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Measuring DNI Using a Cost-Effective Fiber-Optic Radiometer

A recent paper in Sensors introduced a novel and cost-effective radiometer for measuring direct normal irradiance (DNI), a critical parameter for solar energy applications. The researchers aimed to provide an accurate and affordable alternative to traditional pyrheliometer-based DNI measurements.

Measuring DNI Using a Cost-Effective Fiber-Optic Radiometer

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Background

Solar energy is a crucial renewable resource in the global transition towards sustainability. Accurate solar irradiation data, particularly DNI, is essential for informed decision-making in various applications, including near-zero-emission building design, agriculture, climate change studies, healthcare, and renewable energy projects.

Solar irradiance, the radiant flux received by a surface per unit area from the sun, is a critical parameter in these fields. Specifically, DNI is the component of solar irradiance that comes directly from the sun without being scattered or reflected by the atmosphere.

DNI depends on geographical location, time of day, season, and weather conditions. Therefore, accurate and reliable measurements of DNI are essential for designing, operating, and optimizing solar energy systems. Traditionally, pyrheliometers, which utilize thermopile sensors, have been the standard for measuring DNI. However, these devices are often expensive and have a slow response time.

About the Research

The authors proposed a radiometer to overcome the limitations of traditional pyrheliometers. This innovative instrument utilized optical fiber and a photodiode to provide a cost-effective and fast-response alternative for measuring DNI. The optical fiber acted as a light beam collector, directing solar radiation to the photodiode, which was measured and converted into DNI.

This approach offered distinct advantages, including the ability to separate the measurement point from the detection point, making it suitable for installation in challenging environments. Additionally, the optical fiber's wide acceptance angle reduced alignment errors with the sun tracker. Complementing this, the photodiode offered fast response times, a broad dynamic range, and affordability.

The new instrument comprised several integrated components: an optical fiber exposed to solar radiation at one end and connected to the photodiode at the other; a photodiode linked to an optical power meter; and a data acquisition module that registered and stored optical power traces. These traces underwent processing via a calibration algorithm to derive the DNI measurement.

The calibration algorithm utilized a correction factor to compensate for wavelength-dependent photodiode response, solar spectral irradiance variations, and optical fiber attenuation. Specifically, it employed the solar spectral irradiance model from ASTM G173-03 Reference Spectra and the photodiode's responsivity data provided by the manufacturer.

The researchers conducted comprehensive performance evaluations of the radiometer under diverse conditions. They compared its measurements with those obtained using a commercial pyrheliometer, which served as the reference standard.

Their evaluations included testing four different optical fibers with varying core diameters and numerical apertures, assessing multiple working wavelengths for the optical power meter, and rigorously testing the radiometer's performance under various weather conditions, including sunny, cloudy, and rainy days.

Research Findings

The outcomes showed that the new radiometer performed similarly to the commercial pyrheliometer, with comparable accuracy and response time. It exhibited higher accuracy during the central hours of the day (when the solar spectrum is more stable) and lower accuracy during sunrise and sunset (when the solar spectrum varies more).

The findings also indicated that the optical fiber with a narrower core and a lower numerical aperture yielded measurements closer to those of the reference pyrheliometer. The optical fiber with a larger core and a higher numerical aperture had a larger dynamic range and a lower ripple.

Additionally, the study demonstrated the reliability, stability, and robustness of the developed radiometer, as well as its sensitivity to rapid changes in irradiance due to clouds and rain.

Applications

The radiometer has potential implications in various fields where solar irradiance measurements are needed, such as renewable energy, agriculture, climate change studies, and health. It is especially suitable for photovoltaic (PV) and concentrated solar power (CSP) systems, where it can be installed directly on panels or heliostats to provide real-time feedback for optimizing energy generation.

Additionally, the radiometer offers significant advantages due to its low cost, simplicity, modularity, and flexibility. It can be easily adapted to various spectrum ranges, acceptance angles, and dynamic ranges by selecting different optical fibers and photodiodes.

Conclusion

The novel approach for measuring DNI demonstrated effectiveness with several advantages, including quick response time, wide measurement capabilities, versatility, sensitivity, and resilience to noise and temperature changes.

The authors suggested improving their approach by incorporating a correction factor to adjust for changes in solar radiation levels during the day and under different atmospheric conditions.

They also proposed refining the design of the optical fiber and the process of measuring optical power to reduce errors and enhance the radiometer's accuracy and reliability. These enhancements would ensure precise DNI measurements in a variety of environmental settings.

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Journal Reference

Carballar, A., et al. (2024). Measuring DNI with a New Radiometer Based on an Optical Fiber and Photodiode. Sensors. https://www.mdpi.com/1424-8220/24/11/3674

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Muhammad Osama

Written by

Muhammad Osama

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence.

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