System dynamics kinetic model for predicting biogas production in anaerobic condition: Preliminary assessment

Abstract

Introduction: This preliminary assessment of a grey-box model, was predicated on system dynamics principles and developed using Vensim® DSS software. The purpose is to predict biogas production under anaerobic conditions for energy utilization at the design stage. Objective: To describe the process of a developed system dynamics model to predict biogas production under anaerobic conditions. Methods: This method involves two-stage kinetics of the biogas production process in anaerobic conditions using the first-order and Gompertz functions. The model is depicted in two parts: causal loop diagram and stock–flow diagram. The causal loop diagram describes the anaerobic digestion process a substrate undergoes for the production of biogas, while stock–flow diagram depicts basic building blocks of the dynamic behavior of an anaerobic digestion process. Primary data is from a laboratory-scale experiment of biogas production using vegetal wastes, while the secondary one is from the literature on studies using similar substrates. Results: Primary and secondary data are used to validate and stimulate the developed model. The kinetic model shows the substrate being reduced exponentially with increasing time; consumption of substrate and production of methane and carbon dioxide follows exponential growth and decay pattern, with carbon dioxide production starting early compared to methane, and was produced at a rate faster due to the strong and resilient characteristics of fermentative microorganisms. Discussion: Comparing data from empirical and model simulation shows some close relationship, though not too perfectly. Both results reflect signs of inhibitions occurring within the substrates in the digester under anaerobic conditions explaining the low methane yield or instability.

Energy Recovery Potential from Effluents in the Process Industry: System Dynamics Modeling and Techno-Economic Assessments

“…The processes are described using two causal loop diagrams for biogas production and energy recovery potential for CHP use. Figure 1 shows the causal loop diagram (CLD) for biogas production process showing our understanding of the AD process that effluents undergo for biogas production, while Figure 2 is the adapted CLD [26] for energy recovery potential from the biogas produced from the effluents generated in the processes of the three F&B industry types. Specific materials of interest are cassava used in making cassava flakes or garri, millet/sorghum adjuvants used in breweries that serve as malted grain in place of barley for beer production, and sugar cane refined to sugar.…”

“…This stock and flow (or level and rate) diagram (SFD), represents the structure of the 2-module biogas energy recovery model for CHP purposes. The model is adapted from [26], and then coupled to the energy recovery potential to the biogas production module. SFD is the most common first step in building a simulation model showing a more detailed information for the system than the causal loop diagram.…”

Energy Recovery Potential from Effluents in the Process Industry: System Dynamics Modeling and Techno-Economic Assessments

“…This stock and flow (or level and rate) diagram (SFD) represents the structure of the 2-module biogas energy recovery model for CHP purposes. The model is adapted from [31] and is then coupled to the energy recovery Fuels 2022, 3 632 potential of the biogas production module (details of the model documentation are given in the Supplementary Materials). SFD is the most common first step in building a simulation model, showing more detailed information for the system than the causal loop diagram [32].…”

The development of input-monitoring system on biofuel economics and social welfare analysis

“…Equations ( 11) and ( 12) are conditions for optimal commodity consumption. Equation (11) shows that consumers consume products up to the marginal value of the product (the shadow price, in this case). Equation ( 12) is the complementary condition.…”

“…8 Therefore, the energy shortage can only come from renewable energy sources 9 and some advanced artificial intelligence applications that immediate point out the stability of biomass supply might be used to improve the production strategy. 10,11 Taiwan is a small island situated between 21.7˚ and 25.5˚ northern latitude with approximately a total area of 36,000 km 2 . The total cultivated land before 2005 was about 0.83 million hectares (ha) or 23% of the territory.…”