Information technology and smart grid

1. Information
Technology
&
Smart Grid
Energy Efficient Information
Technology
Heather Brotherton

2. 2
What is Information
Technology (IT)?
 Information




+ Technology
Technology: fire, wheel
Early information technology: Dewy
decimal system
Information collections continue to expand
Compiling data into information became
exponentially labor intensive

3. 3
Information Systems
 Information
systems make it possible to
process large amounts of data into
information
 Now that we have good information how
do we quickly share research findings?
 Networking; the internet

4. 4
Ubiquitous Communication
 The
internet gave rise to ubiquitous realtime communications




Anyone can transmit:
Files
Photos
Video
 We
use the internet to connect with
others

5. 5
Convenience
 Bank
by phone
 Turn by turn directions
 Researching purchases
 Home buying
 Meal planning
 Home automation
 Smart Grid

6. 6
Smart Grid: House Concept

7. 7
End User Implementation

8. 8

9. 9
Smart Grid & IT
 Information
technology and the
power grid are interdependent


2003 North East Blackout
The extent and duration of the
outage was due to a race
condition in the SCADA system

10. 10
Smart Grid & IT
 Smart


Grid expands this interdependence
However it also enhances the reliability and
redundancy of the SCADA systems
More situations are automated to avoid
human error

11. 11
Data Centers & Smart Grid
 Can
coordinate energy consumption
during


Low periods
Periods where a high percentage of
renewable energy such as wind or solar is
available

12. 12
What types of IT processes
could take advantage of this?
 Batch
jobs such as running
 Reports
 Back ups
 Scheduled maintenance

13. 13
Big Data Problem
 All
of these integrated systems will create
vast amounts of data


This data will be used for modeling to make
real time decisions
This data will depend upon information
systems infrastructure to maintain; creating
additional IT processing and archive loads.

14. 14
What’s the big deal storage
space is cheap?
 Not
really
 Hard
drive usage must be powered
 Additional load for backups
 Can be a huge deal in a virtualized
environment


Memory usage is also decreased by 34%
Multiply that by 100 in a virtual environment, the
resource savings is huge

15. 15
Storage Problem
 Vast
amounts of data some will be used in
real-time situational analysis to allow
Independent Systems Operators to make
operational decisions.


Past data may not be accessed daily, but
will need to be readily available for
generation of reports to make strategic
decisions
Accessibility to large amounts of data
creates substantial energy overhead

16. 16
Energy Efficient Data Storage
 Hard
Disk Drive (HDD) vs. Solid State Drives
(SDD)


HDD
 Uses 80% of maximum power draw at start-up
SDD
 Linear proportion usage to power relationship
 This
means that any HDD active, but running
at under 80% utilization is wasting energy.

17. 17
Energy Efficient Data Storage
 So
is the answer to use all solid state
drives?

That is one possible answer, but it is currently
an expensive answer.
 Other

possibilities:
Storage consolidation
 Virtualization
is one possible method of
achieving this goal
 Shared storage arrays are another

18. 18
Storage Problem

Increased use of
technologies such
as memcached for
frequently
accessed data



This technique uses RAM
caching
Used in conjunction with
compression this can be
very useful for
transactional loads
Hybrid SDD/HDD
storage systems
managed
intelligently

19. 19
Data Center Power
consumption
 In
2005 data center power usage was 1%
of the worlds power consumption.

The current power usage is estimated to be as
high as 1.5% world wide and up to 2.2% of US
power consumption.

20. 20
Data Center Power
consumption
 Why



should you care?
Every year there are rolling blackouts though
the summer because utilities cannot keep up
with demand.
Energy costs are higher than equipment costs.
Loss of electricity or computing capabilities can
pose national security risks

21. 21
Efficiency Basics
 Power
Usage Effectiveness (PUE)
developed by the Green Grid is a widely
accepted measure of data center
efficiency.
 PUE Calculation
Total data center energy consumption
IT energy consumption=PUE

22. 22
PUE explained
A
PUE of one means that all energy
consumptions is being used by the
servers, storage devices and networking
equipment.


Reaching one is the goal, but may not be
possible currently…
However, Google has reached reach a Power
Usage Effectiveness (PUE) of 1.16.

23. 23
There is a better way…
According to Google “if all data
centers operated at the same
efficiency as ours, the U.S. alone
would save enough electricity to
power every household within the
city limits of Atlanta, Los Angeles,
Chicago, and Washington, D.C.”

24. 24
Google


Google tracks its PUE
Data centers are run at 80 degree Fahrenheit
or more




This “conforms with both the American Society of
Heating, Refrigerating, and Air Conditioning Engineers'
recommendations and most IT equipment
manufacturers' specs.”
Data centers can be cooled without chillers
Remaining chillers have disabled “dehumidifying and
reheating functions on CRACs. Most are set to
dehumidify air to 40% and reheat air if the return air is too
cold, but these functions aren’t needed.”
Each data center element is designed to
operate at optimal efficiency

25. 25
Google: How did they do it?

Power Supply



The average power supply converts power from
AC to DC accounting for 30 to 40% in power
loss.
This process also produces heat
Google power supplies do not perform this
costly conversion and have an integrated
UPS.

“We’ve also cut out 2 of the AC / DC
conversion stages by putting back-up batteries
on the server racks themselves.”

26. 26
Google: Custom Servers
 Parts
are omitted “on servers that aren't
needed for our applications. Hardware is
limited to what is necessary for the
applications to run, and does not include
unnecessary components such as
peripheral connectors or video cards. We
also optimize our servers and racks to use
minimal fan power, and the fans are
controlled to spin only as fast as necessary
to keep the server temperature below a
threshold.”

27. 27
Cascade Effect

28. 28
Facebook
 Facebook
recently adopted a novel
power distribution design that
removes uninterruptible power supply
(UPS) and power distribution units (PDUs)
from the data center.
 The
new design shifts the UPS and battery
backup functions from the data center
by adding 12 volt battery cabinets
 Facebook’s
datacenter has a PUE of 1.07

29. 29
Role of Software
 ”(T)he
only way to have software
consume zero resources is not to run it at
all. Even running very well-behaved
software at the minimum will, in
practice, require some resource overhead.”







Virtualization
Power Management
Node Management
Scheduling
Lean Operating systems
Software development
De-duplication

30. 30
Virtualization
 Virtualization
is useful for consolidation of
under utilized servers


DO: consolidate servers that typically have
usage under 70%
DO NOT: consolidate servers that have
usage higher than 90%
 Unless
the server resources are more than
enough to cover usage patterns including the
other virtualized servers consolidated into the
new server
 WARNING:
Consolidating several high
usage servers on one server may be a
recipe for disaster.

31. 31
Virtualization
 Remember:
Virtualization can lead to the
need to rework cooling in the data
center.
 Fewer machines could lead to
unnecessary cooling of space no longer
occupied by servers. This could result in
wasted cooling.

32. 32
Lean Operating systems
 Graphical
efficient



1 watt can be saved at the server level
though using a command line only server
operating system
The overhead of the GUI is about 100
threads
This does not mean no Windows server OS
 Windows

User Interfaces (GUI) are not
server 2008 R2 Core
Uses less disk space
 Standard
7.5 GB
 Core 3.5 GB

33. 33
Software Development
 CPU



UTILIZATION
Write event-triggered not time-based checks
Use batch processing for processes that cannot
be event based
Make sure batch jobs can be adjusted for time
conflicts
 MEMORY


UTILIZATION
Avoid memory leaks
Release memory when it is no longer
needed, don’t wait for the system to do it foru
you.

34. 34
Software Development
 I/O

UTILIZATION
Buffer/batch I/O requests
 EFFICIENT


SYSTEM STACK
“Features to reduce power consumption of
underutilized system resources have become
pervasive in even the largest systems, and the
software layers responsible for managing those
resources must evolve in turn”
Implement policies:
 Increase performance of resources in use
 Reduce power consumption for resources not
in use

35. 35
Software Development
(Continued)

“Resource consumers clearly have a significant
opportunity either to contribute to or undermine
the efficiency of the broader stack. Though
getting programmers to think differently about the
way they design software is more than a technical
problem, tools such as PowerTOP represent a
great first step by providing programmers and
administrators with observability into software
inefficiency, a point of reference for
optimization, and awareness of the important role
software plays in energy-efficient computing."

36. 36
Hardware
 What
is better one really powerful server
of several low powered servers?
 Answer:
It depends.
 Many low powered servers are ideal for
transactional loads
 Powerful servers are better for simulation and
computation

37. 37
Conclusion
 "Any
intelligent fool can make things
bigger, more complex, and more violent.
It takes a touch of genius -- and a lot of
courage -- to move in the opposite
direction.” ~Albert Einstein
 In
IT this kind of thinking results in huge
payoffs when implemented correctly.