Energy cost minimization in plant factories considering weather factors using additive Bayesian networks

ABSTRACTIn recent years, plant factories have been drawing attention for their capability to solve global food crisis. However, the energy cost of plant factories is high due to the power consumption of air conditioning and cultivation systems necessary for realizing semi-automatic production. As this high cost hinders their propagation,, plant factories must minimize the energy cost of growing plants. We propose an operation planning method of cultivation systems for minimizing energy cost minimization while producing plants with the same amount and quality. The effect of electricity charge and weather factors on electric power consumption under various real-world constraints are used to decide the appropriate operation plan of cultivation systems. Simulation results show that the operation plan of cultivation systems properly reflects the effect of electricity charge and weather factors on electric power consumption to reduce energy cost.