Abstract:
The world has witnessed significant demographic growth and environmental challenges,
prompting researchers to seek sustainable solutions to ensure food security and protect the
environment. To address these challenges, solar energy technologies have been adopted in
agricultural greenhouses, which are an important part of modern agriculture. Despite
advancements in greenhouse technology, improving the microclimate remains a challenge, as
this gap affects agricultural production, increases operational costs, and consumes more
energy.
This study aims to improve the heating system in semi-arid regions using a new latent heat
storage system, taking ventilation into account to enhance productivity. In this experiment, a
phase change material (PCM) was used to store heat during the day and release it at night. To
verify the effectiveness of the system, the obtained results were analyzed based on
temperature and relative humidity inside the greenhouse.
Additionally, the NARX (Nonlinear Autoregressive with Exogenous Inputs) algorithm
was employed within the predictive model. This algorithm relies on past values of the studied
variables and external inputs, allowing for capturing the precise temporal dynamics of the
microclimate inside the greenhouse. The results showed that this approach improves
prediction accuracy and supports better decision-making in agricultural energy management.
