System and method for optimizing cooling efficiency of a data center

Patent metadata

Field	Value
Publication number	US-10721845-B2
Application number	US-201415027134-A
Country	US
Kind code	B2
Filing date	Sep 30, 2014
Priority date	Oct 4, 2013
Publication date	Jul 21, 2020
Grant date	Jul 21, 2020

Abstract

Disclosed is a system and method for optimizing cooling efficiency of a data center is disclosed. The system may comprise an importing module, a Computational fluid dynamics (CFD) modeling module, a scope determination module, a metrics computation module, an identification module and a recommendation module. The importing module may be configured to import data associated to the data center. The CFD modeling module may be configured to leverage an external CFD Analysis tool in order to develop a CFD model of the data center. The scope determination module may be configured to determine a scope for optimizing the cooling efficiency of the data center. The metrics computation module may be configured to compute metrics based upon the data. The identification module may be configured to identify inefficiency and a cause producing the inefficiency. The recommendation module may be configured to facilitate optimizing cooling efficiency of the data center.

First claim

What is claimed is:

1. A method for optimizing cooling efficiency of a data center, the method comprising:
importing data comprising a design parameter of the data center and an operational parameter of the data center;
developing, via a processor, a Computational fluid dynamics (CFD) model of the data center based upon the data, wherein the CFD model is developed using CFD analysis tool capable of performing CFD calculations based upon the information retrieved from the imported data for various scenarios generated based upon various combinations within the data;
computing, via the processor, a first set of metrics for the data center based upon the data and the CFD model, wherein computing the first set of metrics comprises:
dividing the data center into a plurality of sections, wherein each of the plurality of sections comprises an aisle; and
computing the first set of metrics for each of the plurality of sections based upon the data and the CFD model, wherein the first set of metrics include leakage area in the data center, maximum temperature of racks in the data center, power consumed by equipment in the data center, plenum blockage, flow rate of tiles, maximum and minimum values of set points of cooling equipment, ratio of cooling capacity of the data center and heat generated in the data center and an average ambient temperature;
comparing via a processor the first set of metrics with reference metrics, where cooling efficiency optimization has been performed, wherein the comparison provides a match set of reference data centers, and wherein ranges of achievable values for the first set of metrics is derived based on after-optimization values of the reference metrics of the match set of the reference data centers, wherein the reference metrics are associated with a reference data center;

determining, via the processor, a scope for optimizing the cooling efficiency of the data center based upon the comparison of the first set of metrics with the reference metrics, wherein the scope is determined in terms of energy savings in the cooling of the data center;
computing, via the processor, a second set of metrics based upon the operational parameter;
comparing via a processor the second set of metrics with threshold values of the data center;
identifying inefficiency associated with current state of the data center based upon the comparing of the second set of metrics with the threshold values and geometrical criteria of the data center;
determining a cause producing the inefficiency, wherein the cause is determined based upon the data and the inefficiency;
recommending, via a processor, based on the inefficiency and the cause, wherein the recommendation is indicative of suggesting a gradual change in at least one of the design parameter of the data center and the operational parameter of the data center;
displaying the recommendation report and the layout of the data center, wherein at least one section of the layout visually indicates the inefficiency identified; and
facilitating optimizing cooling efficiency of the data center based upon the recommendation.

2. The method of claim 1 , wherein the data comprises information on layout of the data center, information on equipment of the data center, information regarding racking practices in the data center, power consumption by the equipment of the data center, operational parameters of the equipment, temperature and air velocity at various locations of the data center, ambient temperature outside the data center, electricity cost per unit, location of the data center, and combinations thereof.

3. The method of claim 1 , wherein the reference data center indicates another data center having previously undergone the method of claim 1 for optimizing the cooling efficiency.

4. The method of claim 1 , wherein the second set of metrics comprises at least one of a rack inlet temperature, a tile temperature, rack threshold temperature and a combination thereof, and wherein the rack inlet temperature is associated with a rack, and wherein the tile temperature is associated with a tile placed around the rack, and the rack threshold temperature is associated with safe operation of equipment inside rack.

5. The method of claim 1 , wherein the gradual change is feasible to be implemented easily and at a low cost.

6. The method of claim 1 further comprising a step of generating a recommendation report, wherein the recommendation report comprises the inefficiency, the cause, the recommendation, and the scope for optimizing the cooling efficiency of the data center.

7. The method of claim 1 wherein the recommendation report is displayed on an user interface configured to depict the inefficiency and the recommendation corresponding to the inefficiency simultaneously.

8. A system for optimizing cooling efficiency of a data center, the system comprising:
a processor; and
a memory coupled to the processor, wherein the processor is capable of executing a plurality of modules stored in the memory, and wherein the plurality of modules comprising:
an importing module configured to import data comprising a design parameter of the data center and an operational parameter of the data center;
a CFD modeling module configured to leverage a CFD analysis tool in order to develop a Computational fluid dynamics (CFD) model of the data center based upon the data, wherein the CFD model is developed using CFD analysis tool capable of performing CFD calculations based upon the information retrieved from the imported data for various scenarios generated based upon various combinations within the data;
a metrics computation module configured to compute:
a first set of metrics for the data center based upon the data and the CFD model, wherein computing the first set of metrics comprises:
dividing the data center into a plurality of sections, wherein each of the plurality of sections comprises an aisle; and
computing the first set of metrics for each of the plurality of sections based upon the data and the CFD model, wherein the first set of metrics include leakage area in the data center, maximum temperature of racks in the data center, power consumed by equipment in the data center, plenum blockage, flow rate of tiles, maximum and minimum values of set points of cooling equipment, ratio of cooling capacity of the data center and heat generated in the data center and an average ambient temperature, and

a second set of metrics based upon the operational parameter;
a scope determination module configured to:
compare the first set of metrics with reference metrics, where cooling efficiency optimization has been performed, wherein the comparison provides a match set of reference data centers, and wherein ranges of achievable values for the first set of metrics is derived based on after-optimization values of the reference metrics of the match set of the reference data centers, wherein the reference metrics are associated with a reference data center; and
determine a scope for optimizing the cooling efficiency of the data center based upon the comparison of the first set of metrics with the reference metrics, wherein the scope is determined in terms of energy savings in the cooling of the data center;

an identification module configured to:
compare the second set of metrics with threshold values of the data center;
identify inefficiency associated with a current state of the data center based upon the comparing of the second set of metrics with the threshold values and geometrical criteria of the data center, and
determine a cause producing the inefficiency, wherein the cause is determined based upon the data and the inefficiency; and

a recommendation module configured to:
a recommendation module configured to pr

Assignees

• Tata Consultancy Services Ltd

Inventors

• Bhagwat Harshad Girish
• Singh Umesh
• D Sankara Narayanan
• Varghese Arun
• Singh Amarendra Kumar
• Jayaprakash Rajesh
• Sivasubramaniam Anand

Classifications

• G06F30/20

  Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) · CPC title

• H05K7/20745

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

• G06F2111/10

  Numerical modelling · CPC title

• H05K7/20836 Primary

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

• G06F1/20

  Cooling means · CPC title