System and methods for simulation-based optimization of data center cooling equipment

Patent metadata

Field	Value
Publication number	US-2016234972-A1
Application number	US-201615017771-A
Country	US
Kind code	A1
Filing date	Feb 8, 2016
Priority date	Feb 9, 2015
Publication date	Aug 11, 2016
Grant date	—

Abstract

Aspects of this disclosure are directed to a simulation-based cooling optimization method that provides real-time cooling set points in a data center. The method combines airflow and temperature simulation, energy modeling, and an optimization solver to determine optimal cooling set point values for a data center. Other aspects are also directed to estimating power consumption and cost and energy savings.

First claim

What is claimed is:

1 . A method for optimizing cooling power consumption in a data center including a plurality of racks and at least one cooling unit, the method comprising:
receiving information regarding the data center, including a layout of the plurality of racks and the at least one cooling unit within the data center; determining an initial power consumption value for the data center by implementing an energy model; predicting at least one of a temperature value and an airflow rate value by implementing a numerical simulation model; determining at least one optimal cooling set point value for the at least one cooler using an optimization solver based on the initial power consumption value and the at least one predicted value, the optimization solver minimizing a power consumption value of a power consumption function while maintaining at least one constraint associated with operation of the at least one cooling unit; and controlling operation of the at least one cooling unit using the at least one optimal cooling set point value.

2 . The method of claim 1 , further comprising defining the at least one constraint, wherein the at least one constraint comprises maximum and minimum airflow rate values for the at least one cooler, maximum and minimum supply temperature values for the at least one cooler, and a maximum inlet temperature for each rack of the plurality of racks.

3 . The method of claim 2 , wherein the optimization solver iteratively determines the at least one optimized cooling set point until a stopping condition is met by iteratively varying one or more inputs received by at least one of the energy model and the numerical simulation model.

4 . The method of claim 3 , further comprising reducing a number of iterations by averaging at least one input received by at least one of the energy model and the numerical simulation model.

5 . The method of claim 3 , further comprising:
dividing a representation of the data center into a computational grid comprising a plurality of grid cells; determining an inlet temperature value for at least one grid cell of the plurality of grid cells, wherein the inlet temperature value is associated with an inlet temperature of at least one rack of the plurality of racks.

6 . The method of claim 5 , further comprising:
determining a lowest value for an inlet temperature value for the plurality of racks in each iteration; averaging the lowest value associated with each iteration over the number of iterations to determine an average minimum inlet temperature for the plurality of racks; determining a highest value for an inlet temperature for the plurality of racks in each iteration; and averaging the highest value associated with each iteration over the number of iterations to determine an average maximum inlet temperature for the plurality of racks, wherein the at least one constraint includes the average minimum inlet temperature for the plurality of racks and the constraint associated with the maximum inlet temperature for each rack is replaced by the average maximum inlet temperature for the plurality of racks.

7 . The method of claim 6 , further comprising calculating an airflow velocity value and a temperature value for at least one grid cell, wherein the inlet temperature value is based on the airflow velocity value and the temperature value.

8 . The method of claim 7 , wherein the airflow velocity value and the temperature value are calculated using a potential flow method.

9 . The method of claim 3 , wherein the received information includes at least one real-time measurement value including at least one of rack power, rack airflow, cooler airflow, supply temperature of a cooler, and an outside temperature value, and the one or more inputs includes the at least one real-time measurement value.

10 . The method of claim 3 , further comprising statistically tuning at least one of the energy model and the numerical simulation model.

11 . The method of claim 1 , wherein implementing the numerical simulation model includes generating a regression model, the regression model based at least in part on at least one operating parameter of the data center, including a total load of the plurality of racks, an air ratio, and a supply temperature of the at least one cooler.

12 . The method of claim 11 , wherein the regression model is generated using a least square regression technique.

13 . A system for optimizing cooling power consumption in a data center including a plurality of racks and at least one cooling unit, the system comprising:
at least one input configured to receive information regarding the data center, including a layout of the plurality of racks and the at least one cooling unit within the data center; a programmable device in communication with the at least one input, the programmable device comprising:
a memory for storing the received information;
at least one processor coupled to the memory and configured to:
determine an initial power consumption value for the data center by implementing an energy model;
predict at least one of a temperature value and an airflow rate value by implementing a numerical simulation model;
determine at least one optimal cooling set point value for the at least one cooler using an optimization solver based on the initial power consumption value and the at least one predicted value, the optimization solver minimizing a power consumption value of a power consumption function while maintaining at least one constraint associated with operation of the at least one cooling unit; and
control operation of the at least one cooling unit using the at least one optimal cooling set point value.

14 . The system of claim 13 , wherein the at least one constraint comprises maximum and minimum airflow rate values for the at least one cooler, maximum and minimum supply temperature values for the at least one cooler, and a maximum inlet temperature for each rack of the plurality of racks.

15 . The system of claim 14 , wherein the at least one processor is configured to use the optimization solver by iteratively determining the at least one optimized cooling set point until a stopping condition is met by iteratively varying one or more inputs used by at least one of the energy model and the numerical simulation model.

16 . The system of claim 15 , wherein the at least one processor is configured to:
divide a representation of the data center into a computational grid comprising a plurality of grid cells; determine an inlet temperature value for at least one grid cell of the plurality of grid cells, wherein the inlet temperature value is associated with an inlet temperature of at least one rack of the plurality of racks.

17 . The system of claim 16 , wherein the at least one processor is configured to:
determine a lowest value for an inlet temperature value for the plurality of racks in each iteration; average the lowest value associated with each iteration over the number of iterations to determine an average minimum inlet temperature for the plurality of racks; determine a highest value for an inlet temperature for the plurality of racks in each iteration; and average the highest value associated with each iteration over the number of iterations to determine an average maximum inlet temperature for the plurality of racks, wherein the at least one constraint includes the average minimum inlet temperature for the plurality of racks and the constraint associated with the maximum inlet temperature for each rack is replaced by the average maximum in

Assignees

• Schneider Electric It Corp

Inventors

• Billet Laurent
• Healey Christopher M
• Bergerand Jean-Louis
• Le Pape-Gardeux Claude
• Vangilder James William

Classifications

• H05K7/20745

  within rooms for removing heat from cabinets, e.g. by air conditioning device · CPC title

• H05K7/20836 Primary

  Thermal management, e.g. server temperature control · CPC title

• G05B13/041

  in which a variable is automatically adjusted to optimise the performance · CPC title