A dynamic model for calculating methane emissions from digestate based on co-digestion of animal manure and biogas crops in full scale German biogas plants

Recirculation of solid digestate to enhance energy efficiency of biogas plants: Strategies, conditions and impacts

“…This can account for the previously determined increase in plant methane production as well as the higher biogas plant efficiency. Finally, 200 days of AD are seemingly required to reach a 95% methane recovery from the most complex feedstocks to degrade, such as manure [31]. For plant SRT to approach such a value via SD recirculation would be noteworthy for biogas plants that treat complex feedstocks (e.g.…”

New opportunities for agricultural digestate valorization: current situation and perspectives

“…Some authors have recently developed models predicting the amount of methane emissions in the storage tanks of biogas plants. 70,71 Muha et al studied 21 full-scale biogas plants operated with energy crops and cow manure. 71 The energy crops contained maize silage as the main substrate and smaller proportions of grass silage and grain, representing 56% to 100% of the feedstocks.…”

“…70,71 Muha et al studied 21 full-scale biogas plants operated with energy crops and cow manure. 71 The energy crops contained maize silage as the main substrate and smaller proportions of grass silage and grain, representing 56% to 100% of the feedstocks. Their model showed that a high (E95%) degradation of the substrate could be obtained if the hydraulic retention time (HRT) was at least 90 days for energy crops and at least 200 days for cattle manure.…”

“…10 The recirculation of the digestate in the biogas plant is an interesting option to reduce methane emissions and to produce more biogas from feedstocks. 20,36,39,[71][72][73] Several studies have determined the residual methane potentials of digestate, and results show a very high range of values; for example, in the case of pig slurry (87%) and energy crop (13%) co-digestion with 51 days of HRT, Menardo et al 5 obtained a residual methane potential as low as 3 NmL CH 4 g À1 VS 5 . On the contrary, Thygesen et al measured 240 NmL CH 4 g À1 VS as a residual methane potential of the digestate from pig manure (85%) and fish mucus (15%).…”

Design of Biogas Production Prediction Model Based on Improved BP Neural Network and Genetic Algorithm

“…In recent years, many domestic and foreign scholars have carried out research on biogas production forecasts.In [1] introduced kinetics (SD) theory into the prediction of gas production and established a kinetics gas production prediction model, namely the SD model;In [2] established a mathematical model and used multiple regression equation to predict biogas production; In [3][4][5] proposed the model by the artificial neural network to predict biogas production. These models are very complex and have different scopes of application.…”