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<p>This paper presents the development of a temperature model, based on the energy balance of a semi-continuous reactor consisting of 3 stainless steel digesters of 6L each, operating at temperatures from 25 to 75&#xa0;°C, with stirrer, gas sampling points and pH and temperature control panels; in addition, the reactors depend on the ambient temperature and the input power. This model is intended to predict the thermal behaviour of the reactor. The variables that are not independent are estimated from three methods, the method of least squares with a static model, the method of least squares with a dynamic model and the method of nonlinear least squares with dynamic model and additional delay, the last one presents a new dynamic with respect to the original model. For the estimation of variables and subsequent comparison between methods, data were taken from the reactor in operation for 4&#xa0;days. As a result, it was possible to estimate the reactor temperature with a maximum error of approximately one degree Celsius, where it is obtained that the best model is the least squares method with a static model. This pilot-scale work generates contributions to the challenge of improving energy efficiency in biogas production models, or value-added products such as volatile fatty acids, through Anaerobic Digestion (AD) considering that this is one of the conditions to be evaluated in industrial scale-up processes.</p>

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Adaptation of a Temperature Model for Semi Continuous Anaerobic Digestion Reactor

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月21日

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  • Gracia Jeniffer,
  • Montenegro Carlos,
  • Gaona-García Paulo,
  • Rodríguez Francisco

摘要

This paper presents the development of a temperature model, based on the energy balance of a semi-continuous reactor consisting of 3 stainless steel digesters of 6L each, operating at temperatures from 25 to 75 °C, with stirrer, gas sampling points and pH and temperature control panels; in addition, the reactors depend on the ambient temperature and the input power. This model is intended to predict the thermal behaviour of the reactor. The variables that are not independent are estimated from three methods, the method of least squares with a static model, the method of least squares with a dynamic model and the method of nonlinear least squares with dynamic model and additional delay, the last one presents a new dynamic with respect to the original model. For the estimation of variables and subsequent comparison between methods, data were taken from the reactor in operation for 4 days. As a result, it was possible to estimate the reactor temperature with a maximum error of approximately one degree Celsius, where it is obtained that the best model is the least squares method with a static model. This pilot-scale work generates contributions to the challenge of improving energy efficiency in biogas production models, or value-added products such as volatile fatty acids, through Anaerobic Digestion (AD) considering that this is one of the conditions to be evaluated in industrial scale-up processes.