The environmental policy of the European Union is boosting the development of renewable energies. Among these, bioenergy holds the main share and is expected to further increase. Such development requires a higher degree of efficiency in the whole supply chain. This is achieved also with an enhanced fuel quality control and a better matching with the energy conversion systems. For solid biofuels, moisture content is the main quality parameters, influencing the sustainability of the whole energy system. With the aim to provide a real-time and portable tool for moisture measurement, a hand-held near infrared spectrometer was tested on a dataset of 817 wood chip samples provided by an industrial facility. A set of key performance parameters were used to compare the estimation of three alternative prediction models and the standard oven dry method. Results show a satisfactory reliability with R2 ranging from 0.86 to 0.89 depending on the model. A single measure can be acquired in few seconds, and the potential to
Performance of a portable NIR spectrometer for the determination of moisture content of industrial wood chips fuel
Leoni E.;Picchi G.
2022
Abstract
The environmental policy of the European Union is boosting the development of renewable energies. Among these, bioenergy holds the main share and is expected to further increase. Such development requires a higher degree of efficiency in the whole supply chain. This is achieved also with an enhanced fuel quality control and a better matching with the energy conversion systems. For solid biofuels, moisture content is the main quality parameters, influencing the sustainability of the whole energy system. With the aim to provide a real-time and portable tool for moisture measurement, a hand-held near infrared spectrometer was tested on a dataset of 817 wood chip samples provided by an industrial facility. A set of key performance parameters were used to compare the estimation of three alternative prediction models and the standard oven dry method. Results show a satisfactory reliability with R2 ranging from 0.86 to 0.89 depending on the model. A single measure can be acquired in few seconds, and the potential toFile | Dimensione | Formato | |
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