Determination of renewable energy yield from mixed waste material from the use of novel image analysis methods

• Two novel methods used to determine renewable energy content and yield from mixed waste materials.
• Biogenic content of waste components measured, along with proximate and ultimate analysis.
• Determined values accurate to within 5% of actual values.
• Key applications include renewable energy yield prior to combustion and classification of SRF.

Two novel techniques are presented in this study which together aim to provide a system able to determine the renewable energy potential of mixed waste materials. An image analysis tool was applied to two waste samples prepared using known quantities of source-segregated recyclable materials. The technique was used to determine the composition of the wastes, where through the use of waste component properties the biogenic content of the samples was calculated. The percentage renewable energy determined by image analysis for each sample was accurate to within 5% of the actual values calculated. Microwave-based multiple-point imaging (AutoHarvest) was used to demonstrate the ability of such a technique to determine the moisture content of mixed samples. This proof-of-concept experiment was shown to produce moisture measurement accurate to within 10%. Overall, the image analysis tool was able to determine the renewable energy potential of the mixed samples, and the AutoHarvest should enable the net calorific value calculations through the provision of moisture content measurements. The proposed system is suitable for combustion facilities, and enables the operator to understand the renewable energy potential of the waste prior to combustion.