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Title:Razvoj modela sestave različnih rastlinskih substratov za proizvodnjo bioplina
Authors:Ošlaj, Matjaž (Author)
Vindiš, Peter (Mentor) More about this mentor... New window
Tauginienė, Loreta (Co-mentor)
Kraner Šumenjak, Tadeja (Co-mentor)
Files:.pdf DOK_Oslaj_Matjaz_2016.pdf (3,67 MB)
 
Language:Slovenian
Work type:Doctoral dissertation (mb31)
Organization:FKBV - Faculty of Agriculture and Life Sciences
Abstract:Najpomembnejši ukrep za zmanjševanje emisij toplogrednih plinov in energetske učinkovitosti je povečanje deleža rabe obnovljivih virov energije. Slovenija mora, tako kot ostale države EU, na področju razvoja obnovljivih virov energije doseči ambiciozne cilje, ki bodo tako prispevali k povečanju zanesljivosti oskrbe z energijo, zmanjšanju učinkov na okolje, gospodarski rasti in razvoju delovnih mest ter zaposlenosti. Potrebno je iskati nove obnovljive vire, ki v svetu igrajo vse pomembnejšo vlogo pri proizvodnji energije. Proizvodnja bioplina z anaerobno fermentacijo je ena izmed tehnologij za proizvodnjo energije, trajnostno obdelavo odpadkov in zmanjšanje emisij toplogrednih plinov. Z raziskavo smo preučili energetsko vrednost rastlinskih vrst. S tem namenom smo izvajali poljske in laboratorijske poskuse v letih 2010 in 2011. Z optimatizacijo anaerobnega procesa fermentacije novih substratov za proizvodnjo bioplina smo uporabili poskusni reaktor. Pridobivanje bioplina iz energetskih substratov smo izvedli po nemškem standardu DIN 38 414, del 8. Anaerobno digestijo smo izvedli z osnovnim substratom prašičje gnojevke in v različnih sestavah sosubstrata. Sosubstrat smo sestavljali v različnih kombinacijah energetskih rastlin. Za sosubstrat smo uporabili koruzo (glavni posevek), koruzo (strniščni posevek), tritikale (glavni posevek), sirek (glavni posevek), mešanico rastlin za pridelavo biomase (glavni posevek) in koruzo za zrnje (zrnje v fazi voščene zrelosti). Podatke, vključene v raziskavo, smo analizirali s programi MS-Excel 2013 in SPSS (SPSS. Inc., Chicago, IL) ter programom R, verzije 3.0.2. Ločeno smo obravnavali in izračunali aritmetično sredino in standardni odklon. Z enosmerno analizo variance smo ugotavljali vpliv različnih mešanic poljščin na nekatere proučevane spremenljivke. Z multiplo regresijo smo ugotavljali vpliv spremenljivk (sestava substrata) na količino proizvedenega bioplina in količino proizvedenega biometana. Na osnovi MM-metode in OLS-metode smo izdelali več modelov, ki omogočajo napoved proizvodnje bioplina in biometana iz substrata s sosubstratom. Z rezultati poljskih in laboratorijskih analiz smo razvili računalniški model BIOPLIN, s katerim lahko napovedujemo proizvodnjo bioplina in biometana iz določenega substrata in sosubstrata na osnovi metode DIN 38 414. Model za napoved proizvodnje bioplina in biometana je sestavljen iz štirih podmodelov, ki so sestavni del glavnega modela. Koruzo, ki je ključna pri proizvodnji bioplina lahko nadomestimo z drugimi mešanicami sosubstrata. Sestava substrata vpliva na kvaliteto in kvantiteto nastalega bioplina in biometana.
Keywords:anaerobna fermentacija, bioplin, substrat, sestava substrata, model, statistični model
Year of publishing:2016
Source:Maribor
NUK URN:URN:SI:UM:DK:OCAS0H51
Views:894
Downloads:89
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Categories:FKBV
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Secondary language

Language:English
Title:Developing a Model for the Composition of Various Plant Substrates for Biogas Production
Abstract:The most important measure for reducing greenhouse gas emissions and achieving energy efficiency is to increase the share of renewable energy sources. Slovenia, like the other EU countries, has to reach ambitious goals in the field of the development of renewable energy sources; this will contribute to increasing the reliability of the energy supply, reducing the impact on the environment, improving economic growth and to the development of jobs and employment. It is necessary to look for alternate renewable resources which play an increasingly important role in energy production worldwide. The production of biogas from anaerobic fermentation is one of the technologies that can contribute towards energy production, sustainable waste management and the reduction of greenhouse gas emissions. The purpose of the research was to examine the energy value of the plant species; to this end, we conducted field and laboratory experiments in 2010 and 2011. In order to optimiz the anaerobic fermentation process of new substrates for biogas production, we used an experimental reactor. Biogas production from energy substrates was carried out according to the German standard DIN 38414, Part 8 (DIN 38 414, 1985). Anaerobic digestion was carried out using a basic pig slurry substrate and in different configurations of co-substrates. The co-substrates was composed of various combinations of energy crops. For the co-substrates we used maize (main crop), maize (stubble crop), triticale (main crop), sorghum (main crop), a mixture of plants for biomass production (main crop) and grain maize (grain at the wax ripeness stage). The data included in the research were analyzed using MS-Excel 2013 and SPSS (SPSS. Inc., Chicago, IL) and the R program, version 3.0.2. Separately, we discussed and calculated the arithmetic mean and standard deviation. With one-way analysis of variance we determined the influence of different mixtures of crops on some of the studied variables. With the multiple regression we determined the impact of variables (composition of the substrate) on the amount of biogas produced and the quantity of bio methane that was produced. Using the results of the field and laboratory analyses, we developed a model, BIOGAS, with which we can predict the production of biogas and biomethane from a particular combination of substrate and co-substrate based on the DIN 38 414 method. The model for predicting the production of biogas and biomethane is composed of four sub-models, which are integral parts of the main model. Based on the MM-method and the OLS-method, we developed several models that allow us to predict biogas and biomethane production from a given combination of substrate and co-substrates. We came to the conclusion that we can replace corn, which is crucial in the production of biogas, with other mixtures of co-substrates. Findings showed that the composition of the substrate does affect the quality and quantity of the biogas and biomethane that are generated.
Keywords:anaerobic fermentation, biogas, substrate, composition of the substrate, model, statistical model


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