From plant to fuel: Advances in modeling, simulation, and optimization strategies for biofuel production

Abstract

Biofuel production from biofuel plants has become a viable substitute for fossil fuels, potentially addressing issues related to the environment, economy, and energy security. This comprehensive review paper explores the myriad modeling and simulation techniques employed in the biofuel production process from biofuel plants. With a focus on enhancing efficiency, sustainability, and economic viability, researchers have increasingly turned to computational approaches to optimize various stages of biofuel production. The review begins by outlining the different physicochemical and biochemical properties of biofuels, the fundamental principles underlying biofuel production from biofuel plants, and highlighting the significance of biomass feedstock selection, pretreatment methods, and downstream processing. It then delves into the diverse modeling and simulation techniques utilized across these stages, ranging from the design of experiments, agent-based modeling, and simulation, including artificial intelligence and machine learning approaches, along with their strengths, limitations, and applications, which are critically evaluated, providing insights into their suitability for addressing specific challenges in biofuel production. By providing a comprehensive outline and directions in modeling and simulation techniques for biofuel production, the review improves our understanding of maximizing biofuel production and plant selection for biofuels. By harnessing the power of computational tools, researchers can accelerate the development of sustainable biofuel technologies and pave the way toward a greener energy future. © 2026 Elsevier Ltd. All rights reserved.