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Abstract Recently a simple explicit model was introduced to represent the J–V characteristics of an illuminated solar cell with parasitic resistances and bias dependent photocurrent as j = (1 − vm)/(1 + αv), here the normalized voltage, v and normalized current density j can be represented as v = V/Voc and j = J/Jsc respectively, where Voc is the open circuit voltage and Jsc is the short circuit current density. The model is an equivalent rational function form and useful for design, characterization and calculation of maximum power point voltage. The model is intuitive and lacks the analytical support. In this paper an analytical derivation of the model is presented using the physics based implicit J–V equation.

Abstract Recently a simple explicit model was introduced to represent the J–V characteristics of an illuminated solar cell with parasitic resistances and bias dependent photocurrent as j = (1 − vm)/(1 + αv), here the normalized voltage, v and normalized current density j can be represented as v = V/Voc and j = J/Jsc respectively, where Voc is the open circuit voltage and Jsc is the short circuit current density. The model is an equivalent rational function form and useful for design, characterization and calculation of maximum power point voltage. The model is intuitive and lacks the analytical support. In this paper an analytical derivation of the model is presented using the physics based implicit J–V equation.

Abstract The usage of Remotely Piloted Aircraft (RPA) for infrared (IR) imaging of PV systems for health status monitoring of PV modules has been identified as a cost-effective approach which offers 10–15 fold lower inspection times than conventional techniques. It provides easy access to PV systems irrespective of plant capacity and location of installation and is capable of performing a rapid analysis of the system. Reliable IR image is important for accurate assessment to detect and locate defects and defective modules effectively and analyze the impact on power generation. This paper describes the importance of RPA based IR imaging for identifying solar PV systems defects. It also addresses the opportunities that can be achieved through the adoption of RPA based IR imaging technology which can add value to social, economic and environmental performance of the PV systems.

Abstract The usage of Remotely Piloted Aircraft (RPA) for infrared (IR) imaging of PV systems for health status monitoring of PV modules has been identified as a cost-effective approach which offers 10–15 fold lower inspection times than conventional techniques. It provides easy access to PV systems irrespective of plant capacity and location of installation and is capable of performing a rapid analysis of the system. Reliable IR image is important for accurate assessment to detect and locate defects and defective modules effectively and analyze the impact on power generation. This paper describes the importance of RPA based IR imaging for identifying solar PV systems defects. It also addresses the opportunities that can be achieved through the adoption of RPA based IR imaging technology which can add value to social, economic and environmental performance of the PV systems.

Abstract Quantum efficiency and impedance spectroscopy tools are employed for understanding the influence of parasitic absorption losses and partial field effect surface passivation by the silver nanoparticles (Ag NPs) on electrical properties of textured silicon solar cells without and with Si3N4 spacer layer. The parasitic absorption losses from Ag NPs reduced the internal quantum efficiency near the surface plasmon resonance region. The passive components like; series and parallel resistances, chemical capacitance of solar cells without and with Ag NPs are estimated after fitting impedance semicircles, which are further used for estimating effective carrier lifetime (τeff) values. Under AM1.5G illumination, cells with Si3N4 spacer layer showed a large decrease in the τeff due to the strong parasitic absorption losses from the Ag NPs. But, the cells without Si3N4 spacer layer showed a small decrease in the τeff due to the reduced surface recombination after partial field effect passivation from near-fields of Ag NPs’ surface plasmon resonances on the emitter surface.

Abstract Quantum efficiency and impedance spectroscopy tools are employed for understanding the influence of parasitic absorption losses and partial field effect surface passivation by the silver nanoparticles (Ag NPs) on electrical properties of textured silicon solar cells without and with Si3N4 spacer layer. The parasitic absorption losses from Ag NPs reduced the internal quantum efficiency near the surface plasmon resonance region. The passive components like; series and parallel resistances, chemical capacitance of solar cells without and with Ag NPs are estimated after fitting impedance semicircles, which are further used for estimating effective carrier lifetime (τeff) values. Under AM1.5G illumination, cells with Si3N4 spacer layer showed a large decrease in the τeff due to the strong parasitic absorption losses from the Ag NPs. But, the cells without Si3N4 spacer layer showed a small decrease in the τeff due to the reduced surface recombination after partial field effect passivation from near-fields of Ag NPs’ surface plasmon resonances on the emitter surface.

Abstract Photovoltaic (PV) modules convert part of incident solar energy into electrical energy for commercial applications, with the rest being transferred to heat energy. The modelling of PV modules plays an important role in the fault diagnosis of a PV array. The object of this paper is to develop a parameter based model of a PV module. This model is sequentially coupled with an electrical model and energy balance equation. In order to establish the parameter based model, key parameters including the total effective solar energy, total heat exchange coefficient and ambient temperature are calculated from two working points on PV module along with the corresponding temperature from a thermal camera. Using the developed model, a fault diagnosis method based on the model is illustrated. Finally, model validation is carried out by the experiments.

Abstract Photovoltaic (PV) modules convert part of incident solar energy into electrical energy for commercial applications, with the rest being transferred to heat energy. The modelling of PV modules plays an important role in the fault diagnosis of a PV array. The object of this paper is to develop a parameter based model of a PV module. This model is sequentially coupled with an electrical model and energy balance equation. In order to establish the parameter based model, key parameters including the total effective solar energy, total heat exchange coefficient and ambient temperature are calculated from two working points on PV module along with the corresponding temperature from a thermal camera. Using the developed model, a fault diagnosis method based on the model is illustrated. Finally, model validation is carried out by the experiments.

It has been found in many countries with arid climates that massively walled buildings provide steady, comfortable inside temperatures even though the outside temperature fluctuations may be sizeable. The adobe houses of the American South-West, and the rondavels of southern Africa are particular examples. This phenomena is often termed the thermal flywheel effect. One explanation is that the temperature at the inside of a massive wall lags approximately out of phase with the outside, and so it partly offsets the direct, in phase, infiltration losses into the building. Thus the room temperature is kept approximately constant. In this paper the question of designing a non-homogeneous wall to optimize this effect is considered.