(untitled) (ОБРАЗОВАНИЕ НАУКА И ИННОВАЦИОННЫЕ ИДЕИ В МИРЕ, 2026)
This paper presents a comprehensive methodology for optimizing the microclimate— specifically the coupled temperature and humidity regime—within solar greenhouses (geliogreenhouses) operating under variable climatic conditions. Solar greenhouses represent a sustainable pathway toward energy-efficient agriculture; however, their performance is inherently bound to diurnal fluctuations of solar radiation, resulting in extreme overheating during the day and critical chilling at night, alongside excessive relative humidity (RH) that triggers fungal pathogens. This research develops a unified mathematical model and an engineering framework combining Phase Change Material (PCM) thermal energy storage, automated multi-stage ventilation, and localized desiccant dehumidification. The microclimate parameters were simulated using Computational Fluid Dynamics (FD) and validated against experimental data collected from an autonomous solar greenhouse. The results indicate that the proposed optimization method reduces nocturnal heating energy consumption by 42.5%, limits daytime peak temperatures by 6.8°C, and maintains relative humidity within the optimal 65–75% range for vegetable crops. The findings demonstrate that dynamic, integrated control of latent and sensible heat fluxes can maximize agricultural yield while eliminating reliance on fossil-fuel-based auxiliary heating systems.