Modeling of Environmental-Energy Efficiency of the Biogas Installation with Heat Supplying of the Biomass Fermentation Process
, , , oraz
27 sty 2021
O artykule
Kategoria artykułu: research-article
Data publikacji: 27 sty 2021
Zakres stron: 115 - 124
Otrzymano: 03 maj 2020
Przyjęty: 09 paź 2020
DOI: https://doi.org/10.21307/acee-2020-036
Słowa kluczowe
© 2020 Georgiy Ratushniak et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Figure 1.
![Extent of fuzzy based research in renewable energy modeling. “x” axis – denotes year; the origin is [2006,0]. “y” axis – denotes the techniques in increasing complexity. The techniques are 1 – fuzzy regression, 2 – neuro-fuzzy, ANFIS, 3 – fuzzy AHP, ANP, 4 – fuzzy clustering, 5 – fuzzy optimization, 6 – neuro-fuzzy DEA, 7 – fuzzy GA, 8 – neuro-fuzzy GA, 9 – fuzzy expert, 10 – neuro-fuzzy expert, 11 – fuzzy MCDM, 12 – fuzzy TOPSIS, VIKOR, 13 – fuzzy PSO, 14 – fuzzy honey bee optimization, 15 – fuzzy PSO, QPSO, Cuckoo optimization.
Note: the number inside the bubble indicates the technique and size of the bubble indicates the no. of research publication](https://sciendo-parsed.s3.eu-central-1.amazonaws.com/6470700c83f1392090d69816/j_acee-2020-036_fig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA6AP2G7AKOUXAVR44%2F20250906%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Date=20250906T054512Z&X-Amz-Expires=3600&X-Amz-Signature=61053ac27a9436effbd00c7d65915678dfc7f162967240cd9903d9d65baa2243&X-Amz-SignedHeaders=host&x-amz-checksum-mode=ENABLED&x-id=GetObject)
Figure 2.
![Biogas installation with combined system of heat supply for thermal stabilization of the bioconversion process [3]](https://sciendo-parsed.s3.eu-central-1.amazonaws.com/6470700c83f1392090d69816/j_acee-2020-036_fig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA6AP2G7AKOUXAVR44%2F20250906%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Date=20250906T054512Z&X-Amz-Expires=3600&X-Amz-Signature=773e70d51fdf55b8d2f85d8fb12364cb0755ca103b53c15dbe0461954db5fea0&X-Amz-SignedHeaders=host&x-amz-checksum-mode=ENABLED&x-id=GetObject)
Figure 3.
Figure 4.
Classification of influence factors on the environmental- energy efficiency and term values as linguistic variables
| Influence factors | Designation and name of the linguistic variable | Terms for evaluating linguistic variables | |
|---|---|---|---|
| Environme ntal, |
The effect of reducing carbon monoxide emissions in exergy units, |
Low (L) |
|
| The effect of preventing environmental pollution in exergy units, |
Low (L) |
||
| The effect of using biofuels in exergy units, |
Low (L) |
||
| The effect of the use of organic fertilizers in exergy units, |
Low (L) |
||
| Influence factors | Designation and name of the linguistic variable | Terms for evaluating linguistic variables | |
| Exergy effect from receiving additional thermal energy from traditional sources, |
Low (L) |
||
| Energy, |
Exergy effect of obtaining additional solar energy, |
Low (L) |
|
| Exergy effect of receiving additional thermal energy from the heat pump, |
Low (L) |
||
| Fermentation temperature regimes, |
Exergy effect at: | Thermophilic mode, |
Low (L) |