Fuzzy computing for feedstock selection in biogas plant

Fuzzy Inference System was designed to select the combination of feedstock that would provide over 55% methane yield in an anaerobic biogas digester at the same time maintaining neutral pH in it. This area was left untouched by fuzzy system experts in spite of the great importance it holds in determining the retention time of feedstock inside the digester which directly influences digester design dimensions. An FIS based on `Mamdani style' was designed with six Fuzzy `If-then' rules to act on two input variables of Feed stocks-C/N Ratio and Methane Yield that the feed stocks produced on anaerobic decomposition. The output was defuzzified using `centroid method' to classify the Feedstock as `Select' or `Reject'. Feedstock 1 with a C/N ratio of 16.5 and a methane yield of 65% was rejected with a membership of only 0.28 on the output selection scale. Feedstock 2 with a C/N of 25.8 and a methane yield of 70 % met 66 % of the selected feedstock criteria framed while Feedstock 3 proved the most suitable feedstock material featuring at 0.73 on the Feedstock selection membership scale with a C/N of 30.8 and 85% methane yield. The FIS model designed was evaluated for all combinations of C/N Ratio and methane yield. Feedstock belonging to [20-37.5] C/N range yielding at least 55% methane yield fell among the selected category of feedstock. Highest (6-7) membership range of selected feedstock was occupied by feed stocks between 25 to 35 C/N range yielding around 57.2% to 100% methane.