Drying Plant Management Based on Exergy Criterion and Regression Methods

Abstract

Today, energy-saving issues are relevant. Drying of materials in various industries of the fuel and energy complex is one of the energy-intensive technologies. The literature review showed that the proposed measures to improve drying plants’ efficiency are mainly technological. To improve the drying plants’ operation, we propose an approach using regression methods and control algorithms based on them. It is relevant to apply the exergy balance. Since the calculation of exergy balance is complex and time-consuming, we propose building a simplified model based on it. To obtain a mathematical description of a drying unit, we use models based on the equations of mass balance and exergy. A diagram of a spray closed-type drying unit is given. We provide a model of a drying plant based on exergy balance. The results of calculating the exergy of fuel gas, thermomechanical exergy of combustion products, and exergy for moisture evaporation were obtained. The proposed methodology consists of a sequence of steps: calculating material and thermal balances, calculating the exergy balance, providing a training sample based on a balance model, constructing a simplified regression relationship between input and output parameters, optimizing the model taking into account restrictions on quality indicators, and developing control algorithms for the drying plant. The selected methods allow completing the above steps. To derive the regression dependence, we use a rotatable central compositional plan. An optimization criterion is the exergy efficiency of a gas furnace and a drying chamber. We obtained the regression dependence of the exergy efficiency of the drying chamber on the temperature of the drying agent at the inlet, the humidity of the incoming slurry, and the fuel gas consumption. The coefficient of determination is 0,96, indicating that the model adequately fits the original data. A block diagram of the drying unit control is given, taking into account the selected control and disturbing parameters. The proposed method can be used to determine the optimal control parameters of the drying unit. Further research may be aimed at the details and programmatic implementation of this technique.