Microalgae are considered a promising feedstock for biorefineries given that their chemical composition – rich in carbohydrate and lipid - can be directed towards the co-production of various value-added fuels and chemicals. Production of microalgal biomass for biorefinery purposes requires the identification and establishment of optimal cultivation systems, a crucial yet complicated task due to the numerous factors (e.g. media composition, light, temperature) that simultaneously regulate biomass growth and intracellular composition. Modelling these biological processes, taking into account a single or multiple growth-limiting factors, offers a valuable tool to simulate, design and optimise the dynamics of microalgae cultivation. This review provides an overview of existing models developed to describe microalgal growth processes at the macroscopic scale (also termed black-box models) and discusses their formulation in detail. The black-box kinetic modelling frameworks are compiled into single-factor (6 formulations) and multiple-factor (32 formulations - further divided into non-interactive, additive, and interactive) growth kinetic models, as reported in more than 80 studies, for the prediction of biomass growth as a function of major operational factors such as media composition (e.g. nutrient concentration) and environmental factors (e.g. transient light and temperature). In addition, the review focuses on those models that further account for the production dynamics of two microalgal intracellular products with renowned potential as biorefinery substrates: carbohydrate and lipid molecules. Models of microalgal cultivation dynamics offer a robust engineering tool to understand the natural yet complex responses of microalgae to their growing environment and can help - if used appropriately - to optimise microalgae cultivation and increase the economic viability and sustainability of microalgal systems.

微藻被认为是生物精炼厂的有前途的原料，因为它们的化学成分（富含碳水化合物和脂质）可以用于多种增值燃料和化学品的联产。用于生物精炼目的的微藻生物质的生产需要确定和建立最佳的培养系统，这是一项至关重要的任务，但由于同时调节生物质生长和细胞内组成的众多因素（例如培养基组成，光照，温度）而变得十分复杂。考虑到单个或多个生长限制因素，对这些生物过程进行建模可提供一种有价值的工具，可以模拟，设计和优化微藻培养的动力学。黑盒子模型），并详细讨论其公式化。黑匣子动力学建模框架被编译为单因素（6种配方）和多因素（32种配方-进一步分为非交互，加性和交互）生长动力学模型，据80多项研究报道，根据主要操作因素（例如培养基组成（例如营养物浓度）和环境因素（例如瞬时光和温度））预测生物量的增长。此外，本综述着重于那些模型，这些模型进一步说明了两种微藻细胞内产品的生产动态，这些产品具有作为生物精炼底物而闻名的潜力：碳水化合物和脂质分子。