Warm, dry, healthy homes and peak electricity demand: Wham-wham or win-win?

Scene-setting and (slightly) provocative presentation given at BRANZ's HEEP2 Workshop, 4th April 2019 | InterContinental Wellington (https://branz.arlo.co/courses/33-energy-enduse-in-new-zealand-homes-heep2-workshop?e=db803130d8a5492990ee97d1e61b7c45)

Transcript

1. Warm, dry, healthy homes and peak
   electricity demand
   Ben Anderson
   ben.anderson@otago.ac.nz / b.anderson@soton.ac.uk
   @dataknut
   Wham-wham or win-win?
   

   View Slide

2. @dataknut
   What’s the problem?
   2
   Total NZ electricity demand per half hour (June)
   Source: Electricity Authority
   GW (sum)
   

   View Slide

3. @dataknut
   Estimating the Technical Potential for Residential Demand Response in New Zealand
   Fig. 3 illustrates electricity generation by time of day on GWh per half-hour trading
   period. Times of peak electricity generation are characterised by a higher electricity
   supply and demand at certain times and occur in early morning and evening hours in
   winter 2017. The maximum power on an average day in winter 2017 was 6.2 GW (equi-
   valent to 3.1 GWh per half-hour) and 5 GW in summer. Times of electricity peaks change
   by season. In summer 2017, the evening peak was much flatter and occurred slightly
   earlier compared to winter of the same year. This change in the electricity supply pat-
   tern is caused by weather conditions in December that do not necessitate appliances
   such as electrical heating systems to be activated, coupled with daylight saving and also
   longer daylight hours for summer, a lower use of lighting technologies in the early even-
   ing.
   All figures and calculations in this report consider New Zealand daylight saving.
   Fig. 3| Daily average half-hour electricity generation profile in summer and winter 2017
   Source: Based on (Electricity Authority, 2018c)
   Increased demand during time intervals of high electricity demand are largely supplied
   by hydro electricity generation. Hydro electricity generation as depicted in Fig. 4 rep-
   resents a significant part of New Zealand’s electricity supply and necessitates active
   Page 17 of 113
   Why is ‘peak’ a problem?
   • ‘Dirty’ energy (?)
   Carbon problems:
   • Higher priced energy
   Cost problems:
   • PV & Wind
   Renewables mis-match
   • Inefficient use of resources;
   • ‘Local’ (LV network) overload;
   Infrastructure problems:
   3
   Filling the
   trough
   Peak load
   Depends on hydro levels in Feb – April
   Khan et al (2018)
   10.1016/j.jclepro.2018.02.309
   

   View Slide

4. @dataknut
   Estimating the Technical Potential for Residential Demand Response in New Zealand
   Fig. 3 illustrates electricity generation by time of day on GWh per half-hour trading
   period. Times of peak electricity generation are characterised by a higher electricity
   supply and demand at certain times and occur in early morning and evening hours in
   winter 2017. The maximum power on an average day in winter 2017 was 6.2 GW (equi-
   valent to 3.1 GWh per half-hour) and 5 GW in summer. Times of electricity peaks change
   by season. In summer 2017, the evening peak was much flatter and occurred slightly
   earlier compared to winter of the same year. This change in the electricity supply pat-
   tern is caused by weather conditions in December that do not necessitate appliances
   such as electrical heating systems to be activated, coupled with daylight saving and also
   longer daylight hours for summer, a lower use of lighting technologies in the early even-
   ing.
   All figures and calculations in this report consider New Zealand daylight saving.
   Fig. 3| Daily average half-hour electricity generation profile in summer and winter 2017
   Source: Based on (Electricity Authority, 2018c)
   Increased demand during time intervals of high electricity demand are largely supplied
   by hydro electricity generation. Hydro electricity generation as depicted in Fig. 4 rep-
   resents a significant part of New Zealand’s electricity supply and necessitates active
   Page 17 of 113
   Why is ‘peak’ a problem?
   • ‘Dirty’ energy (?)
   Carbon problems:
   • Higher priced energy
   Cost problems:
   • PV & Wind
   Renewables mis-match
   • Inefficient use of resources;
   • ‘Local’ (LV network) overload;
   Infrastructure problems:
   4
   Filling the
   trough
   Peak load
   Depends on hydro levels in Feb – April
   Khan et al (2018)
   10.1016/j.jclepro.2018.02.309
   

   View Slide

5. @dataknut
   Estimating the Technical Potential for Residential Demand Response in New Zealand
   Fig. 3 illustrates electricity generation by time of day on GWh per half-hour trading
   period. Times of peak electricity generation are characterised by a higher electricity
   supply and demand at certain times and occur in early morning and evening hours in
   winter 2017. The maximum power on an average day in winter 2017 was 6.2 GW (equi-
   valent to 3.1 GWh per half-hour) and 5 GW in summer. Times of electricity peaks change
   by season. In summer 2017, the evening peak was much flatter and occurred slightly
   earlier compared to winter of the same year. This change in the electricity supply pat-
   tern is caused by weather conditions in December that do not necessitate appliances
   such as electrical heating systems to be activated, coupled with daylight saving and also
   longer daylight hours for summer, a lower use of lighting technologies in the early even-
   ing.
   All figures and calculations in this report consider New Zealand daylight saving.
   Fig. 3| Daily average half-hour electricity generation profile in summer and winter 2017
   Source: Based on (Electricity Authority, 2018c)
   Increased demand during time intervals of high electricity demand are largely supplied
   by hydro electricity generation. Hydro electricity generation as depicted in Fig. 4 rep-
   resents a significant part of New Zealand’s electricity supply and necessitates active
   Page 17 of 113
   What makes
   up peak
   demand?
   What might be
   reduced?
   Who might
   respond?
   And what are
   the network
   consequences?
   What to do?
   •Levelling the load
   Storage
   •Reducing the load
   Demand Reduction
   •Shifting the load
   somewhere else in time
   (& space)
   Demand Response
   5
   

   View Slide

6. @dataknut
   Estimating the Technical Potential for Residential Demand Response in New Zealand
   Fig. 3 illustrates electricity generation by time of day on GWh per half-hour trading
   period. Times of peak electricity generation are characterised by a higher electricity
   supply and demand at certain times and occur in early morning and evening hours in
   winter 2017. The maximum power on an average day in winter 2017 was 6.2 GW (equi-
   valent to 3.1 GWh per half-hour) and 5 GW in summer. Times of electricity peaks change
   by season. In summer 2017, the evening peak was much flatter and occurred slightly
   earlier compared to winter of the same year. This change in the electricity supply pat-
   tern is caused by weather conditions in December that do not necessitate appliances
   such as electrical heating systems to be activated, coupled with daylight saving and also
   longer daylight hours for summer, a lower use of lighting technologies in the early even-
   ing.
   All figures and calculations in this report consider New Zealand daylight saving.
   Fig. 3| Daily average half-hour electricity generation profile in summer and winter 2017
   Source: Based on (Electricity Authority, 2018c)
   Increased demand during time intervals of high electricity demand are largely supplied
   by hydro electricity generation. Hydro electricity generation as depicted in Fig. 4 rep-
   resents a significant part of New Zealand’s electricity supply and necessitates active
   Page 17 of 113
   What makes
   up peak
   demand?
   Light
   Hot
   water
   Heat
   Some examples…
   •Levelling the load
   Storage
   •Reducing the load
   Demand Reduction
   •Shifting the load
   somewhere else in time
   (& space)
   Demand Response
   6
   

   View Slide

7. @dataknut
   Data: NZ GREENGrid
   7
   Get the data: https://dx.doi.org/10.5255/UKDA-SN-853334
   • Sample of ~ 40 households
   • Circuits measured:
   • Hot water
   • Lighting
   • Heat pumps
   • Kitchen
   • Bedrooms
   • etc
   • Data:
   • Household survey
   • Mean power (W) per minute
   (GridSpy)
   

   View Slide

8. @dataknut
   Reduce: Lighting
   8
   Get the data: https://dx.doi.org/10.5255/UKDA-SN-853334
   VERY small n…
   

   View Slide

9. @dataknut
   Reduce: Lighting
   9
   Get the data: https://dx.doi.org/10.5255/UKDA-SN-853334
   VERY small n…
   

   View Slide

10. @dataknut
    Reduce: Lighting (seasonal)
    10
    Real world
    heterogeneity
    VERY small n…
    Get the data: https://dx.doi.org/10.5255/UKDA-SN-853334
    For whom
    might LEDs
    reduce
    demand?
    

    View Slide

11. @dataknut
    Shift: Hot water
    11
    Complexities
    Ripple
    control
    Gas
    Timers
    Energy
    cultures
    Get the data: https://dx.doi.org/10.5255/UKDA-SN-853334
    

    View Slide

12. @dataknut
    Shift: Hot water
    12
    Complexities
    Ripple
    control
    Gas
    Timers
    Energy
    cultures
    Get the data: https://dx.doi.org/10.5255/UKDA-SN-853334
    We know this (don’t we?)
    

    View Slide

13. @dataknut
    Shift: Hot water
    13
    Get the data: https://dx.doi.org/10.5255/UKDA-SN-853334
    VERY small n…
    

    View Slide

14. @dataknut
    Shift: Hot water
    14
    Complexities
    Ripple
    control
    Gas
    Timers
    Energy
    cultures
    Get the data: https://dx.doi.org/10.5255/UKDA-SN-853334
    What might
    shift
    demand?
    Real world
    heterogeneity
    

    View Slide

15. @dataknut
    Shift: Heat (pumps)
    15
    Complexities
    Thermostats
    Radiant
    heaters
    Woodburners
    Household
    practices
    Norms of
    'comfort'
    Get the data: https://dx.doi.org/10.5255/UKDA-SN-853334
    

    View Slide

16. @dataknut
    Shift: Heat (pumps)
    16
    Complexities
    Thermostats
    Radiant
    heaters
    Woodburners
    Household
    practices
    Norms of
    'comfort'
    Get the data: https://dx.doi.org/10.5255/UKDA-SN-853334
    VERY small n…
    

    View Slide

17. @dataknut
    Shift: Heat (pumps)
    17
    Complexities
    Thermostats
    Radiant
    heaters
    Woodburners
    Household
    practices
    Norms of
    'comfort'
    Get the data: https://dx.doi.org/10.5255/UKDA-SN-853334
    What might
    shift
    demand?
    Real world
    heterogeneity
    

    View Slide

18. @dataknut
    Why bother?
    18
    • We can’t shift light
    • => More efficient lighting
    Lighting
    • Randomisation (ripple)
    • Hot water storage
    • PV?
    Hot water
    • Heat pump into thermal mass
    (insulated solid floor?)
    • Use other fuels (wood?) for
    ‘peak’?
    Heat
    Source: Dortans, C (2019) Estimating the Technical Potential for Residential Household Appliances to
    Reduce Daily Peak Electricity Demand in New Zealand: MSc Thesis, University of Otago
    Could take up to 780 MW out of winter evening peak
    Could take up to 700 MW out of winter evening peak
    Could take up to 1000 MW out of winter morning peak
    Could take up to 280 MW out of winter evening peak
    Could take up to 320 MW out of winter morning peak
    Current adoption levels
    Huntly Power Station
    

    View Slide

19. @dataknut
    Why bother?
    19
    • We can’t shift light
    • => More efficient lighting
    Lighting
    • Randomisation (ripple)
    • Hot water storage
    • PV?
    Hot water
    • Heat pump into thermal mass
    (insulated solid floor?)
    • Use other fuels (wood?) for
    ‘peak’?
    Heat
    Source: Dortans, C (2019) Estimating the Technical Potential for Residential Household Appliances to
    Reduce Daily Peak Electricity Demand in New Zealand: MSc Thesis, University of Otago
    Could take up to 780 MW out of winter evening peak
    Could take up to 700 MW out of winter evening peak
    Could take up to 1000 MW out of winter morning peak
    Could take up to 280 MW out of winter evening peak
    Could take up to 320 MW out of winter morning peak
    Current adoption levels
    Huntly Power Station
    ~ -30% of winter peak load
    Network cost efficiencies of
    ~ $164m/year
    And EVs are coming…
    

    View Slide

20. @dataknut
    What do we need?
    § Energy Cultures:
    • Stephenson et al (2015)
    • https://doi.org/10.1016/j.erss.2015.03.005
    § Better data
    • HEEPS2 might provide it…
    § Questions?
    • @dataknut
    • ben.anderson@otago.ac.nz
    20
    But do we have the data?
    We have the tools
    

    View Slide