**4. Efficiency assessment of laboratory data**

This paper describes the development of a model characterizing an idealized reference process of dark fermentation. Based on the deviation between experimental data and the idealized reference process, the efficiency of the actual process can be quantified.

By comparing the real and the simulated concentration curves, the efficiency of the process can be mapped. At the same time, each concentration present in the reactor provides information about biodegradation *via* the model.

MicroPro GmbH experimentally obtained reaction rates of the components H2 and CO2 in a corn silage fermentation. Other components could not be measured for technical reasons.

Since the real-time process does not relate to the reaction steps in a linear matter, data points have been adopted to the respective reaction steps. At this point, there is no accurate way to measure the progress of the reaction in terms of reaction steps. The experimental data has, therefore, been adjusted to the simulated data based on H2 and CH4 formation.

**Figure 9** compares the experimental data with the calculated reaction conversions.

#### **4.1 Performance indicator for the biological reaction**

The deviation between the experimental and simulated data can be represented by the PhO factor defined by eq. 11. D. Volta first described the PhO factor, which compares an actual process and an idealized reference process, the so-called PhO [36].

$$F\_{\text{PhO,unover}} = \frac{\text{Modded concentration}}{\text{Experimental concentration}} \le 1\tag{10}$$

**Figure 10** shows the course of the PhO factor over the respective reaction steps. As expected, the idealized reference process was not achieved under laboratory conditions. However, it is noticeable that the efficiency of the process fluctuates strongly over the course of the process.

#### **Figure 8.**

*Substance conversions of various (intermediate) products during anaerobic degradation determined by the Petri net. Left: Resulting biogases CH4. CO2 and H2; right: Organic acids.*

*Optimizability of Biogenic Hydrogen Production DOI: http://dx.doi.org/10.5772/intechopen.111853*

#### **Figure 9.**

*Comparison of the model-based and experimental reaction turnovers of hydrogen H2 (blue) and methane CH4 (red). The concentration is in Mol per kilogram of corn silage per liter of fermenter contents.*

#### **Figure 10.**

*PhO turnover factor through comparison of experimental and modeled data for H2 concentration in the reactor.*

During the reaction, the PhO factor is a maximum of 0.79 (reaction step 9) and a minimum of 0.44 (reaction step 23). This suggests an optimization potential of the biological process of 21–56%. However, to be able to make a more precise statement as to whether this optimization potential is technically achievable, more detailed investigations must be carried out.

#### **4.2 Discussion and outlook**

A model was developed to evaluate the efficiency of the metabolism of dark fermentation on a laboratory scale, simulating the degradation and formation of all reactants, products, and intermediates.

The developed model is based on a PN, which uses defined rates and conditions for the course of a reaction for each defined step. A change in these rates and conditions directly influences the results of the PN and thus shifts the modeled optimum of the reaction. While the requirements for a reaction step are already very well described in the literature, the reaction rates can only be determined by approximating experimental data. The practical reaction rates used for the model were taken from various sources (cf. **Table 1**).

Since it was not technically possible to measure the concentration curves over time in the reactor, a more concrete validation had to be omitted at this point that the final product composition of the simulated process agrees with literature data and values collected in the experiment implies that most reaction rates were chosen realistically. Which reaction rates were defined too inaccurately at the current time can only be found by parameter variation and behavioral analysis of the model under comparison with experimental data.

Thus, the hydrogen and methane production rates were mapped using pressure differences and converted into concentrations for evaluation. Therefore, the pure hydrogen increase could only be measured up to reaction step 21. From then on, a comparison had to be made with combination experiments to estimate the concentration of H2 and CH4, separately. In these combination experiments, reactor contents were fed unchanged to methanation after dark fermentation.

Since the concentrations of the reactants, intermediates, and products cannot be monitored technically during the reaction, the temporal assignment of the experimental data to the respective reaction steps was based solely on the calculated H2 concentrations in the reactor. Further experiments must prove the reproducibility of this assignment.

Another reason for possible inaccuracies in the model is that a change in pH was not considered in the modeling. However, these effects were deliberately neglected since the process is intended to represent an idealized reference process to identify optimization potential by comparison with an actual process.

As part of the HyPerFerment II project, the construction of a demonstration plant for dark fermentation is planned. Here, data can be collected for the first time on a small industrial scale and under nonlaboratory conditions. Further experimental data must be collected to better adapt the model of the idealized reference process of dark fermentation to actual conditions.
