Optimization Of Biogas Production Research Articles

Optimization of biogas production from anaerobic co-digestion of fish waste and water hyacinth

Many fresh water bodies face a great challenge of an invasive weed called water hyacinth (WH) which has great impacts on the environment, ecology, and society. Food and Agriculture Organization (FAO) estimates that over nine million tons of Fish wastes (FW) are thrown away each year. The fish waste generated poses environmental and health hazards because in most cases it is either disposed into pits or discarded onto the open grounds. Both WH and FW are potential substrates for biogas production. However, utilization of FW substrate alone has a limitation of producing a lot of amounts of volatile fatty acids (VFAs) and ammonia. Their accumulation in the digester inhibits substrate digestion. Consequently, as stand-alone it is not suitable for anaerobic digestion (AD). This can be overcome by co-digestion with a substrate like WH which has high carbon to nitrogen (C/N) ratio prior to biodigestion. Experimental variable levels for biogas were substrate ratio (WH:FW, 25–75 g), inoculum concentration (IC, 5–15 g/250 mL), and dilution (85–95 mL). Design-Expert 13 was used for optimization and results analysis. Response surface methodology (RSM) was used to examine the effects of operating parameters and identify optimum values for biogas yield. Optimum values for maximum biogas with the highest methane yield of 68% were found to be WH:FW ratio, 25:75 g, 15 g of IC, and 95 mL for dilution. The yield was 16% and 32% greater than FW and WH mono-digestion, respectively. The biogas yield was expressed as a function of operating variables using a quadratic equation. The model was significant (P < 0.05). All factors had significant linear and quadratic effects on biogas while only the interaction effects of the two factors were significant. The coefficient of determination (R2) of 99.9% confirmed the good fit of the model with experimental variables.

Modeling and optimization of biogas production in a batch bioreactor

Ever increasing demands for renewable energy sources are the driving force for the development of waste management technologies such as anaerobic digestion (AD) technology. For AD process understanding and optimization the numerical simulations provide a useful tool. Therefore, in this work, the main attention is focused on the development of an efficient and stable optimization approach. The optimization procedure is coupled with a suitable mechanistically inspired selfdeveloped BioModel. For BioModel calibration, a special procedure was developed which incorporates the used BioModel, a sensitivity analysis, and a gradient-based optimization algorithm. The results of numerical simulation, obtained by the AD of various animal manures in a batch lab-scale bioreactor, confirm the reliability of BioModel and the efficiency of the presented calibration procedure. Furthermore, the results of AD process optimization show that the biogas quantity and quality as well as energy used up for bioreactor heating can be improved essentially when amount of added bacteria, temperature and pH values are optimized properly.

Optimization of biogas production during start-up with electrode-assisted anaerobic digestion.

To better understand anaerobic digestion (AD) conditions during start-up, a series of batch and bench-scale studies were conducted to investigate conditions affecting the performance of the anaerobic reactors, including pH fluctuations, ammonia inhibition, and bioaugmentation. Capacitive soil moisture sensors were placed inside the AD reactors to provide near real-time microbial monitoring under experimental batch conditions and to create a microbial electrolysis cell (MEC) environment. After an eight-day digestion process at 40°C, the capacitive soil moisture sensors performed as a rudimentary microbial activity tracking device. However, the electrodes had a statistically significant impact on biogas production with a small potential 0.8V having a stabilizing effect on AD at 40°C during start-up. Furthermore, electrode-assisted AD noted a biogas output 63.7% higher than the conventional AD without electrodes. Conversely, the bioaugmented electrode-assisted AD showed a 7% increase in biogas volume when compared to the non-bioaugmented batch.

Optimization of Biogas Production from Cassava Peels Mixed with Urea by Central Composite Design Methodology

The amount of cassava wastes is increasing day by day especially in the developing countries like Nigeria and Democratic Republic of Congo because of the high demand of cassava as food or as raw matter in starch factories. In the both process, 1/3 of wastes is generated from 1 Kg of cassava tubers which could be used as substrate to produce biogas which is the renewable energy to decrease oil dependence and therefore atmospheric pollution depletion. The present study aims to know the optimal conditions for biogas production from biomethanization of cassava peels mixed with urea in mesophilic conditions during 14 days in sixteen reactors of 1 Litre capacity, using response surface methodology (RSM). Two parameters were studied, organic loading rate (OLR) and urea concentration (UC). The variations used for OLR was 5% and 15% TS and for UC, it was 0.01 % and 0.05 %. The variations obtained inside were determined by Central Composite Design (CCD) made from rsm package of R software 4.1.1. Based on experimental results analysis, it was found that urea concentration affect biogas production (P&lt;0.05), the optimum value of Organic Loading Rate and urea concentration were 6.688%TS and 0.0067% respectively, with a optimal biogas yield of 3260.694 mL. The analysis of variance (ANOVA) showed a high coefficient of determination value (R2=0.8146) at 95% confidence level and a p-value of 0.002. The results show that urea concentration has a major impact on biogas production (P&lt;0.05).

Prediction and Optimization of Biogas Production from OMW Digestion Using Fenton Pre-Treatment Process with Particle Swarm Optimization

Prediction and Optimization of Biogas Production from OMW Digestion Using Fenton Pre-Treatment Process with Particle Swarm Optimization

Optimization of Biogas Production from Sewage Sludge: Impact of Combination with Bovine Dung and Leachate from Municipal Organic Waste

Biogas is a bioenergy produced from organic or all types of biological degradable wastes and could make it possible to limit energy dependence. Sludge is the best alternative substrate for biogas production at a community-level biogas plant. The literature shows that co-digestion can increase the efficiency of sludge anaerobic digestion. This research, thus, focused on (i) determining the conditions of optimal biogas production in the co-digestion of primary sludge (PS) and bovine dung (BD), (ii) evaluating the impact of leachate from organic waste and cellulose on biogas production. Primary sludge was collected in Bacau town wastewater treatment plant in Romania. The sampling of municipal solid waste was carried out in Ouagadougou pre-collect centers (Burkina Faso). Batch tests were conducted in glass bottles through anaerobic digestion (1 L). The following parameters were monitored during the digestion process: pH, volatile fatty acid (VFA), volatile solids (VS) and biogas production. Primary sludge, bovine dung and leachate showed 50.51%, 72.41% and 70.48% of volatile solids content, respectively. Sludge showed good stability, unlike the other two substrates, such as bovine dung and leachate, with VFA to alkalinity ratio 0.54. Leachate from organic waste had high values of VFA to alkalinity ratio &gt; 3600. Co-digestion could make it possible to raise the levels of organic matter and improve microbial growth and the stability of anaerobic biomass. The best biogas production yield of 152.43 mL/g VS was obtained with a combination of 30% bovine dung and 70% primary sludge at 45 °C, with a 21.57% reduction in organic matter. An improvement in biogas productivity was effective with the addition of leachate, which could be used as an additive element during anaerobic digestion.

Effect of Cow Dung to Maize Silage Mix Ratios and Temperature Variation on Biogas Production in Laboratory Batch Digester

Optimization of biogas production from a given substrate and digester is an issue that needs to be addressed during the development of anaerobic digestion. To maximize the biogas production rate, the operating parameters that influence anaerobic digestion must be controlled and monitored. This research was carried out using a 0.15 m³ laboratory digester. The study evaluated the effect of cow dung and maize silage mix ratios (1:1, 1:3, and 3:1) on biogas production which were compared to their pure substrates at a constant temperature of 20°C. The temperatures (20°C, 25°C, and 30°C) were then evaluated using the optimal mix ratio of 3:1 as feedstock. The Temperature of the digester was controlled and monitored using Programmable Temperature Controller (Multispan UTC 421) and the (PLC) running on SIEMENS LOGO. The mix ratios and temperatures showed a significant effect on biogas production (P≤0.05) with mix ratios of 3:1 and 1:1 improving biogas production by 31.24% and 15.52% respectively compared to cow dung. The temperatures of 25°C and 30°C increased biogas by 26.99% and 47.35% and methane increased by 3.92% and 11.76% respectively compared to the mesophilic temperature of 20°C. The study thus, recommends a mix ratio of 3:1 and the optimal temperature of 30°C for a 0.15 m³ laboratory temperature-controlled fixed-dome anaerobic digester of cow dung and maize silage as a substrate when fed as a batch reactor.

Optimization of biogas yield from anaerobic co-digestion of corn-chaff and cow dung digestate: RSM and python approach

The utilization of various feedstocks of unique characteristics in producing biogas could potentially enhance the application of clean fuel from biomass wastes. Two modelling tools were used to explore biogas production from plant and animal wastes. In this study, corn chaff was inoculated with cow dung digestate using different mixing ratios of substrate/inoculum (S/I) of 1:1, 1:1.55, and 1:3.5 for hydraulic retention time (HRT) of 25, 31, and 37 days as modelled using Central Composite Design (Face Centered Design) to optimize the process and predict the optimal response. The result shows that the mixture ratio of 1:1.55 for 37 days gave a cumulative highest biogas yield of 6.19 L under mesophilic conditions. The model p-value is <0.0001, an indication that the model term is significant. The python coding of the input factors gave the optimal value of 4.71 L, which is similar to the result obtained via CCD. Thus, both CCD (Face Centered Design) and python coding are reliable in the optimization of biogas production as they both predicted the same optimal values and approximately the same highest cumulative biogas yield. The GC-MS characterization of produced biogas revealed that it contains 68% methane and 22.76% CO2. Other constituents present are confirmed by FTIR analysis results. The methane in produced biogas has a flashpoint of -182 °C, which is extremely flammable. This data shows that both CCD and python coding can model biogas production with high accuracy and biogas produced can be used for heating purposes.

Co-digestion of microbial biomass with animal manure in three-stage anaerobic digestion

Microbial biomass (MB) was co-digested with different animal manures namely, chicken manure (CM), pig manure (PM) and cow dung (CD) at the ratios of 1:1:1:1, 2:1:1:1 and 3:1:1:1, and analyzed for biogas production. Maximum biogas yield and methane concentration were found at the ratio of 1:1:1:1. The optimization of biogas production was carried out using different pH values, temperatures, and substrate concentrations. The yield of methane was measured at different temperatures (35, 40, 50 and 55 ˚C). The optimum was 40 ˚C giving 62% CH4/d yield on the 6th day. The result of this study showed that co-digestion with microbes is beneficial for maximizing biogas production when compared to the anaerobic digestion of animal manure alone. A digester with a three-stage anaerobic digesting facility was designed, fabricated and analyzed for biogas production using the co-digestion of yeast biomass with pig manure. The reactor had separate chambers for hydrolysis, acidogenesis and methanogenesis. Each of them was optimized independently for simultaneous production and improvement of biogas and to analyze the performance of the reactor. The average methane yield with a three-stage anaerobic digester was 0.442 L/gVS. Higher volatile solids (VS) reduction of about 68% was seen at the third stage pf anaerobic digesting. Based on the findings from this study, the three stage anaerobic digestion was identified to be advantageous for high solids anaerobic digestion of microbial biomass with animal manure. Solid organic matters in the substrate was solubilized which leads to the formation of improved biogas production and volatile fatty acids.

Optimization of Biogas Production Using Food Waste by Floating Drum Type Anaerobic Reactor

Optimization of Biogas Production Using Food Waste by Floating Drum Type Anaerobic Reactor

Optimization of biogas production through anaerobic digestion of municipal solid waste: a case study in the capital area of Reykjavik, Iceland

AbstractBACKGROUNDBiogas is a valuable carbon‐free renewable energy source that can be produced from anaerobic digestion of organic waste. Accordingly, biogas production is promoted worldwide in efforts to reduce carbon emissions and optimize the recovery of resources from waste streams. In this paper the biogas production from bioresidues collected in the capital area of Reykjavik was modelled in Aspen Plus v10.RESULTSMunicipal solid waste (MSW), food waste (FW) and lignocellulosic biomass (LCB) were the feedstocks used in this research. A total of 16 scenarios were simulated at thermophilic temperature conditions of 55 °C. Each scenario accounted for different inlet mass flows, varying the kind of feedstock, i.e. MSW, FW, LCB, or co‐digestion of various feedstocks, using two model approaches: (i) one digestion stage and (ii) two stages coupled in series. Sizing, costing and environmental aspects were analysed for all the scenarios. A sensitivity analysis was carried out by changing the substrate concentration and studying its effect on the methane mass flow. Simulations showed biogas yields measured in millilitres per gram of volatile solids (VS) in the range 305.5–406.4 mL g−1 VS (single‐stage approach); and biogas yields ranging from 64.78 to 358.8 mL g−1 VS (two‐stage approach). Maximum methane yields were obtained using LCB as feedstock resulting in 106.0 mL g−1 VS.CONCLUSIONSFrom a technical viewpoint the highest biogas yield is obtained when using MSW whereas optimum calorific value of biogas and electrical power potential is achieved working in co‐digestion of various feedstocks. © 2020 Society of Chemical Industry

Optimization of biogas production by mixture design of agro-industrial waste and biofertilization by co-digestion residues

L’objectif de cette étude est de proposer, par approche intégrée, une voie de gestion des déchets agro-industriels : halieutique, avicole, agrumicole. La valorisation énergétique du point de vue de la production de biogaz et aussi la valorisation du digestat qui en découle sont étudiées. Dix mixtures sont établies dans le cadre d’un plan simplexe-centroïde, leur digestion anaérobie dure environ 5000 min, suffisante pour atteindre la stabilité. L’évolution de plusieurs paramètres physico-chimiques tels que le pH, la conductivité, la matière sèche est déterminée. La conversion du carbone organique total (COT), le phosphore (P) et l’azote (NT) sont étudiés et modélisés par les surfaces d’isoréponses. Les contrôles microbiologiques pour vérifier l’hygiénisation des digestats sont menés. Le volume de biogaz produit pour les différents mélanges est mesuré en fonction du temps en utilisant la méthode du liquide déplacé. Finalement, le digestat est valorisé dans la fertilisation des sols agricoles, pour cela des tests de fertilisation sont ainsi conduits sur des cultures de poivrons (Capsicum annum). Les résultats montrent qu’il est possible de générer, après processus de digestion anaérobie optimale, un digestat, intéressant pour une application dans la fertilisation des sols agricoles, hygiénique par l’absence des micro-organismes d’altération, riche en azote, phosphore, potassium, caractérisé par un pH idéal pour la culture de poivrons.

Prediction and optimization of biogas production from POME co-digestion in solar bioreactor using artificial neural network coupled with particle swarm optimization (ANN-PSO)

Biogas production from anaerobic co-digestion (ACoD) of palm oil mill effluent (POME) and cattle manure (CM) is getting a lot of attention due to its wide availability and relatively simple energy conversion technology. The ACoD process is extremely complex to model with conventional mathematical modeling methods and requires the use of advanced computational tools due to the mixing of different substrates. Artificial neural network (ANN) is a very recent alternative to modeling tools used to predict complex ACoD problems. To get the best performance from ANN, the parameters of ANN need to be optimized. Here, particle swarm optimization (PSO) algorithms can be a great option. The present study investigates the possibility of using the combined ANN-PSO framework to simulate the process and to predict biogas production from the ACoD of POME and CM. The mixture ratio of POME and CM, oxidation by hydrogen peroxide, and ammonium bicarbonate effects were analyzed separately to increase biogas production using solar-assisted bioreactors. From the experiment, five data volumes of the amounts of POME, CM, hydrogen peroxide, ammonium bicarbonate, and biogas yield were recorded. This dataset has been used to design the proposed model. The results of the proposed ANN-PSO framework with an understanding of mean square error (MSE) and correlation coefficient (R) are 0.0143 and 0.9923, respectively. This result indicates that the proposed method is found to be effective and flexible in predicting biogas production from the ACOD of POME and CM.

Optimization of Biogas Production in a Batch Laboratory Digester Using Total Solids, Substrate Retention Time, and Mesophilic Temperature

Optimization of Biogas Production in a Batch Laboratory Digester Using Total Solids, Substrate Retention Time, and Mesophilic Temperature

Optimization of biogas production from water hyacinth by liquid anaerobic digestion (L-AD) using response surface methodology

In this biogas research from water hyacinth, we are using Central Composite Design and full factorial design. Enzyme (X1), C/N ratio (X2) and total solid (X3) is three experimental variables were selected as controlled factors. Performed on a laboratory scale and at room temperature with 16 runs for 60 days measured every two days. The variables were set at 3-9% for Enzyme concentration, C/N at between 20-50, and concentration of TS between 5-15% (LAD condition). Based on the research that has been done, the optimum conditions for the biogas production process from water hyacinth in Liquid State Anaerobic Digestion (LAD) conditions use Response Surface Methodology (RSM) in the variable range are the C/N ratio 30-40, 6% enzyme, and for TS was not significant factor. Following the run in the central composite experimental design, these values correspond to run number 10 with variable C/N ratio 35, enzyme 6% and TS 1.59% with biogas production 202.51 mL/g TS.

Optimization of biogas production in Indonesian region by liquid anaerobic digestion (L-AD) method from rice husk using response surface methodology (RSM)

Rice husk is one of agricultural waste that is potentially converted to biogas. In this research, rice husk is used as the material to produce biogas by liquid anaerobic digestion (L-AD) with TS concentration below 15/5. The purposes of this research are finding the optimum value of total solid (TS), C/N ratio, and microbial consortium (MC) for biogas production and then analyzing the optimum biogas production rate from rice husk. Because of the high lignin content, rice husk must be through the pretreatment stage using NaOH 3%. The variations of the observed factor are 5%, 10%, 15% for TS concentration; 20, 35, 50 for C/N ratio; and 3%, 6%, 9% for MC concentration. There are 16 reactors in which the variation for each reactor was determined by Central Composite Design. Data obtained from the research will be optimized using Response Surface Methodology (RSM) in Statistica 10. The result shows that the optimum condition of biogas production from rice husk is TS in between 1%-2.5%, C/N ration 33.45, and MC in between 5.5%-7%. Reactor having a combination of value factors that close to the optimum value will be analyzed using Polymath 6.0, which is reactor 10. The kinetics constant of biogas production rate (u) is 3.625 ml/grTS.day, the maximum biogas production (A) is 277.374 ml/gr TS, and the minimum time needed to produce biogas (λ) is 3.878 days.

Supply chain pinch analysis to optimal planning of biogas production

Supply chain is essential for an organization as it helps to maximize the operations which are profitable through the production, capacity, subcontracting, inventory and stock outs optimum levels. The traditional supply chain involves high documentation cost, with data involved that are mostly inaccurate and useless. In supply chain, the system of production plays an important role. The pinch analysis concept is initially used in the approach of energy conservation, and has extended to the optimization of resources and process integration. This paper presents the application of supply chain using pinch and cascade analysis for biogas production from palm oil mill effluent (POME). Biogas falls under the renewable energy where it can be produced via anaerobic digestion of POME. POME contributes to huge environmental impact mainly due to its high organic content. Supply chain via pinch analysis is used targeting to eliminate or reduce the difficulties faced in conventional supply chain. In this biogas supply chain analysis, it aims to meet the demand in a specific time frame. Minimum production rates are determined as accordance to the demand of electricity from 2020 to 2050. The pinch points are the points where the supply and demand are at the minimum, which the optimum production rate of electricity is able to determine from supply chain via pinch analysis. Monte Carlo Simulation tool is involved in the later stage of the study. It is used in the findings of analysing the increment of more than 10% of up-scale and down-scale production demand for each year for 35 years. The simulation is done from 2016 to 2035 of every five years interval. At the end of the study, the optimization of biogas production was achieved with the application of supply chain via pinch analysis. The supply and demand of biogas to electricity projection from 2020 to 2050 is forecasted. The optimal planning of electricity production from biogas was indicated in the supply chain cascade analysis.

Enhanced Biogas Production in Pilot Digesters Treating a Mixture of Olive Mill Wastewater and Agro-industrial or Agro-livestock By-Products in Greece

The selection of appropriate co-substrates is very important to the feasibility of an anaerobic co-digestion process. A proper choice of co-substrate compositions leads to system balance and increased methane generation. To valorize agricultural wastes and byproducts in southern Greece, anaerobic co-digestion of four feedstocks (olive mill wastewater—OMW, poultry manure—PM, liquid pig manure—LPM, and cheese whey—CW) was studied to produce biogas for renewable energy generation. Pilot- scale continuous co-digestion approaches were adopted to carry out the investigation under mesophilic temperatures (35 ± 2 °C) for 30 days. The feedstocks were mixed at different percentages according to their availabilities in southern Greece with a total solids (TS) ratio of approximately 10% and an OLR of 2.2 kg VS m−3 day−1. The main agro-industrial feedstock of this study is OMW. Two types of influent feedstock were utilized: a mixture of 30% v/v OMW and 70% PM and LPM, and a mixture of 40% v/v of OMW and 60% PM and CW. Therefore, optimization of biogas production from OMW was attempted by co-digesting with PM and LPM or CW. The aim of this study was to investigate the effect of different liquid feedstocks in order to have a total solids (TS) ratio of approximately 10%. Reduction in the volatile solids ranged between 50 and 57%. The average removal of dissolved chemical oxygen demand (COD) was 50% and 58% for the two examined scenarios, while the biogas production rate at the steady state reached 0.7 ± 0.4 and 1.2 ± 0.3 L/Lreactor/day respectively.

Optimization of Biogas Production from Anaerobic Fermentation of Corn Stalk by Combination Alkali Pretreatment

In order to explore the influence of alkali concentration, solid-liquid ratio, pretreatment time and component ratio on biogas production from corn stalk anaerobic fermentation in the pretreatment process of combined alkali, four factors and five levels of quadratic orthogonal rotary combination design experiment were used to optimize the technological conditions for biogas production from corn stalk anaerobic fermentation by combined alkali pretreatment, and corresponding mathematical model is established. The results showed that the regression equation was significant and the fitting condition was good. The four factors affected the biogas production of corn stalk in the order of composition ratio, treatment time, alkali concentration and solid-liquid ratio. The optimum combination of process parameters was as follows: alkali concentration was 6%, solid-liquid ratio was 1:5, treatment time was 4.5 days, component ratio was 1:1.25. Under the optimum conditions, the production of biogas from corn stalk anaerobic fermentation was the highest.

Optimization of biogas production through selection of appropriate Inoculum-to-Substrate ((I/S) ratio

The impact of Inoculum-to-Substrate (I/S) ratio on the optimization of biogas yield from the co-digestion of FW and MH was investigated in five anaerobic reactors B-1 to B-5 at 37±1oC. Cumulative biogas yield of digester B-3(28.92 L/gVS) with the I/S ratio 1 was higher than that of the other digesters. Simulation study through adoption of Gompertz model (modified) showed a large reduction in latency (λ) by 59.7% with increase in I/S ratio from 0.25 to 1, which indicates that the time taken for methanogenesis to begin was reduced by over 59%. Increase in I/S ratio had positive effects on maximum specific biogas production (Rm) and maximum biogas production potential (A) with reactor B-3 having the largest (Rm) and (A) values of 1.26 L/gVS/day and 29.58 L/gVS respectively. Lower I/S ratios of 0.25 and 0.5 were found to rather decrease biogas production. Biogas yield at I/S ratios 2 and 4 was lower than the yield at ratio 1.Keywords: Optimization, Inoculum-to-Substrate, Biogas, Gompertz modelling, Digester