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

Figures & data

Figure 1. Schematic image of a plant factory.

Figure 2. Power consumption of a cultivation system.

Figure 3. Relationship of three variables.

Table 1. Variables investigated in the experiment.

		Description
Weather factors	$Temp$	Difference between outside temperature and indoor setting temperature
	$Hum$	Humidity
Internal environment	v3	Flow rate of nutrient circulation
	v4	EC of the nutrient circulation tank
	v5	pH of the nutrient circulation tank
	v6	Conserved enzyme of nutrient circulation
	v7	Indoor CO2
	v8	Temperature of the cultivation room
	v9	Humidity of the cultivation room
	v10	Temperature of the nutrient solution room
	v11	CO2 flow rate
	v12	Water level of the nutrient solution tank
	v13	Water amount of nutrient solution
	v14	Room temperature of the cultivation room
	v15	Temperature of the takeout room
Power consumption factors	$Ip$	Internal control panel 200V power consumption
	$Sp$	Servo motor power consumption
	$Ep$	External control panel 200V power consumption
	$Cp$	Chiller unit power consumption
	$ACp$	Power supply AC 100V power consumption

Figure 4. Result of light period.

Figure 5. Result of dark period.

Figure 6. Electricity price.

Figure 7. Average power consumption of a cultivation system.

Table 2. Relative power consumption and cost.

	Maximum power consumption [%]	Cost [%]
Uniform plan	100.00	100.00
Plan discounting weather factors	100.32	98.91
Plan based on the proposed method	100.00	98.87

Figure 8. Number of cultivation systems starting at each time slot.

Figure 9. Power consumption of derived pattern and weather factors.