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Tipperary Energy Agency
Cold weather performance of Heat pumps in Irish homes – Do we really need back up
heat?
Presented by Paul Kenny
September 2018 | London
 Tipperary Energy Agency – Local Energy Agency established under
SAVE (20 years ago)
 Established the Superhomes Program to test, demonstrate and scale up
deep retrofit with heat pumps
 150 homes completed to date (80% with metering).
 Significant communications & Market development actions
 Monitoring of most homes to date – Heat & Elec
 Parallel R&D project Superhomes 2.0 testing:
 Validation of ASHP building integration
 Optimisation of ASHP
 Experimental ToU tariffs; PV integration;
 Aiming to provide smart grid and financing
 Just submitted my MSc Dissertation on HP optimisation
About Us
How we design Heat pump Installations
 Radiators predominantly
 High volume mass produced steel radiators (Stelrad/
Quinn etc)
 Cheapest heat transfer area per €uro invested.
 Usually on existing radiator pipe spacing
 Only replaced if required (<80% of design load)
 Generally replace sitting room/ kitchen radiators
 Sized for -3/21 at 43 Mean water temperature MWT (about
15-20% larger than condensing boilers)
 Room by room heat load calcs
 Allow 2hours per day for DHW.
 Demand Curve (flow temperature)
 34 Degrees 7 to 15 degrees C. (operational hours
increase as temp. drops)
 46 Degrees -3
 Engineer.
Retrofit Results
0
100
200
300
400
500
600
700
800
900
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77
kWh/M2/Annum
Pre & Post BER (Energy Certificate)
 26kWh / m2 delivered energy per annum average
 Energy certificate of 67 KWh/M2 Primary energy
 65% - 80% cost savings from buildings.
The Beast from the East
 1st March 2018 significant weather event
 7 days below zero
 300mm snow
 Not a single complaint – several positive emails & texts.
-6.0
-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
10.0
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
20-Feb 22-Feb 24-Feb 26-Feb 28-Feb 02-Mar 04-Mar 06-Mar 08-Mar 10-Mar
Temperature(°C)
COP
Day
SH001 - COP vs Outside Temperature
Overall COP Average Outside Temperature COP required to equal Oil Cost
Deep dive into one house
-6
-4
-2
0
2
4
6
8
10
20-Feb 21-Feb 22-Feb 23-Feb 24-Feb 25-Feb 26-Feb 27-Feb 28-Feb 01-Mar 02-Mar 03-Mar 04-Mar 05-Mar 06-Mar 07-Mar 08-Mar 09-Mar 10-Mar
€0.00
€0.50
€1.00
€1.50
€2.00
€2.50
€3.00
€3.50
Temperature(°C)
Day
CostSavingsperday(€) SH001 - Cost Savings vs Outside Temperature
Savings Average of OutsideTemperature
Deep dive into one house
0
10
20
30
40
50
60
70
80
90
100
20-Feb 21-Feb 22-Feb 23-Feb 24-Feb 25-Feb 26-Feb 27-Feb 28-Feb 01-Mar 02-Mar 03-Mar 04-Mar 05-Mar 06-Mar 07-Mar 08-Mar 09-Mar 10-Mar
Energy(kWh)
Day
SH001- Energy Consumed per day (ASHP actual, Fossil Estimation @85%)
Oil Energy Consumption ASHP Energy Consumption
1-Feb 22-Feb 23-Feb 24-Feb 25-Feb 26-Feb 27-Feb 28-Feb 01-Mar 02-Mar 03-Mar 04-Mar 05-Mar 06-Mar 07-Mar 08-Ma
OIL COST ASHP COST
0.00
0.50
1.00
1.50
2.00
2.50
3.00
0 2 4 6 8 10 12 14 16 18
COP per house - Worst Day
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
COP per house - 2 weeks of cold weather
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
0
2
4
6
8
10
12
14
16
18
COP
COP Oct ‘17- May ‘18 for 16 Superhomes
Overall Average = 3.1
0%
5%
10%
15%
20%
25%
30%
35%
0 2 4 6 8 10 12 14
%ofheatinghours
kW load
Hourly 2-Hourly 4-Hourly Daily average
kW Hourly 2-Hourly 4-Hourly
Daily
average
1 6.5% 12.7% 15.0% 20.6%
2 8.0% 13.7% 16.9% 27.1%
3 14.1% 14.4% 16.9% 30.4%
4 15.1% 17.1% 18.9% 19.0%
5 22.0% 20.7% 17.0% 2.4%
6 17.7% 15.7% 12.0% 0.4%
7 8.0% 4.3% 2.6% 0.0%
8 3.1% 0.7% 0.4% 0.0%
9 2.4% 0.3% 0.2% 0.0%
10 1.7% 0.2% 0.0% 0.0%
11 0.9% 0.1% 0.0% 0.0%
12 0.3% 0.1% 0.0% 0.0%
 150 homes – no backup heater
 No immersion
 Some stoves – but largely unused
 Histogram of heat loads is
surprisingly low.
 Minimising cycling by sizing
correctly.
 Extra Cap-ex into radiators
instead.
Backup heater – Can’t fathom why?
 Decreasing Flow => increasing
performance
 Floor is minimum compressor
output
 Cycling an issue at milder
temperatures
 Commissioning setpoints =>
steady state dissipated heat ~
70% compressor minimum load
0
0.5
1
1.5
2
2.5
3
3.5
4
0 5 10 15 20
COP
Run Time (min)
2
3
4
5
6
7
8
32 34 36 38 40 42
Heatoutput(kW)
Flow Temperature (°C)
Radiator load by Temperature Heat pump Minimum Capacity
Linear (Radiator load by Temperature) Linear (Heat pump Minimum Capacity)
Careful of Cycling
Summary and Key Take-Outs
 Well sized and designed Heat pumps perform wonderfully in cold
weather
 Savings go up as temperature drops
 Average -4 degrees performance 2.5; 0 degrees 2.75
 Typical electrical loads from 1.5kW to 2.5kW (150kWh heat).
 Size emitters large and all* other problems disappear
 DT23 Vs DT30 ~ 18% increase in cost (€400 for 200m2
home)
 Increases HP performance by c. 15% - 20%
 Decreases cycling & lowers operational temperatures
 3-5 year payback.
 Improves comfort levels through faster response.

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Cold weather performance of heat pumps in Irish homes – Do we really need to have backup heaters/ boilers?

  • 1. Tipperary Energy Agency Cold weather performance of Heat pumps in Irish homes – Do we really need back up heat? Presented by Paul Kenny September 2018 | London
  • 2.  Tipperary Energy Agency – Local Energy Agency established under SAVE (20 years ago)  Established the Superhomes Program to test, demonstrate and scale up deep retrofit with heat pumps  150 homes completed to date (80% with metering).  Significant communications & Market development actions  Monitoring of most homes to date – Heat & Elec  Parallel R&D project Superhomes 2.0 testing:  Validation of ASHP building integration  Optimisation of ASHP  Experimental ToU tariffs; PV integration;  Aiming to provide smart grid and financing  Just submitted my MSc Dissertation on HP optimisation About Us
  • 3. How we design Heat pump Installations  Radiators predominantly  High volume mass produced steel radiators (Stelrad/ Quinn etc)  Cheapest heat transfer area per €uro invested.  Usually on existing radiator pipe spacing  Only replaced if required (<80% of design load)  Generally replace sitting room/ kitchen radiators  Sized for -3/21 at 43 Mean water temperature MWT (about 15-20% larger than condensing boilers)  Room by room heat load calcs  Allow 2hours per day for DHW.  Demand Curve (flow temperature)  34 Degrees 7 to 15 degrees C. (operational hours increase as temp. drops)  46 Degrees -3  Engineer.
  • 4. Retrofit Results 0 100 200 300 400 500 600 700 800 900 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 kWh/M2/Annum Pre & Post BER (Energy Certificate)  26kWh / m2 delivered energy per annum average  Energy certificate of 67 KWh/M2 Primary energy  65% - 80% cost savings from buildings.
  • 5. The Beast from the East  1st March 2018 significant weather event  7 days below zero  300mm snow  Not a single complaint – several positive emails & texts.
  • 6. -6.0 -4.0 -2.0 0.0 2.0 4.0 6.0 8.0 10.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 20-Feb 22-Feb 24-Feb 26-Feb 28-Feb 02-Mar 04-Mar 06-Mar 08-Mar 10-Mar Temperature(°C) COP Day SH001 - COP vs Outside Temperature Overall COP Average Outside Temperature COP required to equal Oil Cost
  • 7. Deep dive into one house -6 -4 -2 0 2 4 6 8 10 20-Feb 21-Feb 22-Feb 23-Feb 24-Feb 25-Feb 26-Feb 27-Feb 28-Feb 01-Mar 02-Mar 03-Mar 04-Mar 05-Mar 06-Mar 07-Mar 08-Mar 09-Mar 10-Mar €0.00 €0.50 €1.00 €1.50 €2.00 €2.50 €3.00 €3.50 Temperature(°C) Day CostSavingsperday(€) SH001 - Cost Savings vs Outside Temperature Savings Average of OutsideTemperature
  • 8. Deep dive into one house 0 10 20 30 40 50 60 70 80 90 100 20-Feb 21-Feb 22-Feb 23-Feb 24-Feb 25-Feb 26-Feb 27-Feb 28-Feb 01-Mar 02-Mar 03-Mar 04-Mar 05-Mar 06-Mar 07-Mar 08-Mar 09-Mar 10-Mar Energy(kWh) Day SH001- Energy Consumed per day (ASHP actual, Fossil Estimation @85%) Oil Energy Consumption ASHP Energy Consumption
  • 9. 1-Feb 22-Feb 23-Feb 24-Feb 25-Feb 26-Feb 27-Feb 28-Feb 01-Mar 02-Mar 03-Mar 04-Mar 05-Mar 06-Mar 07-Mar 08-Ma OIL COST ASHP COST
  • 10. 0.00 0.50 1.00 1.50 2.00 2.50 3.00 0 2 4 6 8 10 12 14 16 18 COP per house - Worst Day
  • 11. 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 COP per house - 2 weeks of cold weather
  • 12. 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 0 2 4 6 8 10 12 14 16 18 COP COP Oct ‘17- May ‘18 for 16 Superhomes Overall Average = 3.1
  • 13. 0% 5% 10% 15% 20% 25% 30% 35% 0 2 4 6 8 10 12 14 %ofheatinghours kW load Hourly 2-Hourly 4-Hourly Daily average kW Hourly 2-Hourly 4-Hourly Daily average 1 6.5% 12.7% 15.0% 20.6% 2 8.0% 13.7% 16.9% 27.1% 3 14.1% 14.4% 16.9% 30.4% 4 15.1% 17.1% 18.9% 19.0% 5 22.0% 20.7% 17.0% 2.4% 6 17.7% 15.7% 12.0% 0.4% 7 8.0% 4.3% 2.6% 0.0% 8 3.1% 0.7% 0.4% 0.0% 9 2.4% 0.3% 0.2% 0.0% 10 1.7% 0.2% 0.0% 0.0% 11 0.9% 0.1% 0.0% 0.0% 12 0.3% 0.1% 0.0% 0.0%  150 homes – no backup heater  No immersion  Some stoves – but largely unused  Histogram of heat loads is surprisingly low.  Minimising cycling by sizing correctly.  Extra Cap-ex into radiators instead. Backup heater – Can’t fathom why?
  • 14.  Decreasing Flow => increasing performance  Floor is minimum compressor output  Cycling an issue at milder temperatures  Commissioning setpoints => steady state dissipated heat ~ 70% compressor minimum load 0 0.5 1 1.5 2 2.5 3 3.5 4 0 5 10 15 20 COP Run Time (min) 2 3 4 5 6 7 8 32 34 36 38 40 42 Heatoutput(kW) Flow Temperature (°C) Radiator load by Temperature Heat pump Minimum Capacity Linear (Radiator load by Temperature) Linear (Heat pump Minimum Capacity) Careful of Cycling
  • 15. Summary and Key Take-Outs  Well sized and designed Heat pumps perform wonderfully in cold weather  Savings go up as temperature drops  Average -4 degrees performance 2.5; 0 degrees 2.75  Typical electrical loads from 1.5kW to 2.5kW (150kWh heat).  Size emitters large and all* other problems disappear  DT23 Vs DT30 ~ 18% increase in cost (€400 for 200m2 home)  Increases HP performance by c. 15% - 20%  Decreases cycling & lowers operational temperatures  3-5 year payback.  Improves comfort levels through faster response.