Distributed electrical network modelling approach for spatially resolved characterisation of photovoltaic modules

Distributed electrical modelling and simulation plays an important role in investigating local operating points and the overall power generation of photovoltaic (PV) modules. A PV module is a three-dimensional device in which inhomogeneities can cause a non-uniform performance and hence, electrical mismatches which consequently reduce the overall power generation. Distributed modelling and simulation can be used to identify local electrical properties and their impacts on the power output. In this study, a flexible, distributed electrical network modelling approach is presented. The proposed approach introduces a hierarchical architecture built up from the diode model-based sub-cell level to the module level. A PV-oriented nodal analysis solver is developed to enable the spatially resolved quantitative analysis of electrical operating points by given local properties including irradiance, temperature, series resistance, shunt resistance and ideality factor. The approach has been verified by PSpice software. The case studies have shown that this modelling and simulation tool can be used to analyse spatially resolved characterisation results and to predict global and distributed operating points under different conditions

Accelerated spatially resolved electrical simulation of photovoltaic devices using photovoltaic-oriented nodal analysis

This paper presents photovoltaic-oriented nodal analysis (PVONA), a general and flexible tool for efficient spatially resolved simulations for photovoltaic (PV) cells and modules. This approach overcomes the major problem of the conventional Simulation Program with Integrated Circuit Emphasis-based approaches for solving circuit network models, which is the limited number of nodes that can be simulated due to memory and computing time requirements. PVONA integrates a specifically designed sparse data structure and a graphics processing unit-based parallel conjugate gradient algorithm into a PV-oriented iterative Newton--Raphson solver. This first avoids the complicated and time-consuming netlist parsing, second saves memory space, and third accelerates the simulation procedure. In the tests, PVONA generated the local current and voltage maps of a model with 316 x 316 nodes with a thin-film PV cell in 15 s, i.e., using only 4.6% of the time required by the latest LTSpice package. The 2-D characterization is used as a case study and the potential application of PVONA toward quantitative analysis of electroluminescence are discussed

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

miR-210-3p promotes obesity-induced adipose tissue inflammation and insulin resistance by targeting SOCS1 mediated NF-κB pathway

Under the condition of chronic obesity, an increased level of free fatty acids along with low oxygen tension in the adipose tissue creates a pathophysiological adipose tissue microenvironment (ATenv) leading to the impairment of adipocyte function and insulin resistance. Here, we found the synergistic effect of hypoxia and lipid (HL) surge in fostering adipose tissue macrophages(ATMs) inflammation and its polarization. ATenv significantly increased miR-210-3p expression in ATMs which promotes NF-kB activation-dependent proinflammatory cytokines expressions along with the downregulation of anti-inflammatory cytokines expression. Interestingly, delivery of miR-210-3p mimic significantly increased the macrophage inflammation in absence of HL co-stimulation; while miR-210-3p inhibitor notably compromised HL-induced macrophage inflammation through increased production of SOCS1 (suppressor of cytokine signalling 1), a negative regulator of NF-kB inflammatory signalling pathway. Mechanistically, miR-210 directly binds to 3′ UTR of SOCS1 mRNA and silenced its expression and thus preventing proteasomal degradation of NF-kB p65. Direct delivery of anti-miR-210-3p LNA in the ATenv markedly rescued mice from obesity-induced adipose tissue inflammation and insulin resistance. Thus, miR-210-3p inhibition in ATMs could serve as a novel therapeutic strategy for managing obesity-induced type 2 diabetes.</p