Fast spatially-resolved electrical modelling and quantitative characterisation of photovoltaic devices

An efficient and flexible modelling and simulation toolset for solving spatially-resolved models of photovoltaic (PV) devices is developed, and its application towards a quantitative description of localised electrical behaviour is given. A method for the extraction of local electrical device parameters is developed as a complementary approach to the conventional characterisation techniques based on lumped models to meet the emerging demands of quantitative spatially-resolved characterisation in the PV community. It allows better understanding of the effects of inhomogeneities on performance of PV devices. The simulation tool is named PV-Oriented Nodal Analysis (PVONA). This is achieved by integrating a specifically designed sparse data structure and a graphics processing unit (GPU)-based parallel conjugate gradient algorithm into a PV-oriented numerical solver. It allows more efficient high-resolution spatially-resolved modelling and simulations of PV devices than conventional approaches based on SPICE (Simulation Program with Integrated Circuit Emphasis) tools in terms of computation time and memory usage. In tests, mega-sub-cell level test cases failed in the latest LTSpice version (v4.22) and a PSpice version (v16.6) on desktop PCs with mainstream hardware due to a memory shortage. PVONA efficiently managed to solve the models. Moreover, it required up to only 5% of the time comparing the two SPICE counterparts. This allows the investigation of inhomogeneities and fault mechanisms in PV devices with high resolution on common computing platforms. The PVONA-based spatially-resolved modelling and simulation is used in various purposes. As an example, it is utilised to evaluate the impacts of nonuniform illumination profiles in a concentrator PV unit. A joint optical and electrical modelling framework is presented. Simulation results suggest that uncertainties introduced during the manufacturing and assembly of the optical components can significantly affect the performance of the system in terms of local voltage and current distribution and global current-voltage characteristics. Significant series resistance and shunt resistance effects are found to be caused by non-uniformity irradiance profiles and design parameters of PV cells. The potential of utilising PVONA as a quality assessment tool for system design is discussed. To achieve quantitative characterisation, the PVONA toolset is then used for developing a 2-D iterative method for the extraction of local electrical parameters of spatially-resolved models of thin-film devices. The method employs PVONA to implement 2-D fitting to reproduce the lateral variations in electroluminescence (EL) images, and to match the dark current-voltage characteristic simultaneously to compensate the calibration factor in EL characterisations. It managed to separate the lateral resistance from the overall series resistance effects. The method is verified by simulations. Experimental results show that pixellation of EL images can be achieved. Effects of local shunts are accurately reproduced by a fitting algorithm. The outcomes of this thesis provide valuable tools that can be used as a complementary means of performance evaluation of PV devices. After proper optimisation, these tools can be used to assist various analysis tasks during the whole lifecycle of PV products

Imaging of TCO lateral resistance effects in thin-film PV modules by lock-in thermography and electroluminescence techniques

The lateral sheet resistance of transparent conductive oxide (TCO) electrode in thin-film photovoltaic (PV) modules is a major component of series resistance losses that causes significant reduction in the fill-factor and output power. This paper presents the investigation of TCO lateral resistance effects in the encapsulated thin-film modules by lock-in thermography (LIT) technique, which is predominantly used for shunt investigation in the solar cells. The LIT technique has been employed under both dark and illuminated conditions to compare their spatial sensitivity for imaging TCO resistance effects in a module. The LIT images have also been compared with electroluminescence (EL) images to find a correlation between localized heating and voltage drop across distributed TCO layer resistances, and to determine their advantages and limitations. Experimental results show that both, DLIT and ILIT, exhibit a gradient in thermal signal along the cell width due to variation in power dissipation across the lateral resistance of TCO electrode. However, ILIT appears to be more sensitive for imaging TCO resistance losses due to less junction masking effect. The spatial sensitivity also depends on the width of cell in a module. For narrower cells, DLIT and EL techniques are observed to be more sensitive near the higher potential edge of a cell as compared to ILIT. The study concludes that the LIT technique is also a potential candidate for providing the spatially-resolved characterization of TCO resistive losses in thin-film modules

Cross-characterization for imaging parasitic resistive losses in thin-film photovoltaic modules

Thin-film photovoltaic (PV) modules often suffer from a variety of parasitic resistive losses in transparent conductive oxide (TCO) and absorber layers that significantly affect the module electrical performance. This paper presents the holistic investigation of resistive effects due to TCO lateral sheet resistance and shunts in amorphous-silicon (a-Si) thin-film PV modules by simultaneous use of three different imaging techniques, electroluminescence (EL), lock-in thermography (LIT) and light beam induced current (LBIC), under different operating conditions. Results from individual techniques have been compared and analyzed for particular type of loss channel, and combination of these techniques has been used to obtain more detailed information for the identification and classification of these loss channels. EL and LIT techniques imaged the TCO lateral resistive effects with different spatial sensitivity across the cell width. For quantification purpose, a distributed diode modeling and simulation approach has been exploited to estimate TCO sheet resistance from EL intensity pattern and effect of cell width on module efficiency. For shunt investigation, LIT provided better localization of severe shunts, while EL and LBIC given good localization of weak shunts formed by the scratches. The impact of shunts on the photocurrent generation capability of individual cells has been assessed by li-LBIC technique. Results show that the cross-characterization by different imaging techniques provides additional information, which aids in identifying the nature and severity of loss channels with more certainty, along with their relative advantages and limitations in particular cases

Fast current mapping of photovoltaic devices using compressive sampling

Light Beam Induced Current (LBIC) measurements are a useful tool in photovoltaic (PV) device characterisation for accessing the local electrical properties of PV devices. The main disadvantage of a typical LBIC system is measurement time, as a raster scan of a typical silicon solar cell can last several hours. The focus of this paper is the reduction of LBIC measurement time by means of compressed sensing (CS). The CS-LBIC system described in this paper can theoretically reduce measurement time to less than 25% of that required for a standard LBIC raster scan. Measurement simulations of a CS-LBIC system are presented as well as a practical demonstration using a digital micro-mirror array, which further reduces the measurement time by an order of magnitude. Instead of a raster scan, the PV device under measurement is sampled by a series of patterns and the current map is reconstructed using an optimization algorithm. Simulations of CS-LBIC measurements using the 2D spatially-resolved PV-Oriented Nodal Analysis (PVONA) model developed at CREST are used as a tool to explore the capabilities and verify the accuracy of this measurement technique as well as its ability to detect specific defects, such as cracks and shunts. Simulation results confirm that the CS sampling theory can be applied as an effective method for significantly reducing measurement time of current mapping of PV devices. An initial CS-LBIC system prototype has been built at the National Physical Laboratory (NPL) and measurements of small area devices (1cm x 0.8cm) using this system are given. The current maps are created using a Digital Micromirror Device (DMD) kit as a pattern generator. The response time of the micro mirror array is less than 20μs. This is another factor in the reduction of measurement time, as the movement time of an x-y translation stage is considerably slower. Initial measurement results show that current maps of PV cells can be acquired with 75% fewer measurements which, combined with the fast response of the pattern generator, can reduce LBIC measurement time by an order of magnitude

Synthesis of Hierarchical Hollow MnO₂ Microspheres and Potential Application in Abatement of VOCs

Hierarchical hollow MnO₂ microspheres have been synthesized by a facile hydrothermal method based on the decomposition of KMnO₄ precursor in nitric acid solution in the presence of Ce³⁺ ions. The hierarchical hollow microspheres consisted of discuslike nanoplatelets and nanorods. The Brunauer–Emmet–Teller (BET) specific surface area and the pore volume of the hierarchical hollow microspheres are 29.2 m² g^–1 and 0.30 cm³ g^–1, respectively. A possible formation mechanism of hierarchical hollow microspheres is proposed. Ce³⁺ ions play a crucial role in controlling the morphology and crystalline structure of MnO₂. The concentration of Ce³⁺ ions is a key factor for the formation of the hierarchical hollow microspheres. The as-prepared hierarchical hollow MnO₂ microspheres exhibit high catalytic ability for the oxidation of benzene

Primers for real-time PCR (rat).

Notch pathway has played a significant role in the pathophysiology of pulmonary hypertension (PH). However, the role of Jagged 2 (Jag2), one ligand of Notch, remains to be elucidated.Therefore, determining the contribution of Jag2 to PH and its impact on pulmonary artery smooth muscle cells (PASMCs) was the aim of this investigation. Adeno-associated virus-mediated Jag2 inhibition was used to explore the role of Jag2 in peripheral pulmonary vascular remodeling assessed in a rat model of chronic hypoxia (10% O2, 4 weeks) induced pulmonary hypertension. In vitro, the effect of Jag2 silencing on hypoxia (1% O2, 24h) induced rat PASMCs was determined. Group differences were assessed using a 2-sided unpaired Student’s t-test for two groups and one-way ANOVA for multiple groups. Jag2 upregulation was first confirmed in rats with sustained hypoxia-induced PH using publicly available gene expression data, experimental PH rat models and hypoxia induced rat PASMCs. Jag2 deficiency decreased oxidative stress injury, peripheral pulmonary vascular remodeling (0.276±0.020 vs. 0.451±0.033 μm, PPJag2 knockdown decreased proliferation (1.227±0.051 vs. 1.45±0.07, P = 0.012), increased apoptosis (16.733%±0.724% vs. 6.56%±0.668%, P</div

Jag2 expression is upregulated in hypoxia-treated rats and PASMCs.

(A) Visualization of Jag2 expression in the GSE85618 dataset. (B) Jag2 mRNA and protein (C) expression by qRT-PCR, immunohistochemistry, and western blotting in lung tissue of normal and hypoxia-treated rats. N = 6 rats per group. (D) Immunofluorescence double staining of α-SMA and Jag2 in lung tissues of normal and hypoxia-treated rats. Scale bar, 10 μm. (E) Jag2 mRNA and protein expression by qRT-PCR, immunofluorescence (F), and western blotting (G) in normal and hypoxia-treated PASMCs. Each group N = 3, and three biological replicates per group for cellular experiments. Scale bar, 25 μm. Data shown are mean ± SD; ***P < 0.001.</p

Heat map and volcano plot of the GSE85618 dataset.

(A) A visual representation in the form of a heat map to highlight the top 40 genes that show significant differences in expression levels within the GSE85618 dataset. Each column in the heat map corresponds to a particular sample, while each row represents the expression level of a specific gene. (B) volcano plot of the GSE85618 dataset showing the fold change (x-axis) differentially expressed genes. (TIF)</p

Hypoxia induces high intracellular Jag2 expression.

And Jag2 activates intracellular intracellular structural domain, ICD transferred to the nucleus to regulate the expression of mitochondria-related gene Sirt1 through the Notch receptor recognition. It causes mitochondrial dysfunction and resistance to proliferation and apoptosis of PASMCs, which in turn promotes the occurrence and development of pulmonary hypertension. (TIF)</p

Inhibition of Jag2 effectively ameliorates hypoxia-induced PH in rats.

(A) Fluorescence microscopy images of lung tissue four weeks after intratracheal AAV.1Jag2 instillation, where green fluorescence represents the expression and localization of AAV1 in lung tissue. DAPI stains the nuclei blue. Scale bar=10μm. (B) Representative immunoblot images and quantitative analysis of Jag2 protein expression in the control and AAV1.Jag2 groups. (C) Waveform diagram and quantitative analysis of RVSP (mmHg) in the indicated groups. (D) Representativemicroscopic images of distal pulmonary vascular stained with H&E, immunostained for α-SMA, and Masson trichrome in control, HPH, and HPH+Jag2i rats. Scale bar=10μm. (E) Fulton index RV/(LV+S) in the three groups. (F) The relative medial thickness expressed as a ratio of (total vascular area ‐ lumen area) to total vascular area (media/CSA). N=6 rats per group. Data shown are mean ± SD; **P < 0.01, ***P < 0.001.</p