Smart energy is a trending concept in a field crowded with competing and complementary terms, technologies, and approaches – but has the business case yet been made? Andy Lawrence will share his views on where this technology segment is headed.

1. Smart Energy in the data center
Andy Lawrence, Executive Director of Research,
Uptime Institute
March 2019

2. Smart Energy in
the data center:
About Today’s
Webinar
• The aspiration and the technologies
• Products and services to watch
• Drivers and barriers to deployment
• Conclusions
• Questions and discussion
Andy Lawrence
Executive Director of Research,
Uptime Institute

3. The aspiration

4. 4Company Confidential
Towards the automated datacenter

5. 5Company Confidential
Automation in the data center
Main example/capability
IT Provisioning, orchestration, load management
Network Optimization, route selection, security, dynamic bandwidth allocation,
traffic prioritization,
DC management Maintenance, faults, staff, resource, capacity management, planning,
optimization
Energy Smart Energy, Dynamic power capping, load balancing, demand
response, Software defined power
Cooling Optimization, right sizing, mode change, efficiency management

6. 6Company Confidential
Automation in the data center – Adoption/maturity
Adoption
IT High to very high
Network Moderate to high
DC management Low to moderate
Energy Very low to Low
Cooling Low

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Smart Energy at a glance
 Smart Energy systems use intelligence and data to make decisions about the
production, storage, distribution and use of energy.
 The goal of Smart Energy is usually to improve efficiency, resiliency, or flexibility.
 Smart Energy systems are most effective when driving actions in real time, using
automated controls.

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Main applications of Smart Energy in the Data center
Intelligent IT
power
management
Transactive
energy
Data center
energy
optimization

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Intelligent IT power management: Low demand…
 Power capping, power management, and workload shifting
are rarely used, tactical.
 IT Energy management is isolated from infrastructure IT
management.
 Innovative products left on shelf.
 IT energy management is rarely linked to workload
management/orchestration.
 IT decision making is (mostly) unconcerned with energy use.
 Main savings are from Moore’s Law, VMs and containers and
embedded, invisible power management

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Transactive energy: Slowly gaining traction?
 Data center participates in a wider “smart grid”, helping
to balance grid demand/supply.
 Usually achieved by agreement, supported by manual
processes.
 Usually achieved by running generators, but can/could
use stored UPS power, fuel cells, or reduced IT
demand.
 Emerging products apply cloud based analytics, and
analyze data center loads.
 Take-up held back by risk aversion, poor returns, and
generator costs.

11. Data center energy optimization: High potential?
11
• Number of energy management products:
• Monitor energy use throughout the data center
• Provide centralized repository and management
• Provide a basis for (usually separate) action
• Emerging adaptable power/software defined
products:
• Allocate/switch power based on policy,
conditions, forecasts.
• Increase power availability by using battery
storage, reducing redundancy.
• Interact with IT systems to move/change IT loads
based on policy, conditions, thresholds.

12. 12Company Confidential
Smart Energy Enabler: Li-Ion batteries*
• Over half of the market is adopting or
planning to adopt Lithium-Ion in the next
two years.**
• 11-15% of clients deploying some form of
Li-Ion at scale.**
• Centralized UPS applications lead the way
over distributed approaches.
• Largest organizations lead the adoption
curve.
* Or similar/alternative non-LA batteries.
**Uptime Institute Survey March 2018 – (200 data center design engineers)
Tesla Power pack deployment, Australia

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Smart Energy Enabler: Software Defined architectures
• Control is directly programmable.
Directly
programmable
• Control is abstracted, enabling administrators to dynamically
adjust systems to meet changing needs.Agile
• Intelligence is (logically) centralized in software-based controllers
that maintain a global view of the network.Centrally managed
• Managers configure, manage, secure, and optimize resources very
quickly. Programs do not depend on proprietary software.
Programmatically
configured
• Design and operation is simplified because abstracted instructions
do not use vendor-specific protocols.
Open standards-based
and vendor-neutral

14. Some emerging products to watch…

15. VPS and Software Defined power (Distributed)
• Li Ion batteries in rack or row (OCP compatible)
• Each battery set has a local controller
• Power is “pooled” and managed as a central
resource
• Batteries can be turned on/off according to policy
• Loads can be shifted according to battery state
• Racks can be allocated more power according to
policy
Source: Virtual Power
Systems

16. Smart energy and peak load management
16
0
20
40
60
80
100
2:00
AM
4:00
AM
6:00
AM
8:00
AM
10:00
AM
12:00
PM
2:00
PM
4:00
PM
6:00
PM
8:00
PM
10:00
PM
12:00
AM
Power use (MW)
% Utilisation
Power cap or move load?
A big opportunity:
Build data center to this level
When load goes above
the red line, smart
energy techniques
improve the availability
of power for key loads,
and others are
moved/capped

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Energy as a service (transactive energy)
 Next generation UPS’s balance grid demands with
onsite use of capacity
 Cloud based service manages “arbitrage” of power
under safe conditions.
 Systems constantly monitor UPS and on site
equipment.
 System defaults to safest mode if conditions are less
than optimal.
 Could work with shared reserve/software defined
power.
Source: Vertiv/Upside Energy

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Shared Reserve power…
• Traditional 2N and 2N + 1
designs are being enhanced
with more STS, software and
switching.
• Reserve power is distributed
and allocated where it is
needed.
• Software and policy based
systems determine how
capacity is used.
Source: Vertiv

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Adaptable Redundant Power (i3)
 Adaptable Redundant Power:
 Puts redundancy levels under software control
 Utilizes existing centralized UPSs
 Uses transfer switches to ‘reallocate’ capacity
 Makes use of inherent redundant power
 Developed by i3 solutions
 Uses control system/software
 Best if UPS incorporates firmware
 Better if suppliers build in A/B switching

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N+2 or N+1? A bit of both….
 Shared reserve/Software Defined power enables
flexible allocation of redundancy/capacity.
 Extra or unused capacity can be allocated to blocks
or applications – or taken away.
 Entire data center does not have fail at once.
 The Tier level depends on capacity and on
design/points of failure and proven onsite
performance.
What is the level of redundant power
equipment in your data center?
Source: Uptime Institute Research, Annual Survey 2018

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Product outlier: Software Defined Electricity
 Real time electronic devices sample electricity 50,000x
per second.
 26 different power characteristics measured 8000 times
per phase.
 Performs real time “noise cancellation’ from a distributed
supplemental power supplies.
 Actions, parameters and policies under software control.
Digitizing Electricity?
Real time power
correction may
dramatically improve
efficiency, equipment
life.

22. Drivers and barriers to adoption

23. Capacity forecasting is operators’ top challenge
Which of the following do you believe is the single largest challenge for the majority
of your customers? (Choose one)
Source: Uptime Institute Research 2018, n = 264

24. Hardwarechoices push capacitylimitsfor some
Areanyofyourorganization'shardwaredeployment choices strainingyourcapacity inyourowneddatacenters?
(Select allthatapply)
Source: Uptime InstituteIntelligence Capacity SurveyQ4 2018
n=185
31%
28%
6%
22%
50%
Power density
Cooling
Weight
Network
Noneof the above

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Reallocatingpower capacityon-demand isdifficult…
How would you rate your organization’s ability to reallocate
power capacity on-demand to meet workload changes/surges?
32%
13%
33%
32%
Source: Uptime Institute Intelligence/VPS 2018

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Coloscould use the freed up power…
If you were able to recapture 20% to 40% of stranded power & be able to
resell it (with no reduction in resiliency), what would you most likely do?
(choose one)
Source: Uptime Institute Intelligence/VPS 2018

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Would your organization be willing to adopt software to automatically manage power usage in the data hall
to lower power costs & to reduce risk from human error?
High interest insoftwareto lowerpower costs& risk
Source: Uptime Institute Intelligence/VPS 2018
7%
74%
18%

28. 28Company Confidential
Enterprises prioritizeredundancy over loadshedding
Would your organization consider load shedding – gracefully & automatically
shutting down non-critical workloads or shifting them to another data
center/public cloud – if it meant being able to use fewer redundant electrical
systems in the data centers you use?
39%
61%
Source: Uptime Institute Intelligence/VPS 2018

29. Microgrids andSDP: not likely, not soon, not impactful?
Source : Uptime Institute Intelligence/451 Research Disrupted data center study 2018

30. Conclusions….

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What needs to happen
Supplier support and open standards.
Proof of concurrent maintainability is essential.
Any reduction in resiliency must be transparent, specific and save money.
Early adopters, market validation and cases studies are needed.
Clear definition of use cases and benefits

32. Two For The Road
• Automation andsoftware willbe widely used to manage to balance
supply/demand for data center power/energy.
• Safe, justifiable business cases for deployment are yet to be widely
proven.
AndyLawrence,ExecutiveDirector,Research,UptimeInstitute
alawrence@uptimeinstitute.com

33. 33Company Confidential
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