Forecast of Energy Consumption of Drying System According to The Environmental Temperature and Humidity on IoT by Arima Algorithm

Abstract

The hot air recirculating drying method has the advantage of handling large output. Moreover, in the drying chamber with a large volume of drying material, factors affecting the drying process such as air flow rate, temperature, drying agent humidity, and surface area of the drying product are always concerned. Because this is the deciding factor for the drying time as well as the quality of the drying product. However, the drying time is closely related to the energy consumed in the drying system. In particular, the temperature and humidity of the environment have a great influence on energy consumption. This paper has built a general mathematical model, using ARIMA algorithm to predict energy consumption for the industrial drying system and applying the mathematical model to actually survey the drying system with a capacity of 1000 kg /batch, 03 drying chambers are designed with a size of 3000mm. x 3000mm x 2500 (length x width x height), total drying tray area 192 m2. Energy sources use thermal oil furnace technology or resistive furnaces. The collected temperature and humidity data is based on the IoT platform. The simulation results forecast the temperature accurately to 99.09%, the humidity is accurate to 98.24% and the energy consumption reaches 96.31%.