RESUMO
Anaerobic digestion (AD) is widely adopted for remediating diverse organic wastes with simultaneous production of renewable energy and nutrient-rich digestate. AD process, however, suffers from instability, thereby adversely affecting biogas production. There have been significant efforts in developing strategies to control the AD process to maintain process stability and predict AD performance. Among these strategies, machine learning (ML) has gained significant interest in recent years in AD process optimization, prediction of uncertain parameters, detection of perturbations, and real-time monitoring. ML uses inductive inference to generalize correlations between input and output data, subsequently used to make informed decisions in new circumstances. This review aims to critically examine ML as applied to the AD process and provides an in-depth assessment of important algorithms (ANN, ANFIS, SVM, RF, GA, and PSO) and their applications in AD modeling. The review also outlines some challenges and perspectives of ML, and highlights future research directions.
Assuntos
Reatores Biológicos , Metano , Anaerobiose , Biocombustíveis , Aprendizado de MáquinaRESUMO
The present study aims to evaluate the operating costs of biodiesel production using palm oil in a pilot-scale plant with a capacity of 20,000 L/day (850 L/batch). The production plant uses crude palm oil as a feedstock, and methanol in a molar ratio of 1:10. The process incorporated acid esterification, basic transesterification, and dry washing with absorbent powder. Production costs considered in the analysis were feedstock, supplies, labor, electricity, quality and maintenance; amounting to $3.75/gal ($0.99/L) for 2013. Feedstocks required for biodiesel production were among the highest costs, namely 72.6% of total production cost. Process efficiency to convert fatty acids to biodiesel was over 99% and generated a profit of $1.08/gal (i.e., >22% of the total income). According to sensitivity analyses, it is more economically viable for biodiesel production processes to use crude palm oil as a feedstock and take advantage of the byproducts such as glycerine and fertilizers.