Search Results (1,561)

The motivation for increasing the efficiency of renewable energy sources is the basic problem of ongoing research. Currently, intensive research is underway in technology based on the use of dye-sensitized solar cells (DSSCs). The aim of this work is to investigate the effect of modifying the iodide electrolyte with liquid crystals (LCs) known for the self-organization of molecules into specific mesophases. The current–voltage (I-V) and power–voltage (P-V) characteristics were determined for the ruthenium-based dyes N3, Z907, and N719 to investigate the influence of their structure and concentration on the efficiency of DSSCs. The addition of a nematic LC of 4-n-pentyl-4-cyanobiphenyl (5CB) to the iodide electrolyte influences the I-V and P-V characteristics. A modification of the I-V characteristics was found, especially a change in the values of short circuit current (I_SC) and open circuit voltage (V_OC). The conversion efficiency for cells with modified electrolyte shows a complex dependence that first increases and then decreases with increasing LC concentration. It may be caused by the orientational interaction of LC molecules with the titanium dioxide (TiO₂) layer on the photoanode. A too high concentration of LC may lead to a reduction in total ionic conductivity due to the insulating effect of the elongated polar molecules. Full article

Surface defects of photovoltaic (PV) cells can seriously affect power generation efficiency. Accurately detecting such defects and handling them in a timely manner can effectively improve power generation efficiency. Aiming at the high-precision and real-time requirements for surface defect detection during the use of PV cells, this paper proposes a PV cell surface defect detection algorithm based on SEC-YOLOv8. The algorithm first replaces the Spatial Pyramid Pooling Fast module with the SPPELAN pooling module to reduce channel calculations between convolutions. Second, an ECA attention mechanism is added to enable the model to pay more attention to feature extraction in defect areas and avoid target detection interference from complex environments. Finally, the upsampling operator CARAFE is introduced in the Neck part to solve the problem of scale mismatch and enhance detection performance. Experimental results show that the improved model achieves a mean average precision (mAP@0.5) of 69.2% on the PV cell dataset, which is 2.6% higher than the original network, which is designed to achieve a superior balance between the competing demands of accuracy and computational efficiency for PV defect detection. Full article

Bird-dropping fouling and hotspot anomalies remain the most prevalent and detrimental defects in utility-scale photovoltaic (PV) plants; their co-occurrence on a single module markedly curbs energy yield and accelerates irreversible cell degradation. However, markedly disparate visual–thermal signatures of the two phenomena impede high-fidelity concurrent detection in existing robotic inspection systems, while stringent onboard compute budgets also preclude the adoption of bulky detectors. To resolve this accuracy–efficiency trade-off for dual-defect detection, we present YOLOv8-SG, a lightweight yet powerful framework engineered for mobile PV inspectors. First, a rigorously curated multi-modal dataset—RGB for stains and long-wave infrared for hotspots—is assembled to enforce robust cross-domain representation learning. Second, the HSV color space is leveraged to disentangle chromatic and luminance cues, thereby stabilizing appearance variations across sensors. Third, a single-head self-attention (SHSA) block is embedded in the backbone to harvest long-range dependencies at negligible parameter cost, while a global context (GC) module is grafted onto the detection head to amplify fine-grained semantic cues. Finally, an auxiliary bounding box refinement term is appended to the loss to hasten convergence and tighten localization. Extensive field experiments demonstrate that YOLOv8-SG attains 86.8% mAP@0.5, surpassing the vanilla YOLOv8 by 2.7 pp while trimming 12.6% of parameters (18.8 MB). Grad-CAM saliency maps corroborate that the model’s attention consistently coincides with defect regions, underscoring its interpretability. The proposed method, therefore, furnishes PV operators with a practical low-latency solution for concurrent bird-dropping and hotspot surveillance. Full article

This study presents preliminary findings from an experimental campaign conducted on a pilot-scale green hydrogen production plant powered by a photovoltaic (PV) system. The integrated setup, implemented at the University “Mediterranea” of Reggio Calabria, includes renewable energy generation, hydrogen production via electrolysis, on-site storage, and reconversion through fuel cells. The investigation assessed system performance under different configurations (on-grid and selective stand-alone modes), focusing on key operational phases such as inerting, purging, pressurization, hydrogen generation, and depressurization. Results indicate a strong linear correlation between the electrolyser’s power setpoint and the pressure rise rate, with a maximum gradient of 0.236 bar/min observed at 75% power input. The system demonstrated robust and stable operation, efficient control of shutdown sequences, and effective integration with PV input. These outcomes support the technical feasibility of small-scale hydrogen systems driven by renewables and offer valuable reference data for calibration models and future optimization strategies. Full article

In this paper, a robust optimized controller is implemented in the photovoltaic generator system (PVGS). The PVGS is composed of individual photovoltaic (PV) cells, which convert solar energy to electrical energy. To optimize the efficiency of the PVGS under variable solar irradiance and temperatures, a maximum power point tracking (MPPT) controller is necessary. Additionally, the PVGS output voltage is typically low for many applications. To achieve the MPPT and to gain the output voltage, an increasing boost converter (IBC) is employed. Then, two issues should be considered in MPPT. At first, a smooth control signal for adjusting the duty cycle of the IBC is important. Another critical issue is the PVGS and IBC unknown sections, i.e., the total system uncertainty. Therefore, to address the system uncertainties and to regulate the smooth duty cycle of the converter, a robust dynamic sliding mode control (DSMC) is proposed. In DSMC, a low-pass integrator is placed before the system to suppress chattering and to produce a smooth actuator signal. However, this integrator increases the system states, and hence, a sliding mode observer (SMO) is proposed to estimate this additional state. The stability of the proposed control scheme is demonstrated using the Lyapunov theory. Finally, to demonstrate the effectiveness of the proposed method and provide a reliable comparison, conventional sliding mode control (CSMC) with the same proposed SMO is also implemented. Full article

Improving photovoltaic (PV) panel performance under extreme climatic conditions is critical for advancing sustainable energy systems. In hyper-arid regions, elevated operating temperatures significantly reduce panel efficiency. This study investigates and compares three cooling techniques—air cooling, water cooling, and porous media cooling—using thermal and electrical modeling based on CFD simulations in ANSYS. The numerical model replicates a PV system operating under peak solar irradiance (900 W/m²) and realistic ambient conditions in Adrar, Algeria. Simulation results show that air cooling leads to a modest temperature reduction of 6 °C and a marginal efficiency gain of 0.25%. Water cooling, employing a top-down laminar flow, reduces cell temperature by over 35 °C and improves net electrical output by 30.9%, despite pump energy consumption. Porous media cooling, leveraging passive evaporation through gravel, decreases panel temperature by around 30 °C and achieves a net output gain of 26.3%. Mesh sensitivity and validation against experimental data support the accuracy of the model. These findings highlight the significant potential of water and porous material cooling strategies to enhance PV performance in hyper-arid environments. The study also demonstrates that porous media can deliver high thermal effectiveness with minimal energy input, making it a suitable low-cost option for off-grid applications. Future work will integrate long-term climate data, real diffuser geometries, and experimental validation to further refine these models. Full article

High-voltage unipolar square wave pulsed electric fields (PEFs) can cause cell membrane rupture and cell death during a process termed irreversible electroporation (IRE). PEF effects are influenced by pulse parameters like number of pulses (NP), voltage (PV), width (PW), and interval (PI). This study systematically evaluates their effects on the conductivity and relative conductivity changes between untreated and PEF-treated regions of potato tissue across a frequency range of 1 Hz to 5 MHz by means of electrochemical impedance spectroscopy (EIS), using a custom-made four-point EIS probe with RG58/U coaxial cables. Potatoes were chosen as a plant-based PEF model to reduce animal experiments and untreated tissue showed minimal conductivity variation across regions. Relative conductivity changes were maximal at 1000 Hz. At 1000 Hz, significant conductivity differences between untreated and PEF-treated regions were observed from PV = 200 V, NP = 10, PW = 10 µs, and PI = 50 ms onwards (most significant changes occurred for PV = 700 V; NP = 70; PW = 70 µs; PI = 250 ms and 500 ms). Our results may be beneficial for multiphysics modelling of IRE with specific electrical properties, conductivity mapping with optimal contrast—such as in electrical impedance tomography—and development of IRE procedures. Full article

Fanconi anemia (FA) is a DNA repair deficiency disorder associated with genomic and chromosomal instability and a high cancer risk. In a small percentage of cases, FA is caused by biallelic pathogenic variants (PVs) in the BRCA2/FANCD1 gene, defining the FA-D1 subtype. Experimental and epidemiologic data indicate that the complete absence of BRCA2 is incompatible with viability. Therefore, cells from individuals affected with FA caused by biallelic BRCA2 PVs must have a residual BRCA2 function. This activity may be maintained through hypomorphic missense mutations, translation termination–reinitiation associated with a translational stop mutation, or other non-canonical or uncommon translation initiation and elongation events. In some cases, however, residual BRCA2 function is provided by alternatively or aberrantly spliced BRCA2 transcripts. Here, we review and debate aspects of the contribution of splicing in the 5′ segment to BRCA2 functions in the context of PVs affecting this largely intrinsically disordered protein region, with a focus on recent findings in individuals with FA-D1. In this Perspective, we also discuss some of the broader biological implications and open questions that arise from considering 5′-terminal BRCA2 splicing in light of old and new findings from FA-D1 patients and beyond. Full article

One of the methods for mitigating the duck curve phenomenon in photovoltaic (PV) energy systems is storing surplus energy in the form of hydrogen. However, there is a lack of studies focused on residential PV systems that assess the impact of hydrogen storage on the reduction of energy flow imbalance to and from the national grid. This study presents an analysis of hydrogen energy storage based on real-world data from a household PV installation. Using simulation methods grounded in actual electricity consumption and hourly PV production data, the research identified the storage requirements, including the required operating hours and the capacity of the hydrogen tank. The analysis was based on a 1 kW electrolyzer and a fuel cell, representing the smallest and most basic commercially available units, and included a sensitivity analysis. At the household level—represented by a single-family home with an annual energy consumption and PV production of approximately 4–5 MWh over a two-year period—hydrogen storage enabled the production of 49.8 kg and 44.6 kg of hydrogen in the first and second years, respectively. This corresponded to the use of 3303 kWh of PV-generated electricity and an increase in self-consumption from 30% to 64%. Hydrogen storage helped to smooth out peak energy flows from the PV system, decreasing the imbalance from 5.73 kWh to 4.42 kWh. However, while it greatly improves self-consumption, its capacity to mitigate power flow imbalance further is constrained; substantial improvements would necessitate a much larger electrolyzer proportional in size to the PV system’s output. Full article

Photovoltaic (PV) systems are key renewable energy sources due to their ease of implementation, scalability, and global solar availability. Enhancing their lifespan and performance is vital for wider adoption. Identifying degradation root causes is essential for improving PV design and maintenance, thus extending lifespan. This paper proposes a hybrid fault diagnosis method combining a bond graph-based PV cell model with empirical degradation models to simulate faults, and a deep learning approach for root-cause detection. The experimentally validated model simulates degradation effects on measurable variables (voltage, current, ambient, and cell temperatures). The resulting dataset trains an Optimized Feed-Forward Neural Network (OFFNN), achieving 75.43% accuracy in multi-class classification, which effectively identifies degradation processes. Full article

This study presents the design and techno-economic comparison of two standalone photovoltaic (PV) systems, each supplying a 1 kW critical load with 100% reliability under Cairo’s climatic conditions. These systems are modeled for both the constant and the night load scenarios, accounting for the worst-case weather conditions involving 3.5 consecutive cloudy days. The primary comparison focuses on traditional lead-acid battery storage versus green hydrogen storage via electrolysis, compression, and fuel cell reconversion. Both the configurations are simulated using a Python-based tool that calculates hourly energy balance, component sizing, and economic performance over a 21-year project lifetime. The results show that the PV/H₂ system significantly outperforms the PV/lead-acid battery system in both the cost and the reliability. For the constant load, the Levelized Cost of Electricity (LCOE) drops from 0.52 USD/kWh to 0.23 USD/kWh (a 56% reduction), and the payback period is shortened from 16 to 7 years. For the night load, the LCOE improves from 0.67 to 0.36 USD/kWh (a 46% reduction). A supplementary cost analysis using lithium-ion batteries was also conducted. While Li-ion improves the economics compared to lead-acid (LCOE of 0.41 USD/kWh for the constant load and 0.49 USD/kWh for the night load), this represents a 21% and a 27% reduction, respectively. However, the green hydrogen system remains the most cost-effective and scalable storage solution for achieving 100% reliability in critical off-grid applications. These findings highlight the potential of green hydrogen as a sustainable and economically viable energy storage pathway, capable of reducing energy costs while ensuring long-term resilience. Full article

Plant-beneficial microbes are a perennial ally in an agroecosystems, providing multiple benefits to crop plants. The present study explored the potential of two microbial biocontrol agents (MBCAs), viz., Trichoderma asperellum and Pseudomonas fluorescens, against the bacterial blight pathogen of rice, Xanthomonas oryzae pv. oryzae. In vitro, MBCAs resulted in significant inhibition of X. oryzae pv. oryzae, as evidenced through the distortion of pathogen cell morphology and formation of a pathogen biofilm. Pot studies on the effect of MBCAs in rice showed increased germination, increased vigor index of seedlings, increased tiller numbers, a 10.29% reduction in percentage disease incidence (PDI), and low disease severity following individual inoculation. Activity of plant defense enzymes also increased with MBCA treatment (phenylalanine ammonia-lyase, 2.7-fold increase; peroxidase and polyphenol oxidase, 5-fold increase), establishing the priming effect of MBCAs on host defense. The quantitative polymerase chain reaction data revealed that pathogenesis-related genes (OsPR1a, OsPR1b, and OsPR10a) and X. oryzae pv. oryzae resistance genes (Xa1 and Xa26) were upregulated 4- to 14-fold in MBCA-treated rice plants over control plants. These results provide insights into the phenological, physiological, and molecular responses of rice crops treated with MBCAs in the presence of X. oryzae pv. oryzae and could be used to develop an effective field management strategy. Full article

The immune response triggered when plant cell surface receptors recognize pathogen-associated molecular patterns (PAMPs) is known as PAMP-triggered immunity (PTI). Several studies have demonstrated that extracellular plant ferredoxin-like protein (PFLP) can enhance PTI signaling, thereby conferring resistance to bacterial diseases in various plants. The C-terminal casein kinase II (CK2) phosphorylation region of PFLP is essential for strengthening PTI. However, whether phosphorylation at this site directly enhances PTI signaling and consequently increases plant disease resistance remains unclear. To investigate this, site-directed mutagenesis was used to generate PFLPT90A, a non-phosphorylatable mutant, and PFLPT90D, a phospho-mimetic mutant, for functional analysis. Based on the experimental results, none of the recombinant proteins were able to enhance the hypersensitive response induced by the HrpN protein or increase resistance to the soft rot pathogen Pectobacterium carotovorum subsp. carotovorum ECC17. These findings suggest that phosphorylation at the T90 residue might be essential for PFLP-mediated enhancement of plant immune responses, implying that this post-translational modification is likely required for its disease resistance function in planta. To further explore the relationship between PFLP phosphorylation and endogenous CK2, the Arabidopsis insertion mutant cka2 and the complemented line CKA2R were analyzed under treatment with flg22_Pst from Pseudomonas syringae pv. tomato. The effects of PFLP on the hypersensitive response, rapid oxidative burst, callose deposition, and susceptibility to soft rot confirmed that CK2 is required for these immune responses. Furthermore, expression analysis of PTI-related genes FRK1 and WRKY22/29 in the mitogen-activated protein kinase (MAPK) signaling pathway demonstrated that CK2 is necessary for PFLP to enhance flg22_Pst-induced immune signaling. Taken together, these findings suggest that PFLP enhances A. thaliana resistance to bacterial soft rot primarily by promoting the MAPK signaling pathway triggered by PAMP recognition, with CK2-mediated phosphorylation being essential for its function. Full article

Due to the high demand for fuel efficiency, electric vehicles have come into the picture, as they only use batteries to power the vehicle. This requires constant charging of the batteries at charging stations, which are costly and impractical to install. But it is possible to install charging stations by making use of photovoltaic (PV) cells and demagnetization currents to self-charge batteries under stand-still conditions. The design of a bidirectional converter with asymmetrical half-bridge converter based on a switched reluctance motor (SRM) drive, using PV for electric vehicles, is implemented in this paper. It consists of developing a control unit (GCU), Li-ion battery pack, and photovoltaic (PV) solar cells that are integrated with a bidirectional converter and asymmetrical half-bridge converter (AHBC) to provide power to the SRM drive. The solar-assisted SRM drive can be operated in either the motoring mode or charging mode. In the motoring-mode GCU, the battery or PV energy can be used in any combination to power the SRM. In the charging-mode PV, the GCU and AC grids are used to charge the battery under stand-still conditions. This work helps in the self-charging of batteries using either the GCU or PV cells, as well as aids in the improvement in the performance characteristics. Also, this work compares the performance metrics for the proposed system and conventional system. The performance of the drive system using PV cells/GCU is evaluated and verified through MatLab/Simulink and experimental results. Full article

Concentrating photovoltaic-thermal (CPVT) collectors use reflective surfaces to focus sunlight onto a smaller receiver area, increasing thermal energy output while maintaining annual energy efficiency. Ray-tracing simulations are employed in this study using Tonatiuh to optimise the characteristics of the Double MaReCo (DM) collector, which is an improved version of the commercially available Solarus Power Collector (PC). Focused on enhancing electrical performance, the photovoltaic (PV) cell configurations are varied on the bottom side of the receiver, while the top-side PV cells remain constant. The study also analyses the influence of diodes and transparent gables on the annual solar irradiance received by the PV cells. From the analysis, it is observed that the specific annual irradiance received by the PV cells in the DM collector with transparent gables is nearly 64% more compared to that of the PC counterpart. It is also observed that the transparency of gables becomes significant only when the whole area of the receiver is covered by PV cells. With the goal of improving performance while lowering the cost and complexity of the DM collector, the study investigates various collector design characteristics that may shed more light on optimising the current model. Full article