Toward integrated crop and building simulation for controlled environment agriculture using EnergyPlus

• Integrates crop-level energy balance into EnergyPlus using its Python API. • Solves the crop-level energy balance using fixed-point iteration algorithm. • Estimates the hygrothermal loads of controlled environment agriculture spaces. • Validates the model against literature data, demonstrating improved applicability. This paper presents an approach for integrating crop modelling into building performance simulation (BPS) of controlled environment agriculture (CEA) spaces. A comprehensive review of recent literature on CEA energy modelling using building performance simulation (BPS) software highlighted the need for such integrated capabilities. Leveraging EnergyPlus and the Python application programming interface (API), the proposed approach estimates the hygrothermal (sensible and latent) loads within CEA spaces by applying a fixed-point iteration root-finding algorithm based on the crop-level energy balance. The implementation was verified using data from the literature, enhancing the applicability of BPS tools for simulating the unique environmental conditions of CEA spaces.