POWER OPTIMIZATION SYSTEM FOR AIR-SIDE APPARATUS OF AIR CONDITIONING AND POWER OPTIMIZATION METHOD OF THE SAME

• US 20170205101A1
• Filed: 08/09/2016
• Published: 07/20/2017
• Est. Priority Date: 01/19/2016
• Status: Active Grant

• Current Assignee: Delta Electronics Incorporated
• Original Assignee: Delta Electronics Incorporated
• Inventors: CHEN, Meng-Seng, LO, Tien-Szu
• Granted Patent: US 10,310,478 B2
• Time in Patent Office: Days
• CPC Class Codes: F24F 11/30 for purposes related to the operation of the system, e.g. for safety or monitoring
• CPC Class Codes: F24F 11/46 Improving electric energy efficiency or saving
• CPC Class Codes: F24F 11/62 characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
• CPC Class Codes: F24F 11/63 Electronic processing
• CPC Class Codes: F24F 2110/10 Temperature
• CPC Class Codes: F24F 2110/20 Humidity
• CPC Class Codes: F24F 2110/70 Carbon dioxide
• CPC Class Codes: F24F 2120/10 Occupancy
• CPC Class Codes: G05B 19/042 using digital processors G05B19/05 takes precedence
• CPC Class Codes: G05B 19/05 Programmable logic controllers, e.g. simulating logic interconnections of signals according to ladder diagrams or function charts
• CPC Class Codes: G05B 2219/2614 HVAC, heating, ventillation, climate control
• CPC Class Codes: G05B 2219/2639 Energy management, use maximum of cheap power, keep peak load low
• CPC Class Codes: Y02B 30/70 Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating

Abstract

A power optimization system including an optimization processing unit and a plurality of air conditioning'"'"'s air-side apparatuses is disclosed. The system obtains a target comfort value when people enter a zone, and calculates an improving demand for the zone'"'"'s indoor environment to approach the target comfort value. The system then collects an improving capacity of each air-side apparatus by operating in different working modes in the current indoor environment. After that, the optimization processing unit calculates multiple working combinations according to the improving demand and the improving capacities of the air-side apparatuses for the indoor environment to approach the target comfort value, and chooses a most power-saving working combination according to the basic power consumption of the air-side apparatuses.

Claims

1. A power optimization system for air-side apparatus of air conditioning, comprising:

an optimization processing unit, obtaining a first target comfort value of a first zone, and a first improving demand for an indoor environment of the first zone to approach the first target comfort value; and

a plurality of air-side apparatuses for executing an air exchanging operation in the first zone, each of the air-side apparatuses comprising a pre-cooling air handling unit (PAH) and a first fan coil unit (FCU), wherein the PAH and the first FCU record a first improving capacity that provides to the current indoor environment of the first zone and transmit the first improving capacity to the optimization processing unit;

wherein the optimization processing unit calculates a plurality of working combinations that assist the indoor environment of the first zone to approach the first target comfort value in a predicted time according to the first improving demand and the first improving capacity;

the optimization processing unit chooses a specific working combination that is the most power-saving one of the plurality of working combinations according to basic power consumption of the plurality of air-side apparatuses, and the optimization processing unit controls the PAH and the first FCU to respectively operate according to the specific working combination.

2. The power optimization system in claim 1, further comprising a plurality of sensors, which are arranged in the first zone and respectively sense a plurality of indoor environment parameters of the first zone, wherein the plurality of indoor environment parameters comprises indoor temperature, indoor humidity, indoor CO2 quantity and indoor person amount.

3. The power optimization system in claim 2, wherein the plurality of sensors comprises a human detector for detecting if a person enters the first zone, and the human detector triggers the optimization processing unit to obtain the first target comfort value when detecting the person enters the first zone.

4. The power optimization system in claim 2, wherein the first target comfort value comprises target temperature, target humidity and target CO2 quantity, the first improving demand is heat exchanging quantity and air exchanging quantity needed for assisting the indoor temperature, the indoor humidity and the indoor CO2 quantity to approach the target temperature, the target humidity and the target CO2 quantity, and the first improving capacity is the heat exchanging quantity and the air exchanging quantity that are provided in a time period by the PAH and the first FCU to the first zone when operating in each working mode.

5. The power optimization system in claim 4, further comprising:

a FCU controller, arranged in the first zone and connected to the first FCU, the FCU controller arranged to control the working modes of the first FCU;

a zone controller, arranged in the first zone and connected to the optimization processing unit and the FCU controller, the zone controller arranged to control the FCU controller; and

a programmable logic controller, connected to the optimization processing unit and the PAH.

6. The power optimization system in claim 5, wherein the FCU controller calculates the first improving demand according to the first target comfort value and the plurality of indoor environment parameters of the first zone, and also calculates the first improving capacity of the PAH and the first FCU, and transmits the first improving demand and the first improving capacity to the optimization processing unit.

7. The power optimization system in claim 6, wherein the FCU controller calculates the first improving capacity according to a plurality of improving factors, which comprises at least one of fan speed of the first FCU, valve on/off status of the first FCU, fan speed of the PAH, valve on/off status of the PAH, outdoor temperature, size of the first zone, indoor temperature, indoor humidity, indoor CO2 quantity, indoor person amount, current time, and environmental history data of the first zone.

8. The power optimization system in claim 4, wherein the plurality of air-side apparatuses further comprises a second FCU that executes the air exchanging operation for a second zone in cooperating with the PAH;

the optimization processing unit obtains a second target comfort value of the second zone when detecting a person enters the second zone, and also obtains a second improving demand for an indoor environment of the second zone to approach the second target comfort value.

9. The power optimization system in claim 8, wherein the PAH and the second FCU record a second improving capacity that provides to the current indoor environment of the second zone when operating in each working mode, the optimization processing unit re-calculates the plurality of working combinations for the indoor environment of both of the first zone and the second zone to approach the first target comfort value and the second target comfort value in the predicted time simultaneously according to the first improving demand, the first improving capacity, the second improving demand and the second improving capacity, and re-chooses the specific working combination according to the basic power consumption, and controls the PAH, the first FCU and the second FCU to respectively operate according to the re-chosen specific working combination.

10. A power optimization method for air-side apparatus of air conditioning, applied to a plurality of air-side apparatuses, each of the air-side apparatuses comprising a PAH and a first FCU used to execute an air exchanging operation for a first zone, the power optimization method comprising steps of:

a) calculating a first improving demand for an indoor environment of the first zone to approach a first target comfort value;

b) recording a first improving capacity that is provided by the PAH and the first FCU to the current indoor environment of the first zone when operating in each working mode;

c) transmitting the first improving demand and the first improving capacity to an optimization processing unit;

d) calculating a plurality of working combinations needed for assisting the indoor environment of the first zone to approach the first target comfort value in a predicted time according to the first improving demand and the first improving capacity by the optimization processing unit;

e) choosing a specific working combination that is the most power-saving one from the plurality of working combinations according to basic power consumption of the plurality of air-side apparatuses by the optimization processing unit; and

f) controlling the PAH and the first FCU to respectively operate according to the specific working combination by the optimization processing unit.

11. The power optimization method in claim 10, wherein before the step a, the power optimization method further comprises following steps of:

a01) detecting if a person enters the first zone; and

a02) triggering the optimization processing unit to obtain the first target comfort value when detecting the person enters the first zone.

12. The power optimization method in claim 10, wherein the first target comfort value comprises target temperature, target humidity and target CO2 quantity, and the step a further comprises following steps of:

a1) obtaining indoor temperature of the first zone;

a2) obtaining indoor humidity of the first zone;

a3) obtaining indoor CO2 quantity of the first zone; and

a4) calculating the first improving demand, wherein the first improving demand is heat exchanging quantity and air exchanging quantity needed for assisting the indoor temperature, the indoor humidity and the indoor CO2 quantity to approach the target temperature, the target humidity and the target CO2 quantity.

13. The power optimization method in claim 12, wherein the first improving capacity is heat exchanging quantity and air exchanging quantity that are provided in a time period by the PAH and the first FCU to the first zone when operating in each working mode.

14. The power optimization method in claim 13, wherein the step b is to calculate the first improving capacity according to a plurality of improving factors, and the plurality of improving factors comprises at least one of fan speed of the first FCU, valve on/off status of the first FCU, fan speed of the PAH, valve on/off status of the PAH, outdoor temperature, size of the first zone, indoor temperature, indoor humidity, indoor CO2 quantity, indoor person amount, current time and environmental history data of the first zone.

15. The power optimization method in claim 13, wherein the step b further comprises following steps of:

b1) testing average heat exchanging quantity and average air exchanging quantity that are provided by the first FCU to the current indoor environment of the first zone when operating in the current working mode to generate a testing data;

b2) changing working mode of the PAH and re-executing step b1 if not all working modes of the PAH are tested completely;

b3) determining whether all working modes of the first FCU are tested completely after all working modes of the PAH are tested completely;

b4) changing the working mode of the first FCU and re-executing step b1 to step b3 if not all working modes of the first FCU are tested completely;

b5) recording the plurality of testing data as the first improving capacity after all working modes of the first FCU are tested completely.

16. The power optimization method in claim 15, wherein the step b5 further comprises following steps of:

b51) obtaining an environmental history data of the first zone; and

b52) weighting the plurality of testing data and the environmental history data for generating the first improving capacity.

17. The power optimization method in claim 16, wherein the step b further comprises following steps of:

b6) determining whether a difference between the testing data and the environmental history data exceeds a threshold;

b7) issuing a warning message when the difference exceeds the threshold; and

b8) abandoning the first improving demand when the difference exceeds the threshold.

18. The power optimization method in claim 10, wherein the power optimization method further comprises following steps of:

g) determining whether receiving a second improving demand and a second improving capacity, wherein the second improving demand is used to assist indoor environment of the second zone to approach a second target comfort value, and the second improving capacity is heat exchanging quantity and air exchanging quantity that are provided in a time period by the PAH and a second FCU related to the second zone when operating in each working mode;

h) when receiving the second improving demand and the second improving capacity, re-calculating the plurality of working combinations that can assist the indoor environment of both of the first zone and the second zone to approach the first target comfort value and the second target comfort value in the predicted time simultaneously based on the first improving demand, the first improving capacity, the second improving demand and the second improving capacity; and

i) re-choosing the specific working combination according to the basic power consumption, and controlling the PAH, the first FCU and the second FCU to respectively operate according to the specific working combination.

19. The power optimization method in claim 18, wherein the optimization processing unit obtains the second target comfort value, the second improving demand and the second improving capacity whenever a person enters the second zone.

20. The power optimization method in claim 18, wherein the power optimization method further comprises a step j of:

determining whether the first improving demand or the first improving capacity changes;

wherein the step h is to re-calculate the plurality of working combination when the first improving demand or the first improving capacity changes, or when receiving the second improving demand and the second improving capacity.