This document discusses how machine learning and IoT technologies can be applied to heat pumps to improve efficiency and operation. Data collected from connected heat pumps can be analyzed to establish a performance baseline and detect deviations. Applications include fine-tuning systems for better efficiency, issuing alerts for underperformance, detecting maintenance issues, and benchmarking different units and models. The goal is to transform electricity into household comfort through smart, efficient heat pump operation optimized for different conditions.

1. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Improved controls for smart heat
pumps
Anthony Harrigan
The Future of HVAC –
AIRAH
Sept 2017
This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden

2. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Background
Last 10 years
Heat Pumps were designed with a
big focus on energy efficiency:
• Advanced heat exchangers
• COP optimisers (i.e. subcooler, economiser)
• Inverter controlled compressors
• Vapor injection
• Electronic Expansion valves
• EC fans, EC pumps
• Smart controllers

3. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Background
Seasonal COP regulation: EN 14825
Seasonal COP initial target
was >2.8 to be compared
with the energy cost of gas
boilers.
SCOP values of 4.0 or more
were needed to reduce ROI
and achieved thanks to High
Efficiency technologies

4. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Background
Energy labelling regulation (811/2013) helps to
compare heating technologies
e.g. Heat pumps are the
most efficient technology for
space heating

5. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Future evolution
What about the next 10 years?
Heat Pumps are currently and will be designed for a
“demand/response” scenario to provide:
• Real time energy efficiency
• Flexible use of electricity
• Optimised load profile
• Optimised compromise comfort VS operative costs according to:
o Electricity cost profile
o Building/heat pump inertia
o End user related criteria

6. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
IoT
Internet of Things
The Internet of things (IoT) is the inter-networking of physical devices, vehicles, also
referred to as "connected devices" and "smart devices", buildings, and other
items embedded with electronics, software, sensors, actuators, and network
connectivity which enable these objects to collect and exchange data.
(Brown, Eric, 13 September 2016, "Who Needs the Internet of Things?“, Linux.com)
Collect, analyze and make
a wise use of data

7. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Heat Pumps are often equipped by monitoring/data logging
systems, providing:
• Large amount of data not correlated and analysed as a whole
• Limited understanding of the unit efficiency in its real operation
• Interpretation left to each maintenance operator
EEV status,
superheat
Refrigerant
charge,
subcooling
Water
temperatures
Compressor
Status
Too many
information!
Is it working
efficiently?
? ?
?
Operator
IoT: Connected Heat Pump
Fans/Pumps
status, speed

8. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Case study:
show and improve the real operation efficiency1 of Heat Pumps by
means of machine learning and A.I. tools
1 regardless the influences due to heat pump position, geographical location, seasonal
and environmental aspects, weather conditions, etc.
EEV status,
superheat
Refrigerant
charge,
subcooling
Water
temperatures
Compressor
Status
IoT: Connected Heat Pump
Heat Pump
#16 is
under-
performing!
Fans/Pumps
status, speed
0
15
30
45
60
6 12 18 24
Machine
learning
and A.I.

9. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Case study, benefits and features:
• Real time energy efficiency
• Fine tuning and what-if analysis
• Dynamic alerts for irregular or abnormal energy consumption
• Predictive maintenance
• Benchmarking between:
o different units of the same model
o different maintenances operators/operations
o different sets of parameters
IoT: Connected Heat Pump

10. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Case study, how machine learning works:
Training and Calibration: collected data are used to learn how Heat Pumps
perform on field.
Test and Results: trained algorithm is tested using new data as input. The
output is the “baseline” definition
0
20
40
60
80
6 12 18 24
Baseline definition
Energy measured
Energy expected
Trained
algorithm
Test and Results
Dataset
Input data
Training and Calibration
IoT: Connected Heat Pump
hour of the day, outdoor temperature/humidity, EEV position, fan flow,
water temperature, compressor speed, regulation setpoint, etc.

11. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Case study, application 1: fine tuning
IoT: Connected Heat Pump
Machine learning algorithm defined the Heat Pump “baseline” consumption.
Fine tuning + what if analysis allowed to increase unit efficiency
Increased efficiency

12. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Case study, application 2: dynamic alerts
IoT: Connected Heat Pump
Machine learning algorithm
defined the Heat Pump
“baseline” consumption
(lower and upper bound).
Alerts are provided when
the energy consumption is
constantly higher than the
“baseline”.

13. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Case study, application 3: detection and resolution
IoT: Connected Heat Pump
Alerts drive to maintenance operations that can be later analyzed in terms of
effectiveness

14. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Case study, application 4: benchmarking
IoT: Connected Heat Pump
Between units of the same model to identify the most well manteined
Between units of different models to identify the most performant one under
the defined conditions

15. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden
Conclusion
The path towards residential heating decarbonisation
meets IoT technology in a scenario where Heat
Pumps will provide the best way to wisely transform
available electricity (and renewable energy) into
household comfort.

16. This document and all its contents are for Carel internal use only and strictly CONFIDENTIAL
All unauthorized use, reproduction or distribution of this document or the information contained in it,
by anyone other than Carel employees is severely forbidden