Monofermentation of grass silage under mesophilic conditions: Measurements and mathematical modeling with ADM 1

Wichern, Marc; Gehring, Tito; Fischer, Katrin; Andrade, Diana; Lübken, Manfred; Koch, Konrad; Gronauer, Andreas; Horn, Harald

doi:10.1016/j.biortech.2008.09.030

Cited by 74 publications

(45 citation statements)

References 28 publications

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“…Lantz 48 investigated three types of manure-based 1-6 GWh y -1 biogas plants with 35 -290 kW el installed electrical capacity and found that none of them was profitable under Swedish market conditions. Hochloff and Braun 14 also concluded that none of their scenarios would be profitable without the German flexibility premium, and there is no such incentive in Sweden.…”

Section: Discussionmentioning

confidence: 99%

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Demand-Orientated Power Production from Biogas: Modeling and Simulations under Swedish Conditions

et al. 2015

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The total share of intermittent renewable electricity is increasing, intensifying the need for power balancing in future electricity systems. Demand-orientated combined heat and power (CHP) production from biogas has potential for this purpose. An agricultural biogas plant, using cattle manure and sugar beet for biogas and CHP production was analysed here. The model Dynamic Biogas plant Model (DyBiM) was developed and connected to the Anaerobic Digestion Model No. 1 (ADM1). Flexible scenarios were simulated and compared against a reference scenario with continuous production, in order to evaluate the technical requirements and economic implications of demand-orientated production. The study was set in Swedish conditions regarding electricity and heat price and the flexibility approaches assessed were increased CHP and gas storage capacity and feeding management. The results showed that larger gas storage capacity was needed for demand-orientated CHP production, but that feeding management reduced the storage requirement because of fast biogas production response to feeding. Income from 2 electricity increased by 10%, applying simple electricity production strategies to a doubled CHP capacity. However, as a result of the currently low Swedish diurnal electricity price variation and lack of subsidies for demand-orientated electricity production, the increase in income was too low to cover the investment costs. Nevertheless, DyBiM proved to be a useful modelling tool for assessing the economic outcome of different flexibility scenarios for demand-orientated CHP production.

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Section: Discussionmentioning

confidence: 99%

“…31 ADM1 has been applied to various substrates, e.g. grass silage, cattle manure and agricultural substrates, [34][35][36][37] and has been modified and extended by a great number of research groups. [38][39][40][41][42] Several studies report good model performance.…”

Section: Modelmentioning

confidence: 99%

Demand-Orientated Power Production from Biogas: Modeling and Simulations under Swedish Conditions

et al. 2015

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“…The ADMl parameters are set to standard values, except for the parameterŝ s,c4, ^m,pro, ^m,ac, ^i,NH3 and k"_h2, as recommended in Wichern et al ( , 2009. The characterization of the ADMl input stream is based on the following measurements, which have been performed for all substrates.…”

Section: The Biogas Plantmentioning

confidence: 99%

State estimation for anaerobic digesters using the ADM1

Gaida

Wolf

Meyer

et al. 2012

Water Science and Technology

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The optimization of full-scale biogas plant operation is of great importance to make biomass a competitive source of renewable energy. The implementation of innovative controi and optimization algorithms, such as Nonlinear Model Predictive Control, requires an online estimation of operating states of biogas plants. This state estimation allows for optimal control and operating decisions according to the actual state of a plant. In this paper such a state estimator is developed using a calibrated simulation model of a full-scale biogas plant, which is based on the Anaerobic Digestion Model N0.1. The use of advanced pattern recognition methods shows that model states can be predicted from basic online measurements such as biogas production, CH4 and CO2 content in the biogas, pH value and substrate feed volume of known substrates. The machine learning methods used are trained and evaluated using synthetic data created with the biogas plant model simulating over a wide range of possible plant operating regions. Results show that the operating state vector of the modelled anaerobic digestion process can be predicted with an overall accuracy of about 90%.This facilitates the application of state-based optimization and control algorithms on full-scale biogas plants and therefore fosters the production of eco-friendly energy from biomass.

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“…Chen & Hashimoto, 1980;Kiely et al, 1997;Kalfas et al, 2006;Sosnowski et al, 2007;Boubaker & ridha, 2008;Liu et al, 2008;Vavilin et al, 2008;Qu et al, 2009) or waste water treatment (e.g. Batstone et al, 2002;Feng et al, 2006;Tomei et al, 2008;Boubaker & ridha, 2008), not so many results can be found on modeling of agricultural biogas production (Hill & Barth, 1977;Simeonov et al, 1996;Angelidaki et al, 1999) and only a few consider the digestion of energy crops (Wichern et al, 2008(Wichern et al, & 2009Beierlein et al, 2010). The developed models, in particular the most complex ADM1, show high complexity and include a great number of parameters, which improve the accuracy of the model on one hand, but create implementation difficulties on the other hand as in many cases all data required by such models cannot be collected.…”

Section: Introductionmentioning

confidence: 99%

Kinetic Considerations on Thermophilic Digestion of Maize Silage at Different Feeding Modes

Golkowska

Sibisi-Beierlein

Greger

2012

Chemie Ingenieur Technik

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Digestion of maize silage in batch, semi‐batch and continuous mode was investigated under similar experimental conditions with the aim to compare the degradation kinetics. The modeling with the 1st order equation shows that despite the ensiling pre‐treatment the disintegration/hydrolysis step determines the total degradation rate of the substrate. The results confirmed an extremely high adaptation capability of anaerobic biocenosis to increased feeding frequency, rather than to higher but less frequent loadings. 2 – 3 times higher degradation rates were observed for tripled feeding frequency. On the other hand, an increase in organic loading within the same feeding mode always resulted in reduction of digestion rate.

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Monofermentation of grass silage under mesophilic conditions: Measurements and mathematical modeling with ADM 1

Cited by 74 publications

References 28 publications

Demand-Orientated Power Production from Biogas: Modeling and Simulations under Swedish Conditions

Demand-Orientated Power Production from Biogas: Modeling and Simulations under Swedish Conditions

State estimation for anaerobic digesters using the ADM1

Kinetic Considerations on Thermophilic Digestion of Maize Silage at Different Feeding Modes

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