a novel digital twin modeling approach that eliminates the need for injecting additional signals or sensors, estimating unknown parameters in the mechanism model solely by using operational data from physical systems. A time synchronization filter was added to address the frequency mismatch between the actual sampling frequency and the solution step size. The results of numerical research indicate that the proposed digital twin model has the ability to accurately simulate the dynamic characteristics of photovoltaic grid connected inverters. The digital twin model of photovoltaic inverters has achieved good results in the cross experiment of device degradation trend monitoring, indicating that the proposed method is expected to make significant contributions to the simulation, power prediction, and degradation monitoring of grid connected photovoltaic systems.

Bifacial photovoltaics (BPVs) have received tremendous attention as a potential contender for efficient and cost-effective light energy harvesting. Recently, advancements in BPV technologies have broadened their scope, allowing them to harness artificial indoor light energy efficiently from both top and bottom sides. This innovative approach has demonstrated its effectiveness in energy harvesting through a single-cell design. Among various available PV technologies, thin-film perovskite photovoltaics (PPVs) exhibit exceptional promise for indoor applications in low-light environments. They offer high-power conversion efficiency and ease of design, making them a superior choice when compared to other emerging indoor PV technologies such as kesterite and dye-sensitized PVs. To improve the performance of the indoor BPVs, it is necessary to further review several characteristics relating to their materials, architecture, processing, and indoor characterizations. Additionally, a comprehensive understanding of charge-transfer mechanisms, the variability in indoor lighting sources, the development of standardized indoor simulators, assessment of materials toxicity, and considerations of scalability are essential elements that must be addressed to advance this technology. In summary, this review examines recent developments, emerging trends, challenges, and provide suggestions for the further advancement of i-BPVs, also highlighting their potential as reliable and sustainable indoor energy-harvesting solution.

This paper presents dynamic air-based models of a hybrid photovoltaic-thermal (PVT) collector. The models are developed with the aim of estimating the temperature of the collector components and therefore of estimating the annual generation of electrical energy and thermal energy outputs, by using actual climate data of six different cities based on Köppen-Geiger-Photovoltaic (KGPV) climate zones. The results show that the unglazed type collector has the best PV cooling while the dual channel collector has the best air heating among air-based PVT collectors. The results also indicate that the use of additional fluid enhances both electrical and thermal performance. The dynamic models are validated by comparison with results found in the literature. The paper also discusses a novel bi-fluid PVT system combined with a storage tank and an H-infinity based robust controller that can handle uncertainties. The results of the bi-fluid system show that the fraction of energy demand covered by the system is highly dependent on climate conditions and the collector’s surface area. It was found that for a small-scale house (standard for four people), the proposed system can cover more than 70% annual domestic hot water demand for cities with high solar irradiance and 32% for a city with low solar irradiance.

Rooftop solar micro-power plants mitigate pollution and transmission problems in crowded Indian cities. The Indian government is exploring alternate solutions, and the micro, small, and medium enterprises (MSME) sector is also coming forward to opt for sustainable solutions. This study is focused on the MSME segment in India, which constitutes approximately 63 million entities. Installing a solar system for which a rooftop could be the best place to tap solar energy from these entities is required. Checking the rooftop solar potential of any MSME entity requires a suitable technique to decide which sector to target first and the further order. A unique methodology based on multi-criteria decision-making (MCDM) methods is presented to rank 10 MSME alternatives with seven criteria. It includes the measurement of alternatives and ranking according to compromise solution (MARCOS) to rank MSME sectors in India with rooftop solar potential. Weights of importance are assigned with three objective techniques and combined with the Bonferroni operator. The ranks attained are compared with different MCDM methods, and sensitivity analysis is performed while changing weights. Kendall and Spearman rank correlation coefficients are utilized to access the correlation levels between various strategies. Finally, Garrett’s ranking technique is used to finalize the different ranks. The results reveal that the MARCOS method performed well, and “textiles” ranks first, followed by “auto and engineering products.” As a result, the leading industrial sectors will help improve energy utilization while concentrating on renewable energy resources.

This study aims to establish a foundation for estimating energy demand according to building types by proposing a method to establish a time-series energy data inventory solely based on energy consumption in countries where typical models or benchmarking data by building types have not been developed. First, we presented the characteristics of energy consumption patterns that can be defined from the energy consumption itself based on frequency characteristics. Then, we defined a method to normalize and classify types of daily energy consumption patterns using this method and validated it with measured data. Finally, based on the results, a generalized method for establishing building time series energy data inventory was proposed. This method has a simple procedure and its result can be interpreted intuitively. It does not require data to be converted into stationary time-series data, unlike statistical methods, and it can avoid data distortion due to building operational errors. Moreover, it is easy to find the reasons for the results because the processes are easy to understand, unlike artificial intelligence methods. This study proposes a method to establish a time-series building energy data inventory by classifying types based solely on energy consumption. Furthermore, it suggests the possibility of its application in the early stages of planning an energy-sharing community.

Thermal management and efficiency optimization are crucial for improving photovoltaic thermal (PVT) system performance. This study investigated both numerically and experimentally, the performance of a newly designed PVT module enhanced by integrating phase change material (PCM) with metal foam. The PVT module operating with Copper Foam Matrix (CFM) plus PCM as a heat sink was evaluated across various input operating parameters. The experimental results were used to validate a numerical model, enabling the prediction of thermal behavior and system efficiency under various conditions. The key parameters examined were PCM type and metal foam geometry along with their effects on heat transfer, operating temperature regulation, and combined electrical-thermal efficiency. The numerical optimization indicated that thermal conductivity and latent heat storage capacity of the PCM-CFM composite could be readily tuned to maximize collector efficiency for given ambient conditions. Comparative analyses reveal that the inclusion of a CFM alongside PCM significantly boosts the thermal efficiency, achieving up to 72.74% under optimal conditions, a notable improvement from PCM-only configurations. Additionally, this hybrid setup demonstrated a peak electrical efficiency increase to 10.74%, underscoring the synergy between thermal management and electrical performance enhancements. The study provides new insights into structure-performance relations in PVTs with direct policy implications for technology development and deployment. The combined experimental and modeling approach enables reliable PVT performance predictions for real-world operating constraints.

Solar thermal power generation has been widely employed as an effective method for efficiently harnessing solar energy, with solid heat-collecting particles serving as the medium for collecting and storing solar energy, thus holding significant developmental potential. However, challenges such as high thermal radiation losses and inadequate high-temperature stability have hindered the further advancement of solid heat-collecting particles. The present study addresses these challenges by utilizing solid waste fly ash to prepare solar-selective absorbing solid heat-collecting particles. Specifically, particles sintered at 1070℃ exhibit impressive characteristics, including an average solar absorptance of 93.26 % at room temperature, an emissivity in the mid-infrared range of 68.12 %, and a specific heat capacity of 0.82 J/(g·℃). Moreover, rigorous high-temperature stability tests demonstrate that these particles maintain a stable solar absorptance in the ultraviolet–visible-near-infrared range, consistently around 93.26 %. Additionally, the particles exhibit outstanding wear resistance and stability, further enhancing their suitability for practical applications. This research achieves the dual objectives of environmental sustainability and cost reduction by utilizing solid waste materials, while the preparation process remains simple, bolstering the feasibility of implementing these findings in real-world scenarios. In summary, this study effectively addresses the challenges of high thermal radiation losses and poor high-temperature stability in solid heat-collecting particles for solar thermal power generation.

Energy-efficient windows are being used to increase the thermal insulation of a façade. Such insulating windows contain an ultra-thin, multilayered, transparent silver coating that acts as an infrared mirror which significantly reduces thermal losses that occur through radiation from inside the building. These so-called low-emissivity coatings revolutionized the field of building insulation but also decreased solar heat gain coefficient which reduces the potential for energy savings during winter. Insulating windows in cold climates should achieve a selective behavior in the transmittance of EM waves. Ideally, solar energy should be transmitted and mid-infrared radiation reflected, thus reducing the heating needs in buildings. This scientific paper presents a numerical investigation based on finite-difference time-domain (FDTD) focused on the optical transmission characteristics of silver plasmonic square nanohole arrays and explores their potential application in insulating windows. It is found that a nanohole array with a periodicity of 350 nm and a linewidth of 50 nm gives outstanding properties and represents a good candidate to achieve high solar heat gain in low-e coatings. The findings contribute to the understanding of plasmonic effects in nanohole arrays and offer insights into the practical application of such structures in the development of advanced insulating windows with enhanced optical performance.