A Multi-objective Control Strategy Considering the Ambient and Controlled Air Conditions for Stored Grain Forced Air Ventilation Process

Abstract

Based on the principle of heat and mass transfer in stored grain aeration, a new multi-objective optimization strategy considering both the ambient and controlled air conditions was proposed. The control variables are inlet air temperature and humidity which also considered the ambient air conditions. A multi-objective optimization function was worked out with the inlet control variables and optimization objectives are the energy consumption, and grain temperature, moisture content. The proposed strategy was simulated with Matlab. The results showed that, with the proposed strategy, the grain moisture content and temperature can finally be controlled to safe aim values with optimized energy consumption.