Leveraging the Internet of Things and Analytics for Smart Energy Management

Business Process Services
White Paper
Leveraging the Internet of Things and Analytics
for Smart Energy Management

About the Author
Akhil Bhardwaj
Akhil Bhardwaj is a Senior Manager in the Analytics and Insights division of Tata
Consultancy Services' (TCS) Business Process Services (BPS) unit. He has over 11 years of
experience in providing innovative solutions for a range of analytical problems across
domains such as banking, supply chain, retail, and marketing. He is currently working on
driving technological transformation in product based analytics. Bhardwaj graduated
from the Indian Institute of Technology, Bombay and Xavier Labor Relations Institute,
Jamshedpur.

Abstract
The rising cost of energy is causing organizations to evaluate smart ways of saving
energy. Energy suppliers are increasingly penalizing organizations that use
inefficient assets or devices with a low power factor. Simultaneously, governments
are raising the bar for compliance with energy standards and reduction in carbon
footprints. Smart energy management systems (EMS), combined with the Internet
of Things (IoT), provide the ideal solution for these pressing challenges by
supporting radical changes in the way energy consumption is monitored and
managed.
This paper examines how the combined power of the IoT and energy management
systems can revolutionize energy management. It illustrates how these systems
leverage information collected through different devices to automatically control
operational parameters and minimize energy consumption across buildings or
campuses. The paper also highlights the role of analytics in optimizing energy
management by helping organizations make holistic sense of the large volumes of
data gathered by various devices.

Contents
The Need for Energy Management 5
Planning for Efficient Energy Management 5
Exploring the Possibilities: Internet of Things and Analytics 6
Making Sense of Data 7
Controlling operational parameters of chillers 7
Optimizing lighting 8
Realizing Holistic Benefits through Analytics 9
Future Outlook: Revolutionizing Energy Management with IoT 10

The Need for Energy Management
Effective energy management is an increasingly critical focus area for utilities and energy service
providers, as well as end-customers. Energy consumption needs to be minimized without compromising
on comfort and other ergonomic considerations such as appropriate humidity, fresh air, carbon dioxide
levels, and so on. An efficient energy management system helps optimize energy consumption for
heating, ventilation, air conditioning, refrigeration, lighting, fire systems, and security systems, ensuring
that energy is used only when needed.
An advanced energy management system can ensure monitoring of building conditions, equipment
status, utility sub-metering, climatic data, and demand limiting that includes load scheduling and duty
cycling. Such a system can also focus on maintenance (remote operation and control of equipment,
generation of maintenance schedules, and diagnosis of breakdowns), and record generation
(modification or replacement analysis, energy conservation documentation).
Planning for Efficient Energy Management
Many enterprises are now developing different hardware, software, and analytical solutions for energy
management. Effective planning serves as the foundation for this exercise. Planning for a building energy
management system starts with the layout of the building. Based upon the floor space area, the cooling
or heating capacity needs to be determined; this should be greater than the expected maximum
requirement for a given area and set of environmental conditions. This might require installation of
multiple chillers with separate piping plans.
Another important factor to be considered is that certain chillers might have lower procurement costs
but higher operational costs due to lower efficiency. Typically, higher efficiency chillers are associated
with a higher procurement cost but a lower operational cost. If the business decides to install higher
efficiency chillers, they will need to consider the breakeven tenure involved.
For lighting, the aim is to leverage as much natural light as possible. This can be hampered by factors such
as reflection glare of neighboring buildings. High floor space can also prevent the utilization of natural
light. In such a case, the type of lighting installation becomes important.
It is imperative to ensure optimization of procurement cost, energy efficiency (operating cost), and the
life of each energy consuming asset. The power factor also plays a key role. It indicates the relationship
between real power (power consumed by electrical equipment) and apparent power (power that is
drawn by equipment but not completely used, so that it includes wasted energy). If the power factor of
an asset is low, it implies a loss of energy. Therefore, energy management also calls for effective planning
and monitoring of the power factor.
5

Exploring the Possibilities: Internet of Things
and Analytics
In the age of the Internet of Things (IoT), each device can be connected to the internet or intranet, or to
other devices on the network. This enables the collection of a variety of information from the devices,
including data on operations, configuration, energy consumption, and the power factor. The IoT enables
devices to make smart decisions based upon analytical rules that serve the purpose of the devices best.
The devices can send, receive, store, and leverage information, sending the information individually to
another device or broadcasting it to all devices. Figure 1 illustrates such a set-up.
Chiller data Lighting data Air handling
units data
Hub room/
workstation data
Different
sections in
the building
One specific section of the building
LAN Connectivity
Energy
management
system
application on a
central computer
Temperature
sensors
Illumination
sensors
Humidity
sensors
Fire
sensors
Figure 1: IoT based energy management system in buildings
Data scientists can use analytics and study historical data usage patterns in the building. They can create
scorecards and algorithms that allow individual devices to make better decisions about operational
parameters in different scenarios. The scorecards and algorithms might also govern the flow of data from
the devices to different destinations. Depending on the building, data scientists might create individual
scorecards and algorithms for individual devices, or joint algorithms for a set of devices that are supposed
to operate together in a certain order.
Data from each device can be stored in a central repository for future reference. While the communication
between devices may be synchronous or asynchronous based upon the requirement, a central
intelligence unit such as the energy management system serves as a facilitator. The EMS can also help
control the devices when direct communication between devices fails to serve the required purpose. In
such cases, the system optimizes the operational parameters and broadcasts them to the respective
devices over the LAN. On receiving the new instructions from the EMS, the devices change their
operational parameters accordingly. 6

In addition to assets and devices, different sensors are also connected to the internet through the LAN.
Sensors for illumination, humidity, occupancy, and temperature transmit information in real time,
enabling different assets to leverage the information. The EMS also receives and stores this information,
and leverages it to make smart decisions.
Making Sense of Data
A host of analytical solutions is emerging in the area of energy management backed by the increased
ability of the IoT to connect devices, collect data from devices, and distribute data. These solutions
leverage historical patterns of occupancy, people movement, temperature, provision of natural lighting,
energy consumption, and other information collected by smart meters, sensors, actuators, and
controllers.
Below are two scenarios where analytics enables smart insights for intelligent decision-making.
Controlling operational parameters of chillers
Commercial chillers operate by circulating chilled water into the rooms' water pipes. In each room, a
number of blowers blow air over the chilled water pipes, in turn cooling the air and leading to air
conditioning of the room. (The same mechanism is followed by central heaters; the only difference being
that the water is heated instead of chilled.) This is a two-stage process of energy expenditure. First, energy
is consumed in cooling the water that is then circulated through pipes that run in the rooms. In the
second stage, energy is consumed by the blowers that blow air over the water chilled pipes.
The ability to maintain a static temperature in a location depends upon a host of factors. These include
the occupancy, weather conditions, chiller parameters, the temperature of chilled water, the blowers in
the room, and other factors such as heat-producing items in the room. The IoT brings together
information from all these controllable and uncontrollable factors for all sections in the building. The EMS
then makes real-time decisions about the number of blowers to be switched on to maintain the required
temperature in each room and achieve ergonomic comfort. However, the EMS needs smart algorithms to
leverage the data and make intelligent real-time decisions.
A set of scorecards also needs to be developed. One set of scorecards needs to consider the
environmental conditions of the building and inform the EMS about the amount of energy required to
chill the water to the required temperature. The EMS then computes the operational parameters at which
the chiller should operate and sends this information to the chiller, enabling it to operate efficiently.
The second set of scorecards needs to consider environmental conditions, occupancy patterns,
information about the room, the number of blowers available, and past energy consumption patterns.
Using this information, the scorecards can predict the amount of energy required to maintain a specific
temperature in the room. Separate scorecards will be required for each room and each chiller. Figure 2
illustrates this process.
7

Based on the information from multiple rooms, the EMS leverages the scorecards to determine the optimal
temperature of the chilled water
Chiller
EMS switches air blowers/fans
on/off to control the room
temperature
Room 1
Chilled Water
Energy Management
System
EMS leverages
analytical scorecards to
determine the scenario
of minimal energy
consumption
Information on occupancy and
temperature sent to EMS
Figure 2: How the IoT and EMS help control the key parameters of chillers
Optimizing lighting
The EMS monitors the Air Handling Unit parameters to maintain optimal air circulation for dynamic
occupancy. This helps ensure that occupants can comfortably breathe and work in their respective rooms.
With such a system in place, lighting can also be automatically turned on when the first person enters the
room and automatically turned off in case the last person to exit the room forgets to do so.
When granular occupancy information is available, the EMS effectively governs the required lighting for
individuals who are entering or exiting. Similarly, the EMS can interact with workstations to determine if
they can be turned off or not. The workstations send information to EMS over the LAN that no active
thread is running and the EMS then validates that the user has, in fact, exited the building. It then sends
instructions to the workstation to turn itself off.
8

Realizing Holistic Benefits through Analytics
Here are a few ways to leverage the IoT and analytics simultaneously to realize benefits across the energy
management spectrum:
Asset efficiency analysis: Asset efficiency can be calculated for a variety of assets in real time. This also
helps determine the cost implications of non-optimal device performance. The efficiency of assets can
drop due to age or maintenance issues. Benchmarking techniques compute the optimal efficiency levels
at which the devices should run under the given set of environmental conditions. This can be used to
identify scenarios involving excessive energy consumption within a building.
Root cause analysis: This can be performed in cases where a higher than expected level of energy was
consumed. Given the IoT enabled data, the hypothesis generated through root cause analysis can be
statistically validated.
Predictive analytics on asset maintenance: The cost implications of maintaining all energy consuming
devices can be determined using predictive analytics. Similarly, warranty lifetime analysis can also be
performed to arrive at the optimal warranty period and costs. If certain devices are observed to fail early
in their lifecycle, the warranty tenure is expected to be long enough to cover all such early lifetime
failures. Also, while the device might not be likely to fail as a whole, certain components might be more
prone to failure than others. Furthermore, warranty analysis acquires importance if the error-prone
components in the device are expensive.
Correction and exception analysis: Analytical techniques help identify areas where power factor
correction might be required early on to enable cost savings. Analysis of exceptions, alarms, and manual
overrides to EMS is important to highlight the discrepancies that are likely to be registered in operations
from time to time. Such analysis helps determine the optimal state, the factors responsible for deviation,
and the preventive and corrective actions required to run the automated operations optimally.
Carbon emission analytics: Scenarios that help minimize the total carbon emissions from the
commercial buildings can be simulated using carbon emission analytics. Energy management standards
mandated by relevant laws can be taken into account for such simulation. This can help tailor energy
management solutions according to the location of the building.
9

Future Outlook: Revolutionizing Energy
Management with IoT
IoT is expected to play a pivotal role in efficient energy management in the future.
As people walk into a commercial building, devices and assets will gather important information about
their movements. The occupancy of each location at every point of time will also be captured,
transmitted, and stored. The control parameter of the assets and devices will be auto adjusted to levels
that create ergonomically convenient working conditions and simultaneously optimize the consumption
of energy. In offices, unique tagging of desk space to individual employee consumption will further
contribute towards efficient management of energy requirements.
Artificial lighting in the rooms will be oriented in ways that ensure the total illumination in the room is
ergonomically convenient for all the occupants. This will also allow for the best use of the natural light. As
the sunlight in the room increases, artificial illumination is automatically reduced so that the total
illumination remains constant at the desired ergonomic level. This optimized energy consumption of
lighting will be maintained by the energy management system in real time. The results are savings in
lighting costs and enhanced life of the lighting equipment.
Fire sensors can become active in the event of fire and flash the nearest exit. The same fire exits can
detect the number of people in the process of exiting through different routes. The EMS can use this
information to develop and highlight routes to streamline traffic through exit routes, ensuring that more
people reach safety.
With the rising cost of commercial energy, smart energy management systems will be used by
organizations for competitive advantage. As the volume of data collected by smart meters increases over
time, these systems will increasingly leverage the latent information hidden in the data to make smart
choices. Big Data and Hadoop are expected to be extensively used in the process as data scientists begin
to mine this data to develop smarter algorithms and decision making tools. Furthermore, robust
analytical algorithms will be applied across varied scenarios, to identify and prioritize energy optimization
opportunities.
10

About TCS Business Process Services Unit
Enterprises seek to drive business growth and agility through innovation in an increasingly
regulated, competitive, and global market. TCS helps clients achieve these goals by managing and
executing their business operations effectively and efficiently.
TCS' Business Process Services (BPS) include core industry-specific processes, analytics and insights,
and enterprise services such as finance and accounting, HR, and supply chain management. TCS
TM
creates value through its FORE simplification and transformation methodology, backed by its deep
TM
domain expertise, extensive technology experience, and TRAPEZE suite of solution accelerators
and governance enablers. TCS complements its experience and expertise with innovative delivery
models such as using robotic automation and providing Business Processes as a Service (BPaaS).
TCS’ BPS unit has been positioned in the leaders’ quadrant for various service lines by many leading
analyst firms. With over four decades of global experience and a delivery footprint spanning six
continents, TCS is one of the largest BPS providers today.
Contact
For more information about TCS’ Business Process Services Unit, visit: www.tcs.com/bps
(http://www.tcs.com/bps)
Email: bps.connect@tcs.com
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