CFD Modeling of the Microclimate in a Greenhouse Using a Rock Bed Thermal Storage Heating System

Abstract

The rock bed heating system is a more cost-effective concept for storing thermal energy use in greenhouses at night during the cold winter season. This system is considered an environmentally friendly solution compared to conventional heating systems that rely on fossil fuels. Despite the abundance of research on thermal energy-based heating systems, only limited work on climate modeling in greenhouses using rock bed heat storage systems has been reported. To fill this research gap, this study aims to simulate the microclimate in a greenhouse equipped with a rock bed heating system using computational fluid dynamics (CFD) models. User-defined functions have been implemented to account for the interactions between the plants and the air within the greenhouse. Crop rows and rock bed blocks have been considered as porous media with their dynamic and thermal proprieties. The model’s accuracy was approved by comparing simulated and experimental climate parameter data from the greenhouse. The model’s ability to predict temperature, humidity, and air velocity fields in the greenhouse as well as in the rock bed system during both phases of energy storage and restitution was demonstrated. The thermal, dynamic, and hygric fields were accurately replicated with this numerical model. The growing zone had a vertical temperature gradient between the ground and the greenhouse roof, as well as high humidity. The distribution of temperature fields along the rock bed blocks showed a significant temperature gradient between the air inlet and outlet in the blocks during the two phases of heat storage and restitution. As a result, the model could be useful for sensitivity studies to improve the performance of this thermal storage heating system.

Parametric Analysis of a Radiant Gas Heating System for Controlled-Environment Agriculture with Preheated Ventilation

“…The choice of artificial heating methods for buildings and structures is only part of the energy conservation solution [9,13,[17][18][19][20][21][22]. In conjunction with this, there is a need for optimal architectural and planning solutions [15,[23][24][25][26][27][28], and the implementation of modern innovative technologies aimed at reducing the consumption of non-renewable fuel and energy resources [24,[29][30][31][32][33]. Therefore, within the context of addressing this problem, research on the impact of various factors on the energy balance of cultivation structures is required, consequently affecting the thermal regime of the premises and the calculated power of the adopted heating system.…”

Prediction of Greenhouse Indoor Air Temperature Using Artificial Intelligence (AI) Combined with Sensitivity Analysis

“…The basis for all these research studies is the initial modeling of the greenhouse conditions based on external variables such as temperature, humidity, wind speed, radiation level, etc. [16][17][18].…”