Energy-optimal control decisions for systems

• US 8,924,026 B2
• Filed: 08/22/2011
• Issued: 12/30/2014
• Est. Priority Date: 08/20/2010
• Status: Active Grant

• Current Assignee: Vigilent Corporation
• Original Assignee: Vigilent Corporation
• Inventors: Federspiel, Clifford C., Chin, Jerry
• Primary Examiner(s): JARRETT, RYAN A
• Application Number:
  US13/215,189
• Publication Number:
  US 20120101648A1
• Time in Patent Office: 1,226 Days
• Field of Search: None
• US Class Current: 700/276
• 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 11/58 using Internet communication
• 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 11/77 by controlling the speed of ventilators
• CPC Class Codes: G05B 13/026 using a predictor
• CPC Class Codes: G05D 23/1934 each space being provided with one sensor acting on one or more control means
• CPC Class Codes: H05K 7/1498 Resource management, Optimisation arrangements, e.g. configuration, identification, tracking, physical location thermal management H05K7/20836
• CPC Class Codes: H05K 7/20836 Thermal management, e.g. server temperature control

Abstract

Methods, systems, and apparatuses are provided for controlling an environmental maintenance system that includes a plurality of sensors and a plurality of actuators. The operation levels of the actuators can be determined by optimizing a penalty function. As part of the penalty function, the sensor values can be compared to reference values. The optimized values of the operation levels can account for energy use of actuators at various operation levels and predicted differences of the sensor values relative to the reference values at various operation levels. The predicted difference can be determined using a transfer model. An accuracy of the transfer model can be determined by comparing predicted values to measured values. This accuracy can be used in determining new operational levels from an output of the transfer model (e.g., attenuating the output of the transfer model based on the accuracy).

Claims

1. A method of controlling an environmental maintenance system that includes a plurality of actuators and a plurality of sensors, each sensor measuring a value of a physical condition of an environment, the method comprising:

receiving sensor values S corresponding to the sensors;

determining a potential change dU to operation levels U of the actuators;

calculating, with a computer system, a first contribution to a penalty function by;

applying a transfer model to dU to determine a predicted change dS in the sensor values S, the transfer model providing a relation between changing an operation level of an actuator and resulting changes in sensor values;

determining new sensor values S_New from the predicted change dS; and

using S_New to determine the first contribution to the penalty function, the first contribution being based on a relationship of each new sensor value relative to one or more respective setpoint values;

calculating, with the computer system, a second contribution to the penalty function by;

determining new operation levels U_new, corresponding to the potential change dU to the operation levels U;

for each new operation level, determining a cost of operating the corresponding actuator with the new operation level; and

aggregating the costs to obtain the second contribution;

determining a first value of the penalty function based on the first and second contributions for the potential change dU;

determining an optimal change to the operation levels U of the actuators based on values of the penalty functions for a plurality of potential changes to the operation levels U; and

setting the operation levels of the actuators based on the optimal change.

2. The method of claim 1, wherein setting the operation levels of the actuators based on the optimal change includes:

adjusting the optimal change; and

adding the adjusted optimal change to U.

3. The method of claim 2, wherein adjusting the optimal change includes at least one of normalization, randomization, and scaling.

4. The method of claim 2, further comprising:

determining an accuracy of the transfer model by comparing predicted sensor value with measured sensor values, wherein the optimal change is adjusted based on an accuracy of the transfer model.

5. The method of claim 1, wherein setting the operation levels of the actuators based on the optimal change includes:

receiving new settings for the actuators; and

adjusting the new settings based on the optimal change.

6. The method of claim 5, further comprising:

calculating the new settings using a PID object, wherein the PID object provides new settings based on;

a comparison of a midpoint of the sensor values to a midpoint reference, or

a comparison of an extremum of the sensor values to an extremum reference.

7. The method of claim 1, wherein a maximum number of potential changes to the operation levels U are analyzed to determine the optimal change, and wherein the optimal change is selected from the plurality of potential changes if at least one of the corresponding potential changes has a value for the penalty function that is less than the penalty function with no change to U.

8. The method of claim 1, wherein the cost of operating an actuator with a new operation level includes at least one of an energy cost and a maintenance cost.

9. The method of claim 8, wherein the cost of operating the actuator includes:

receiving a cost per rate of energy usage; and

inputting the cost per rate of energy usage and the new operation level into a function that outputs the cost of operating the corresponding actuator.

10. The method of claim 1, wherein using S_New to determine the first contribution includes:

for each sensor;

inputting S_New into a respective function that has at least one setpoint of the sensor as a parameter to obtain an output of a partial first contribution; and

summing the partial first contributions from the sensors.

11. The method of claim 10, wherein a respective function includes:

taking a difference between the corresponding new sensor value S_New and a setpoint; and

multiplying the difference by a gain factor to obtain the partial contribution for the sensor.

12. The method of claim 1, wherein determining a potential change dU to operation levels U of the actuators is accomplished by receiving the new operation levels U_new, where U_new=U+dU, and wherein applying a transfer model to dU to determine a predicted change dS in the sensor values S is accomplished by applying the transfer model to the potential new value for U.

13. The method of claim 1, wherein determining a potential change dU to operation levels U of the actuators uses an optimization algorithm that incorporates past potential changes to determine the current potential change.

14. The method of claim 1, wherein the setpoint values include a range of sensor values.

15. The method of claim 1, wherein the transfer model is a matrix of numerical values.

16. A computer product comprising a non-transitory computer readable medium storing a plurality of instructions that when executed control a computer system to control an environmental maintenance system that includes a plurality of actuators and a plurality of sensors, each sensor measuring a value of a physical condition of an environment, the instructions comprising:

receiving sensor values S corresponding to the sensors;

determining a potential change dU to operation levels U of the actuators;

calculating a first contribution to a penalty function by;

applying a transfer model to dU to determine a predicted change dS in the sensor values S, the transfer model providing a relation between changing an operation level of an actuator and resulting changes in sensor values;

determining new sensor values S_New from the predicted change dS; and

using S_New to determine the first contribution to the penalty function, the first contribution being based on a relationship of each new sensor value relative to one or more respective setpoint values;

calculating a second contribution to the penalty function by;

determining new operation levels U_new corresponding to the potential change dU to the operation levels U;

for each new operation level, determining a cost of operating the corresponding actuator with the new operation level; and

aggregating the costs to obtain the second contribution;

determining a first value of the penalty function based on the first and second contributions for the potential change dU;

determining an optimal change to the operation levels U of the actuators based on values of the penalty functions for a plurality of potential changes to the operation levels U; and

setting the operation levels of the actuators based on the optimal change.

17. The computer product of claim 16, wherein setting the operation levels of the actuators based on the optimal change includes:

adjusting the optimal change; and

adding the adjusted optimal change to U.

18. The computer product of claim 17, wherein the instructions further comprise:

determining an accuracy of the transfer model by comparing predicted sensor value with measured sensor values, wherein the optimal change is adjusted based on an accuracy of the transfer model.

19. The computer product of claim 16, wherein setting the operation levels of the actuators based on the optimal change includes:

receiving new settings for the actuators;

adjusting the new settings based on the optimal change; and

calculating the new settings using a PID object, wherein the PID object provides new settings based on;

a comparison of a midpoint of the sensor values to a midpoint reference, or

a comparison of an extremum of the sensor values to an extremum reference.

20. The computer product of claim 16, wherein a maximum number of potential changes to the operation levels U are analyzed to determine the optimal change, and wherein the optimal change is selected from the plurality of potential changes if at least one of the corresponding potential changes has a value for the penalty function that is less than the penalty function with no change to U.

21. The computer product of claim 16, wherein using S_New to determine the first contribution includes:

for each sensor;

inputting S_New into a respective function that has at least one setpoint of the sensor as a parameter to obtain an output of a partial first contribution; and

summing the partial first contributions from the sensors.

22. The computer product of claim 16, wherein determining a potential change dU to operation levels U of the actuators is accomplished by receiving the new operation levels U_new, where U_new=U+dU, and wherein applying a transfer model to dU to determine a predicted change dS in the sensor values S is accomplished by applying the transfer model to the potential new value for U.

23. An environmental maintenance system comprising:

a plurality of actuators;

a plurality of sensors, each sensor measuring a value of a physical condition of an environment; and

one or more processors configured to;

receive sensor values S corresponding to the sensors;

determine a potential change dU to operation levels U of the actuators;

calculate a first contribution to a penalty function by;

applying a transfer model to dU to determine a predicted change dS in the sensor values S, the transfer model providing a relation between changing an operation level of an actuator and resulting changes in sensor values;

determining new sensor values S_New from the predicted change dS;

using S_New to determine the first contribution to the penalty function, the first contribution being based on a relationship of each new sensor value relative to one or more respective setpoint values;

calculate a second contribution to the penalty function by;

determining new operation levels U_new, corresponding to the potential change dU to the operation levels U;

for each new operation level, determining a cost of operating the corresponding actuator with the new operation level;

aggregating the costs to obtain the second contribution;

determine a first value of the penalty function based on the first and second contributions for the potential change dU;

determine an optimal change to the operation levels U of the actuators based on values of the penalty functions for a plurality of potential changes to the operation levels U; and

set the operation levels of the actuators based on the optimal change.

24. The system of claim 23, wherein setting the operation levels of the actuators based on the optimal change includes:

adjusting the optimal change; and

adding the adjusted optimal change to U.

25. The system of claim 24, wherein the one or more processors are further configured to:

determine an accuracy of the transfer model by comparing predicted sensor value with measured sensor values, wherein the optimal change is adjusted based on an accuracy of the transfer model.

26. The system of claim 23, wherein setting the operation levels of the actuators based on the optimal change includes:

receiving new settings for the actuators;

adjusting the new settings based on the optimal change; and

calculating the new settings using a PID object, wherein the PID object provides new settings based on;

a comparison of a midpoint of the sensor values to a midpoint reference, or

a comparison of an extremum of the sensor values to an extremum reference.

27. The system of claim 23, wherein a maximum number of potential changes to the operation levels U are analyzed to determine the optimal change, and wherein the optimal change is selected from the plurality of potential changes if at least one of the corresponding potential changes has a value for the penalty function that is less than the penalty function with no change to U.

28. The system of claim 23, wherein using S_New to determine the first contribution includes:

for each sensor;

inputting S_New into a respective function that has at least one setpoint of the sensor as a parameter to obtain an output of a partial first contribution; and

summing the partial first contributions from the sensors.

29. The system of claim 23, wherein determining a potential change dU to operation levels U of the actuators is accomplished by receiving the new operation levels U_new, where U_new=U+dU, and wherein applying a transfer model to dU to determine a predicted change dS in the sensor values S is accomplished by applying the transfer model to the potential new value for U.