Optimization of Watering for Minimizing the Inside Temperature of Zero Energy Cool Chamber for Storing Fruits and Vegetables

Abstract

Abstract A zero energy cool chamber (ZECC) has been developed for storing fruits and vegetables from the viewpoints of low installation and operating cost. The inside temperature of the ZECC is cooled by adding water to a sand and zeolite based filler between the brick walls based on the principles of a natural evaporative cooling mechanism. The objective of this study was to minimize the inside temperature of the ZECC by controlling watering operation using an intelligent optimization technique combined with neural network and genetic algorithm. The objective function was given by the average value of the inside temperature for one day. For optimization, the control process (24 hours) was divided into 8 steps, and the optimal value (8-step ON-OFF intervals) of watering was obtained using neural networks and genetic algorithms. In this method, dynamic changes in the inside temperature of the ZECC, as affected by the watering strategy and outside temperature, were first identified using neural network, and then the optimal value, which minimized the objective function, was determined through simulation of the identified neural-network model using genetic algorithm. The average inside temperature for this optimal ON-OFF control was 5°C lower than that for the simple ON-OFF watering for 24 hours, and was also 8°C lower than that for no watering. The ZECC with the optimal ON-OFF watering strategy extended the shelf-life of untreated tomato from 7 to 16 days. Thus, it was concluded that a ZECC optimized by using neural networks and genetic algorithms is useful for storing tomato with no electric energy.