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AbstractGlobal energy demand is experiencing a notable surge due to growing energy security. Renewable energy sources, like ethanol, are becoming more viable. In the present study, the application of a PSO-PID (Particle Swarm Optimization – Proportional Integral Derivative) controller with a split-range control strategy was suggested for the regulation of temperature within the fermentation system. To optimize performance, a POS-PID controller with a split-range arrangement utilizing two control valves for hot and cold utilities was constructed. The study began by examining the open-loop dynamic response of the system to inlet temperature and concentration disturbances during ethanol production fermentation. Subsequently, a transfer function model was developed through linearization at the steady-state operating point. The split-range controller structure, implemented by optimizing the PSO-PID controller parameters using PSO, effectively demonstrated temperature control in simulations of a nonlinear model. In this investigation, the ethanol fermentation system was modeled as a CSTR using a modified Monod equation for microbial growth kinetics. Various dynamic behavioral disturbances were explored and verified in the model with plant data in this study. The simulation model results were validated through plant data. The proposed method showed superior closed-loop performance with respect to errors, with the actuators proving to be effective than other reported methods for temperature control. [ABSTRACT FROM AUTHOR]

Growing demand for renewable and sustainable energy sources has prompted research into bioethanol production as a viable alternative to hydrocarbon fuel for automobile engines. Based on their high carbohydrate content, Chlorella vulgaris microalgae were chosen for this study as a feasible biomass for bioethanol synthesis. After conducting microwave-based acid hydrolysis with varying acid concentrations of sulfuric acid (H2SO4) for 1–15 min, this study found that 3% H2SO4 for 5 min yielded the highest yield of reducing sugar (6.77 g/L). In this work, the RSM approach of central composite design (CCD) was utilized for modeling and optimization of ethanol fermentation and the MATLAB Simulink approach was employed for the simulation of ethanol fermentation. This study compared the effects of using Saccharomyces cerevisiae yeast for fermentation at different fermentation times (12 to 48 h), temperatures (28 to 32°C), and size of inoculum (0.5–1.5 g/L). Based on the actual and predicted results, the best conditions for fermentation were 36 h of time, 30°C of temperature, and 1.5 g/L of inoculum size. This gave the maximum ethanol concentration of 3.31 g/L. Furthermore, the RSM method provides minimum error and maximum R² value results for ethanol production compared to MATLAB simulation prediction (MSP). In addition, residue biomass from biofuel production is evaluated for its suitability for a further form of biofuel production. This research explores the opportunities for zero-waste biomass utilization in the development of biofuels. [ABSTRACT FROM AUTHOR]