VET4SBO Level 1 module 3 - unit 2 - v0.9 en

ECVET Training for Operatorsof IoT-enabledSmart Buildings (VET4SBO)
2018-1-RS01-KA202-000411
Level 1
Module 3: Fundamentals of Internet-of-Things (IoT) and
indicative applications. Opportunities for low-cost
operational improvement
Unit 3.2: Indicative applications in combination with
legacy BMS or for building standalone systems

Outline
1. Legacy Building Management Systems
2. IoT-enabled Building Management Systems
3. Legacy and IoT-enabled Building Management Systems
combined
4. Case Studies and Examples
5. Faults, protection and optimization

Legacy Building Management Systems
Legacy BMS/BAS
• Dedicated to individual processes of critical building systems
– HVAC (Chiller, fan, pump etc.) on/off
– Lighting on/off schedules
– Network & Communication
– …
• Great tool for consolidating information

Legacy BMS/BAS Examples
Functionalities
• View, control, configure
system remotely
(Computer interface or
individual components)
• Control equipment based
on pre-defined schedules
(time, date and holiday)
• Alarm functions

Siemens BMS/BAS Architecture Example
• Programming and Control
only on-field
• Limited available
information
• Hard to evaluate:
– Energy efficiency
– Comfort Levels
– Required Maintenance
Generic buildingautomationsystem

Siemens BMS/BAS Interface 1 (App Interface)

Siemens BMS/BAS Example (Architecture)
Hardware
(sensors/actuators)
CommunicationProtocol
(BACnet/IP/ModBus/Lonwks)
Software (Web
Platforms/Applications)

Johnson Controls BMS/BAS Example
• Manage Occupant Comfort
– Automatic controls & equipment (e.g.
HVAC, lighting, chillers, roof tops, air
handlers, VAV boxes etc.)
– Integration & control of other systems
• Energy Management
– Intelligent sequences and routines to
manage building and system energy
consumption

• Control Core Mechanical Systems

• Key Sub-Systems Integrations

• Non-traditional BMS Integrations

Legacy BMS/BAS Components
• High cost of
upgrading
legacy
BMS/BAS
systems
• Extra sensor
compatibility
problems

Legacy BMS/BAS Protocols
Legacy Protocols:
• BACnet deals with the
upper-level
communications
protocol
• IBECS handles the
lower part of the
network
A bridge intermediates
between the two
protocols.

IoT Devices
• IoT enabled Sensors:
– Occupancy sensor
– Humidity sensor
– Light sensor
• Unified Platform
– Legacy + IoT devices
• Data Analytics 
Decision Making

IoT enabled BMS/BAS Example 1 (Predix)

Legacy BMS/BAS & IoT devices
• Make existing systems smarter
• Improve feedback from the
building and the occupants
• Advanced analytics
• Low integration cost
• Higher improvements in:
– Energy Efficiency
– Occupants Comfort
– Air Quality

Intelligent HVAC- Air-flow Control Example
• Air flow control: When occupants in the room increase, the
thermostat will sense the increase in the room temperature.
Control unit will open its damper allowing more air to the
room, which will cause a drop in the duct static pressure
sensed by the duct static pressure sensor.

Intelligent HVAC- Temperature Control Example
• Temperature and fan control system: When the control unit is
not functioning, the BAS detects and communicates the ‘OFF’
status of the unit, thus shutting it down. For example, if the
room temperature is fixed at 25 degree Celsius, but the actual
room temperature is 27 degree Celsius, BAS/operator must
open the chilled water valve. Once the temperature falls below
25 degree Celsius, the valve must be shut.

Intelligent HVAC- Light System Control Example
• Lighting System: The Lighting System can be controlled using
motion and detection sensors that detect occupancy and
motion. On/Off switches can be configured based on pre-
defined time schedules. Daylight-linked automated response
systems can also be incorporatedinto the system, which in
combinationwith dimmable light offer a higher degree of
flexibility

Intel: Legacy BMS/BAS & IoT Unified Framework (1/2)

Intel: Legacy BMS/BAS & IoT Unified Framework (2/2)

Seamless integration of all protocols

IoTs AND/OR BMS/BAS - Case Study 1 (1/2)
The University of Indonesia (ADVANTEC)
• Objective: Reduce Energy Consumption
• Solution:
– Integrate the class booking system with IoT-enabled actuators and
smart meters to schedule the AC units and lights accordingly
• Requirements:
– SCADA: Light and ACs monitoring and control in real time
– Interface between actuators and online Application (ADVANTEC
WebAccess 8.0.)

Solution Architecture
A Cost Effective IoT
solution interfaced
with Advantec BAS
platform to control
the AC units and
lighting
System Diagram

Bringing the Morgan Building into the
21st Century (Honeywell)
• No prior BMS/BAS system. Only
individual units
• Objective:
– Maximize energy savings
– Improve energy management data
– Integrate control of all systems and devices
– Enhance monitoring, diagnosis and system
configuration

Bringing the Morgan Building into the 21st Century (Honeywell)
• Solution (Honeywell products used):
– WEBs-AX building automation software
– WEBs-AX integration controllers
– Spyder® field controllers
– Zio® LCD wall modules
– TR21 wireless sensors
– TR20 sensors
– Valves and actuators
New
IoT
sensors

Bringing the Morgan Building into the 21st Century (Honeywell)
• Results :
– Using WEBs-AX enabled integration of all systems
– Centralized control resulted in an 18.6% drop in electricity usage and a
52% decrease in BTUs
– Energy savings, improved building management and reduced maintenance
costs
– Morgan Building was awarded LEED Silver Certificationby the U.S. Green
Building Council
– Morgan Building achieved EPA Energy Star certification

• Objective:
– Integrate systems on a common platform
– Efficient precision control in key exhibit
areas
– Maximize energy savings
– Improved monitoring, diagnosis and
configuration
– Better energy management data
San Diego Natural History Museum

• Solution (Honeywell Products):
– WEBs-AX building automation
software
• Integration of existing systems
– Honeywell NiagaraAX Framework
• Monitor and control in a
centralized manner
San Diego Natural History Museum

10 Office Building
• Existing BAS:
– 2 independent sub-
control systems
1. TAC Xenta: switching
on/off of the fan coils
2. Dali Protocol: Switching
on/off and dimming of
the luminaires
Aghemo C, Blaso L, Pellegrino A. Buildingautomationand control systems: A case study to evaluate
the energy and environmental performances of a lighting control system in offices. Automationin
Construction. 2014 Jul 1;43:10-22.

Simplified diagram of generic monitoring and
control system
Brambley, “Advanced Sensors and Controls for BuildingApplications:Market Assessment
and PotentialR&D Pathways“2005

• Added IoT Sensors:
– Photosensor (LI04
Thermokon sensor)
– 2x Occupancy infrared
sensor (WRF04
Thermokon sensor PIR)
– Mixed sensor photocell
(MDS Thermokon Ceiling
multi-sensor 360°)

• Intelligent control of the lights resulted in significant energy savings

Data Visualization Online Example (1/4)
John Jay College of Criminal Justice building of Cuny University
(2015)
• Multiple sensors reading every 15 min
• Sensor data available in (rscript.cisdd.org)
• Online Analytics (rscript.cisdd.org)  Room Temperature
Forecasting

Online Data visualization and Analysis platform:

Sensor Data for a Room:
• Room Temperature
• AHU Return Temp
• AHU Supply Temp
– Sup Temp ↓ then Room Temp↓
– Sup Temp ↑ then Room Temp↑

Sensor Data for a Room:
1. Occupancy ↑ (inferred from the
increased CO2 levels)
2. Cooling system ↑
3. Room Temp ↓
Inference from other sensors
Examples:
• Increased CO2  Occupancy
Occupancy  Room must be
cooled

Legacy BMS/BAS Cross-dependencies (1/5)
• Functions in the
room: Heating 1.1
and Cooling 2.1
• Functions of the
distribution
network, ventilation
and hot water: heat
pump 1.7 and
ventilation plant 4.5.
Siemens: BuildingAutomation – Impact on energy efficiency. Applicationof EN 15232-1:2017

• Both temperature set-
points (for heating and
cooling) have the same
value. In other words,
there is no energy dead
band. The HVAC plant is
operated 24 hours a day,
although occupancy is
only 11 hours.

• Operation of the HVAC
plant starts two hours
prior to occupancy and
ends three hours after
the end of the occupancy
period
• Small setpoint difference
of 1◦ Celsius
Dead energy band
Siemens: BuildingAutomation– Impact on energy efficiency. Applicationof EN 15232-1:2017

• Better adapted operating
times by optimizing
switching on/off periods
• Larger dead energy band

• Advanced BAC functions,
as well as adaptive set-
point adjustments (based
on occupancy) for cooling
or demand-controlled air
flows.

Occupancy levels for different buildings
• HVAC, Lights and
AHU must be
programmed
accordingly
• CO2 sensors can be
used to approximate
occupancy

Faults, Protection and Optimization(1/10)
• While a BMS/BAS has alarms for temperature or failed equipment
at a single point, fault detection and diagnostics and analysis is
most of the times up to the operator to decide
• The Operator needs to compare, correlate and find patterns from
the available information and to decide whether a fault has
occurred or if maintenance needs to be scheduled or parts/sensors
to be replaced
• Measurement Analytics and merging of information from different
IoT devices facilitate the operators’ prompt actions

Faults, Protection and Optimization (2/10)
• Alert operators of facility problems
– Detect problems prior to becoming an issue
– Alarm notification and management
– Performance degradation
• Protect facility assets
– Chiller plants, HVAC and mechanical equipment, people, Fire &
Security systems
– Increase facility value

Problem: Buildings have constantly changing schedules and
temperature requests. A typical university or office will modify the
schedule according to the requirements of the space. That request
may be for only one day, but it may continue to stay in that override
condition without the operator’s attention. As a result, the air
handling unit (AHU) serving the space may be using significantly more
energy than prior to that day, yet no one has found that fault because
there are no alarms to monitor.
Solution: An occupancy IoT-enabled sensor in the room could be the
decisive factor for the operation of the AHU

Problem:
• HVAC system has no feedback and can only be scheduled in
constant set-points
Solution
Adding a CO2 sensor  Information about occupancy 
Shows when to turn on/off the HVAC System
Adding occupancy sensors  Turn on/off the lights
 Major improvements of energy savings!!!

Problem:
• Reduction of HVAC energy consumption
– HVAC energy consumption is considerably affected by the amount of
fresh air pumped into the building
• Solution:
– CO2 sensors to check the quality of air in the building
– Regulate fresh air intake accordingly

• Problem:
– Complaints for uncomfortable temperature
• Possible solution(s):
– Humidity Sensors: Temperature could be fine, but increased humidity
levels affect the occupants comfort
– Illuminance sensors in case of large windows
– Maintenance scheduling of the HVAC system

• Occupancy sensors: many areas have minimal occupancy at
any time or highly variable loads, such as conference rooms. In
such cases it may be appropriate to provide minimal
conditionedair during normal hours and ramp up only when
space is fully occupied. Ramp-up can sometimes be most
effectively provided by standaloneunits to avoid over sizing
the central plant to respond to low frequency situation.

• Problem:
– Abnormal consumption
– Flow meters to alarm on abnormal consumption
– Temperature optimization control of boilers, by control strategy
• Occupancy sensors
• Utilization schedules
• CO2 measurements

• Problem: Reports of headaches and/or dizziness and/or
nausea
– CO2 sensors
– CO sensors
– PM2.5 and PM10 sensors
– Humidity sensors

• Problem: No monitoring in boiler rooms. Occasional incidents
release chemicals and odours that are transferred in the
building HVAC system
– CO & CO2 sensors in the boiler rooms  Immediate system shutdown
if something is outside of the normal range

Fault Inference example
• Let’s say your outdoor air damper is 30% and your return air damper (which is the inverse of
the outdoor air damper) is 70% if you take your outdoor air at 70 degrees and your return
air at 74 degrees, then your mixed air temp should be 72.8 degrees.
• How did I calculate this? I simply took the outdoor air * the 30% outdoor air damper
position + The return air temperature * the 70% return air damper position.
• This is a quick way to tell if something is amiss with your damper control. For example, if
you have 10% outdoor air damper at 100 degrees outdoor air and 90% return air damper at
74 degrees return air your mixed air temp should be 76.6 degrees.
• However, if your mixed air temperature is 85 degrees you can quickly determine that you
have a mixed air temperature control issue.
– Mobile Temperature sensors in the room to facilitate calibration of the outdoor air ratio

Disclaimer
For further information, relatedto the VET4SBO project, please visit the project’swebsite at https://smart-building-
operator.euor visit us at https://www.facebook.com/Vet4sbo.
Downloadour mobile app at https://play.google.com/store/apps/details?id=com.vet4sbo.mobile.
This project (2018-1-RS01-KA202-000411) has been funded with support from the European Commission (Erasmus+
Programme). Thispublicationreflects the views only of the author, and the Commission cannot be held responsible
for any use which may be made of the informationcontainedtherein.

VET4SBO Level 1 module 3 - unit 2 - v0.9 en

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VET4SBO Level 1 module 3 - unit 2 - v0.9 en