Ingemar Olofsson

Analysing biomass torrefaction supply chain costs

The objective of the present work was to develop a techno-economic system model to evaluate how logistics and production parameters affect the torrefaction supply chain costs under Swedish conditions. The model consists of four sub-models: (1) supply system, (2) a complete energy and mass balance of drying, torrefaction and densification, (3) investment and operating costs of a green field, stand-alone torrefaction pellet plant, and (4) distribution system to the gate of an end user. The results show that the torrefaction supply chain reaps significant economies of scale up to a plant size of about 150-200 kiloton dry substance per year (ktonDS/year), for which the total supply chain costs accounts to 31.8 euro per megawatt hour based on lower heating value (€/MWhLHV). Important parameters affecting total cost are amount of available biomass, biomass premium, logistics equipment, biomass moisture content, drying technology, torrefaction mass yield and torrefaction plant capital expenditures (CAPEX).

Quality assurance of torrefied biomass using RGB, visual and near infrared (hyper) spectral image data

Visible and near infrared imaging techniques for analysing characteristics of torrefied biomass were evaluated for possible use in future online process control. The goal of such a control system is to identify products with the desired properties and reject products outside the specification. Two pushbroom hyperspectral cameras with different wavelength regions and a commercial digital colour camera were evaluated. The hyperspectral cameras, short wave infrared (SWIR) and visible–near infrared (VNIR), covered the ranges of 1000–2500 nm and 400–1000 nm, respectively. The biomass was produced according to an experimental design in a torrefaction pilot plant at different temperatures, residence times, and nitrogen and steam flow rates to obtain a wide range of different characteristics and qualities of torrefied material. Chemical characteristics, heating values and milling energy of the different torrefied materials were analysed or calculated using standardized procedures and were used for calibration. For the hyperspectral images, a principal-component analysis was performed on the absorbance spectra. The score plots and score images were used interactively to separate background, outlier pixels and shading effects from sample signal. Averaged spectra of individual torrefied woodchips were used. Partial least-squares regression was used to relate average spectra to heating values and chemical characteristics of the torrefied biomass. Owing to the small size of the data sets, cross-validation using leave-one-out validation was used for testing the models. The ratio of standard error of prediction to sample standard deviation (RPD) values were used for comparing the imaging techniques. For RGB images, all RPD values were 4 or lower. The RPD values for the VNIR technique were all below 5, while the SWIR images produced RPD values above 5 for eight of the 13 properties. The promising results of the SWIR technique strongly suggested that the torrefied biomass undergoes changes to chemical structures, which are not necessarily manifested as changes to the colour of the material.