How can mathematical models help in the biogas generation process?

ABSTRACT

Biogas has garnered increasing interest as a sustainable alternative to fossil fuels. However, due to the complexity of generating biogas, it is crucial to adopt adequate methodologies that aid planning, building, and running operations. Mathematical models have proven to be useful for assisting in the production of biogas, and they are applicable in different stages of the process. Therefore, the objective of this paper is to investigate how mathematical models can contribute to enhancing the efficiency and optimizing the biogas generation process. The Methodi Ordinatio methodology was used to conduct a systematic review of the literature. The VOSviewer software and the bibliometrix package in R were used to generate visual maps. The results revealed that mixed integer linear programming (MILP) models are the most common, accounting for 27% of the studies, followed by simulation models (SIM) with 14%, and hybrid models (HYB) and nonlinear programming models (NLP) in equal proportions, both at 13%. These models are useful for predicting and simulating biogas production. The analysis also revealed a significant trend toward integrating biogas production with the agricultural sector. Continuous advancements and applications of mathematical models are expected to increasingly facilitate biogas generation, thereby propelling global energy usage toward a sustainable energy source.

KEYWORDS:

• Biogas
• mathematical model
• systematic review
• bioenergy
• renewable energy

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15567036.2023.2298702.

Additional information

Funding

The authors thank to Brazilian foundation: PROPe/UNESP [Edital 13/2022], CAPES [Finance Code 001], CNPq [Grant number 306518/2022-8], and FAPESP [Grant number 2013/07375-0] for the financial support.

Notes on contributors

Jovani Taveira de Souza

Jovani Taveira de Souza is a postdoctoral researcher at Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP) and holds a Ph.D. and a master’s degree in Production Engineering from Universidade Tecnológica Federal do Paraná (UTFPR). He has published significant studies in international journals such as the Journal of Cleaner Production, IEEE Access, and Energy Reports.

Thalita Monteiro Obal

Thalita Monteiro Obal is Ph.D. in Numerical Methods from the Federal University of Paraná (UFPR) and is a professor at Universidade Tecnológica Federal do Paraná (UTFPR). She has published relevant studies in international journals such as Renewable Energy and IMA Journal of Management Mathematics.

Rodrigo Salvador

Rodrigo Salvador is Ph.D. in Production Engineering from Universidade Tecnológica Federal do Paraná (UTFPR) and is a professor at the Technical University of Denmark (DTU). He has published significant studies in international journals such as the Journal of Cleaner Production, Renewable and Sustainable Energy Reviews, and Waste Management.

Helenice de Oliveira Florentino

Helenice de Oliveira Florentino is Ph.D. in Electrical Engineering from the University of São Paulo (USP) and is a professor at Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP). She has published relevant studies in international journals such as Applied Mathematics & Information Sciences, Expert Systems with Applications, and Annals of Operations Research.