Hussain Maham, Ali Omer, Raza Nadeem, Zabiri Haslinda, Ahmed Ashfaq, Ali Imtiaz
Department of Chemical Engineering, NFC Institute of Engineering & Technology Multan Pakistan
Department of Electrical Engineering, NFC Institute of Engineering & Technology Multan Pakistan.
RSC Adv. 2023 Aug 8;13(34):23796-23811. doi: 10.1039/d3ra01219k. eCollection 2023 Aug 4.
The conversion of biomass through thermochemical processes has emerged as a promising approach to meet the demand for alternative renewable fuels. However, these processes are complex, labor-intensive, and time-consuming. To optimize the performance and productivity of these processes, modeling strategies have been developed, with steady-state modeling being the most commonly used approach. However, for precision in biomass gasification, dynamic modeling and control are necessary. Despite efforts to improve modeling accuracy, deviations between experimental and modeling results remain significant due to the steady-state condition assumption. This paper emphasizes the importance of using Aspen Plus® to conduct dynamics and control studies of biomass gasification processes using different feedstocks. As Aspen Plus® is comprising of its Aspen Dynamics environment which provides a valuable tool that can capture the complex interactions between factors that influence gasification performance. It has been widely used in various sectors to simulate chemical processes. This review examines the steady-state and dynamic modeling and control investigations of the gasification process using Aspen Plus®. The software enables the development of dynamic and steady-state models for the gasification process and facilitates the optimization of process parameters by simulating various scenarios. Furthermore, this paper highlights the importance of different control strategies employed in biomass gasification, utilizing various models and software, including the limited review available on model predictive controller, a multivariable MIMO controller.
通过热化学过程将生物质转化已成为满足对替代可再生燃料需求的一种有前景的方法。然而，这些过程复杂、劳动强度大且耗时。为了优化这些过程的性能和生产率，已开发出建模策略，稳态建模是最常用的方法。然而，对于生物质气化的精确性而言，动态建模和控制是必要的。尽管努力提高建模精度，但由于稳态条件假设，实验结果与建模结果之间的偏差仍然很大。本文强调使用Aspen Plus®对使用不同原料的生物质气化过程进行动力学和控制研究的重要性。由于Aspen Plus®包含其Aspen Dynamics环境，该环境提供了一个有价值的工具，可以捕捉影响气化性能的因素之间的复杂相互作用。它已在各个领域广泛用于模拟化学过程。本综述考察了使用Aspen Plus®对气化过程进行的稳态和动态建模及控制研究。该软件能够开发气化过程的动态和稳态模型，并通过模拟各种情况促进过程参数的优化。此外，本文强调了生物质气化中采用的不同控制策略的重要性，利用了各种模型和软件，包括关于模型预测控制器（一种多变量MIMO控制器）的有限综述。
