Energie · Gebäude · Umwelt (EGU)
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- Biohydrogen;Hydrogen yield;Volatile fatty acids;Hydrogen production rate;Wastewater treatment;Methane production rate (1)
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Due to a limited number of available measurements on agricultural biogas plants, established process models, such as the Anaerobic Digestion Model No. 1 (ADM1), are rarely applied in practise. To provide a reliable basis for model-based monitoring and control, different model simplifications of the ADM1 were implemented for process simulation of semi-continuous anaerobic digestion experiments using agricultural substrates (maize silage, sugar beet silage, rye grain and cattle manure) and industrial residues (grain stillage). Individual model structures enable a close depiction of biogas production rates and characteristic intermediates (ammonium nitrogen, propionic and acetic acid) with equal accuracy as the original ADM1. The impact of different objective functions and standard parameter values on parameter estimates of first-order hydrolysis constants and microbial growth rates were evaluated. Due to the small number of required model parameters and suitable system characteristics, simplified model structures show clear advantages for practical application on agricultural biogas plants.
Rigorous process models provide a reliable basis for model-based monitoring and control of anaerobic digestion plants. Due to the complex model structure and non-linear system characteristics, the established Anaerobic Digestion Model No. 1 (ADM1) is rarely applied in industrial plant operation. The present investigation proposes a systematic procedure for successive model simplification and presents the description of five model variants of a mass-based ADM1. Individual model structures greatly differ in their number of implemented process phases, characteristic components and required parameters. Simplified model variants combine nutrient degradation and biogas formation based on first-order sum reactions, whereas complex model structures describe individual degradation pathways and intermediates during acido- and acetogenesis. Characteristic features of the derived model structures as well as the stoichiometric methane potentials and microbial biomass yields of the underlying degradation pathways of individual model variations are evaluated and discussed in detail.
Inter-laboratory reproducibility of biomethane potential (BMP) is dismal, with differences in BMP values for the same sample exceeding a factor of two in some cases. A large group of BMP researchers directly addressed this problem during a workshop held in Leysin, Switzerland, in June 2015. The workshop resulted in a new set of guidelines for BMP tests published in 2016, which is the subject of the present commentary. The work has continued with two international inter-laboratory studies and one additional workshop held in Freising, Germany, in 2018. The dataset generated by the two inter-laboratory studies were used to refine the validation criteria for BMP tests. Based on these new results an update to the original guidelines is proposed here.
The effects of different unsteady ventilation strategies on flow-structures in a room are investigated and compared to steady ventilation with the same mean exchange rate. For this, whole-field optical flow measurements were executed by means of a particle image velocimetry system (PIV) in a Reynolds-scaled room model in water. In a first series of experiments, sinusoidal varied supply flows with different frequencies were analysed; two equally supplied simple nozzles in the ceiling were used as inlets. The setup was validated by comparing jet velocities with literature values.
Typically, room airflows are investigated with punctual measurement techniques (e.g.
anemometers), which have an impact on the flow field, or with smoke gas experiments. By using PIV, the flow can be analysed without any influence of sensors or stands/traverses and whole-field measurement data with high spatial resolution and detailed information on the flow field can be collected.
Local and time-averaged velocities and standard deviations were calculated for all scenarios. Unsteady conditions were created by a sinusoidal variation of the supply flow rate with frequencies between 0.025 1/s and 0.050 1/s, an offset of about 1.1 m3/h and an amplitude of about ±1.0 m3/h, which leads to a mean exchange rate of 3.5 1/h. Although averaged velocity fields only show slight differences between steady and unsteady conditions, single pictures vary widely. First effects of unsteady ventilation on flow structures can be recognized. Steady structures are destroyed, and velocities change rapidly.
The inlets will be changed to small-scale ceiling-diffusors in future experiments to create more realistic room ventilation conditions. Other types of unsteady supply flows will be implemented, and parameters will be varied. The results of the PIV-measurements can be used to validate CFD simulations and to derive dimensioning rules and application recommendations.
About 75% of the world's energy consumption takes place in cities. Although their large energy consumption attracts a large number of research projects, only a small fraction of them deal with approaches to model energy systems of city districts. These are particularly complex due to the existence of multiple energy sectors (multi-energy systems, MES), different consumption sectors (mixed-use), and different stakeholders who have many different interests.
This contribution is a review of the characteristics of energy system models and existing modeling tools. It evaluates current studies and identifies typical characteristics of models designed to optimize MES in mixed-use districts. These models operate at a temporal resolution of at least 1 h, follow either bottom-up or hybrid analytical approaches and make use of mixed-integer programming, linear or dynamic.
These characteristics were then used to analyze minimum requirements for existing modeling tools. Thirteen of 145 tools included in the study turned out to be suitable for optimizing MES in mixed-use districts. Other tools where either created for other fields of application (12), do not include any methodology of optimization (39), are not suitable to cover city districts as a geographical domain (44), do not include enough energy or demand sectors (20), or operate at a too coarse temporal resolution (17). If additional requirements are imposed, e.g. the applicability of non-financial assessment criteria and open source availability, only two tools remain.
Overall it can be stated that there are very few modeling tools suitable for the optimization of MES in mixed-use districts.