Photovoltaic Characterization Under Artificial Low Irradiance Conditions Using Reference Solar Cells

Hamadani, Behrang H.; Campanelli, Mark

doi:10.1109/jphotov.2020.2996241

Cited by 26 publications

(20 citation statements)

References 33 publications

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“…The GaAs module is 14.1% efficient and the Si module's PCE is 9.3%. Note that these module PCE values are significantly lower than values reported in reference 20 for individual solar cells of the same type (GaAs: 22.8%, GaInP: 26.8%, and Si: 12.5%). In particular, the fill factors in mini-module form are lower as compared to individual cells.…”

Section: I-v Curve Performancescontrasting

confidence: 59%

“…The effective irradiance ratio, F, on the test mini-modules was determined using a calibrated reference cell and a procedure that has been previously described. 20 In this procedure, the light intensity is adjusted so that the mini-module is exposed to an illuminance of exactly 1000 lx as achieved using a previously established reference light source with a correlated color temperature (CCT) of 3000 K and a total irradiance of 2.93 W/m 2 . Its emission spectrum is shown in Figure 3.…”

Section: Test Setup and Electrical Measurementsmentioning

confidence: 99%

“…As noted previously, I-V curve measurements were taken for each mini-module while illuminated by the LED light source described above (CCT of 3000 K and illuminance of 1000 lx 20 ). Figure 5 shows the I-V curve, and Table 1 summarizes the performance parameters of each mini-module under this lighting condition.…”

Section: I-v Curve Performancesmentioning

confidence: 99%

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Indoor light energy harvesting for battery‐powered sensors using small photovoltaic modules

Shore

Roller

Bergeson

et al. 2021

Energy Science & Engineering

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In recent years, our understanding of the electrical performance of various PV technologies under artificial or natural low light conditions has grown significantly. The main motivating factor for such measurements has been the desire to add to the growing knowledge on how to efficiently harvest ambient light energy in office spaces and homes for powering a variety of electronic devices, particularly Internet-of-Things smart sensors. [1][2][3][4][5] PV cells composed of various cell technologies (a-Si, c-Si, III-V semiconductors, dye-sensitized, and perovskite) have been compared under low light conditions for indoor energy harvesting purposes. [6][7][8] Various types of artificial lighting have been investigated to determine the highest energy density cells for each source. 9,10 Specific spectra in low

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Section: I-v Curve Performancescontrasting

confidence: 59%

Section: Test Setup and Electrical Measurementsmentioning

confidence: 99%

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Indoor light energy harvesting for battery‐powered sensors using small photovoltaic modules

Shore

Roller

Bergeson

et al. 2021

Energy Science & Engineering

Self Cite

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“…By this method, researchers are able to calibrate the light intensity levels simply by using the reference cell, without the need to measure the absolute irradiance of the indoor light sources or the absolute quantum efficiency of the PV devices. 90 3.1.2 Measurement of photovoltaic parameters. For indoor PV measurements, J sc , V oc and FF, extracted from the J-V characteristics, are usually reported.…”

Section: Qdpvs For Indoor Applicationmentioning

confidence: 99%

Indoor application of emerging photovoltaics—progress, challenges and perspectives

et al. 2020

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“…In [23], a comparison of the output performance between with halogen lamps having a power density of 1000 W/m 2 was show showed that, even with the same irradiation, the output performan is worse due to the different spectral behavior of the source and the c research groups have worked on automated test setups to further c For example, Verbelen et al demonstrated in [24] an automated tes ray of different light sources for testing. Hamadani and Campanell ber in [25] for testing reference cells with varying spectra of the LED In general, indoor light energy harvesting results in a strongly reduced output performance of the solar cells. In [22], this issue is shown for a cell with typical dimensions for IoT devices (1.9 cm × 5.0 cm).…”

Section: 21 X For Peer Reviewmentioning

confidence: 99%

Prospects of Wireless Energy-Aware Sensors for Smart Factories in the Industry 4.0 Era

et al. 2021

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Advanced sensors are becoming essential for modern factories, as they contribute by gathering comprehensive data about machines, processes, and human-machine interaction. They play an important role in improving manufacturing performance, in-factory logistics, predictive maintenance, supply chains, and digitalization in general. Wireless sensors and wireless sensor networks (WSNs) provide, in this context, significant advantages as they are flexible and easily deployable. They have reduced installation and maintenance costs and contributed by reducing cables and preinstalled infrastructure, leading to improved reliability. WSNs can be retrofitted in machines to provide direct information from inside the processes. Recent developments have revealed exciting possibilities to enhance energy harvesting (EH) and wireless energy transmission, enabling a reliable use of wireless sensors in smart factories. This review provides an overview of the potential of energy aware WSNs for industrial applications and shows relevant techniques for realizing a sustainable energy supply based on energy harvesting and energy transfer. The focus is on high-performance converter solutions and improvement of frequency, bandwidth, hybridization of the converters, and the newest trends towards flexible converters. We report on possibilities to reduce the energy consumption in wireless communication on the node level and on the network level, enabling boosting network efficiency and operability. Based on the existing technologies, energy aware WSNs can nowadays be realized for many applications in smart factories. It can be expected that they will play a great role in the future as an enabler for digitalization in this decisive economic sector.

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Photovoltaic Characterization Under Artificial Low Irradiance Conditions Using Reference Solar Cells

Cited by 26 publications

References 33 publications

Indoor light energy harvesting for battery‐powered sensors using small photovoltaic modules

Indoor light energy harvesting for battery‐powered sensors using small photovoltaic modules

Indoor application of emerging photovoltaics—progress, challenges and perspectives

Prospects of Wireless Energy-Aware Sensors for Smart Factories in the Industry 4.0 Era

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