Abstract

This report uses the GREEN Grid project research data to analyse a variety of residential household appliances and their contribution to peak demand under several scenarios. Although the data does not derive from a representative sample of households, we demonstrate that identifiable heating contributes ~ 21% to residential peak (17:00-21:00) demand in winter with Hot Water at ~ 17%, Lighting at 14% and Ovens at 7% while non-identified appliances contribute ~ 40%. These percentage contributions are generally similar at both regional network and sample co-incident peaks and across seasons although total power demand varies by season according to the appliance. Thus ‘Others’, heating and lighting are substantially lower in summer and whilst further research is clearly needed to unpack ‘Other’ demand, this suggests heating may be a major component.

Our results also show that simple mean (or median) values or single indicators such as average load factors mask considerable variation both within and between households. Overall we conclude that future work should focus on collecting data from a larger and representative sample of New Zealand households, ensuring that appliances are identified on circuits (especially electric heaters) and that both inter and intra-household heterogeneity should be adequately represented in analytic results.

1 About

1.1 Citation

If you wish to use any of the material from this report please cite as:

  • Dortans, C., Anderson, B. and Jack, M. (2019) NZ GREEN Grid Household Electricity Demand Data: EECA Data Analysis (Part B) Report v2.1_Final, Centre for Sustainability, University of Otago: Dunedin.

This work is (c) 2019 the authors. Usage rights are specified in the License section (1.3).

1.2 Report circulation:

  • Public – this report is intended for publication following EECA approval.

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1.4 History

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1.5 Support

This work was supported by:

  • The New Zealand Energy Efficiency and Conservation Authority (EECA)

2 Introduction

This report uses the GREEN Grid project (Stephenson et al. 2017) research data to analyse a variety of residential household appliances and their contribution to peak demand under several scenarios.

3 Data

The NZ GREEN Grid household electricity demand study recruited a sample of c 40 households in each of two regions of New Zealand (Stephenson et al. 2017). The first sample was recruited in early 2014 and the second in early 2015. Research data includes:

  • 1 minute electricity power (W) data was collected for each dwelling circuit using GridSpy monitors on each power circuit (and the incoming power). The power values represent mean(W) over the minute preceding the observation timestamp;
  • Dwelling & appliance surveys;
  • Occupant time-use diaries (focused on energy use).

The data collection was supported by the New Zealand Ministry of Business, Innovation and Employment (MBIE) through the Renewable Energy and the Smart Grid (GREEN Grid) grant (Contract ID: UOCX1203).

As background, Table 3.1 shows the mean half-hourly and mean total kW and kWh by season for the sample households in 2015. For this purpose the periods are defined as:

  • 21:00 - 07:00 Off peak (night)
  • 07:00 - 09:00 Peak (morning)
  • 09:00 - 17:00 Off peak (day)
  • 17:00 - 21:00 Peak (evening)
Table 3.1: Descriptive statistics for power data
Season Peak Mean total kWh Mean kW s.d. (kW) N households
Autumn Off peak (day) 11.05 0.39 0.67 39
Autumn Off peak (night) 11.04 0.30 0.54 39
Autumn Peak (evening) 9.95 0.68 0.93 39
Autumn Peak (morning) 4.34 0.60 0.94 39
Spring Off peak (day) 12.08 0.36 0.65 32
Spring Off peak (night) 13.18 0.31 0.57 32
Spring Peak (evening) 10.79 0.64 0.93 32
Spring Peak (morning) 4.82 0.58 0.92 32
Summer Off peak (day) 6.74 0.33 0.56 35
Summer Off peak (night) 6.52 0.24 0.41 35
Summer Peak (evening) 4.66 0.44 0.65 35
Summer Peak (morning) 2.16 0.41 0.69 35
Winter Off peak (day) 15.20 0.48 0.80 36
Winter Off peak (night) 16.66 0.41 0.71 36
Winter Peak (evening) 15.21 0.94 1.18 36
Winter Peak (morning) 6.16 0.76 1.13 36

Figure 3.1 shows the mean total kWh consumed per household by period and season. Note that this total reflects not only the power demand level but the number of hours in each period.

Mean total kWh per period by season (2015)

Figure 3.1: Mean total kWh per period by season (2015)

Figure 3.2 on the other hand shows the mean half-hourly kW demand per household by period and season and reflects the greater power demand in the evening and morning peak periods.

Mean kW per half hour by period and season (2015)

Figure 3.2: Mean kW per half hour by period and season (2015)

4 Peak Contribution

In this section we use the GREEN Grid residential sample to estimate the contribution of each appliance to peak demand. For this analysis we use demand data averaged over 30 minute intervals. We consider three different definitions of peak demand:

  • Sample winter evenings 17:00 - 21:00.
    • Mean winter evening load:
      • find the average load across each circuit during the period
      • calculate the percentage contribution of each identified load type to this average peak load.
    • Maximum winter evening load
      • find the maximum half-hour demand for each household during the defined peak period
      • calculate the percentage contribution of each separately identifiable load type (lighting, hot water, heat pump, oven) in that half hour.
  • Regional/network peak. In this case we:
    • find the 100 maximum regional network (GXP) peak half hours
    • calculate the mean contribution of each identifiable load to mean total load across all households in that region across these 100 half-hours
  • Sample co-incident peak. In this case we:
    • find the half-hour across the sample which has the highest total combined demand
    • calculate mean contribution of each identifiable load to mean total load across all households in this half-hour

To do this last part we classify the circuit labels according to the load types mentioned above (see Table 8.1 in the Data Annex).

4.1 Winter (June - August) evenings 17:00 – 21:00

In this section we select the peak-period half hours for all households for the winter evening period and then calculate the mean demand for each dwelling over the period of peak demand.

Table 4.1 shows the winter mean demand (W) at ‘peak’ for each dwelling and circuit in 2015. The complete data table across all houses is saved as “Extracted mean demand by dwelling and circuit at ‘peak’.csv” and is supplied with the report.

Table 4.1: Example data: Extracted mean demand by dwelling and circuit at ‘peak’
linkID eecaCircuit avgPeakDemandW
rf_01 Heat Pump or Heating 2049.79
rf_01 Hot water 135.69
rf_01 Lighting 213.49
rf_01 Other 342.92
rf_01 Oven 70.21
rf_01 Total 2812.10
rf_06 Hot water 462.73
rf_06 Lighting 416.24
rf_06 Other 505.42
rf_06 Oven 144.91
Mean contribution at 'peak' (17:00-21:00) by circuit in winter 2015

Figure 4.1: Mean contribution at ‘peak’ (17:00-21:00) by circuit in winter 2015

Mean percentage load contribution at 'peak' (17:00-21:00) by circuit in winter 2015

Figure 4.2: Mean percentage load contribution at ‘peak’ (17:00-21:00) by circuit in winter 2015

We have then used this data to calculate the mean contribution of each identifiable load to peak demand (time period 17:00-21:00) across the sample for winter in 2015. This is shown in Figure 4.1 and Figure 4.2 (as percentage contribution). On this measure, of the identifiable loads, Heat Pumps contributed the most to peak demand, followed by Hot Water, Lighting, and Oven. However overall ‘Other’ loads contributed the most at ~41% suggesting further research is needed to disaggregate this demand where possible (see Table 8.1) for circuits contributing to ‘Other’.

4.2 Maximum load per season (W)

In this section we extract the half-hour which had the maximum total load during the evening period (17:00-21:00) for each household in season.

Table 4.2 shows the winter maximum load half-hours for each dwelling and year during the winter peak period as defined above. In this data extract, NaN indicates that no circuit data was obtained for this dwelling in this specific time period. We also calculate the proportionate contribution of each identifiable load to the total load. The complete data table across all houses is saved as “Extracted seasonal peak load half-hour circuits.csv” and is supplied with the report.

Table 4.2: Example data: Extracted winter peak load half-hour circuits (NA indicates no such circuit)
linkID year season r_dateTime_nz Heat Pump or Heating Hot water Lighting Other Oven Total pc_HW pc_HP pc_LI pc_OV pc_Other
rf_01 2014 Winter 2014-06-20 19:00:00 6330.77 0.00 738.02 2048.04 1296.61 10413.44 0.00 0.61 0.07 0.12 0.20
rf_01 2015 Winter 2015-08-09 18:30:00 7084.99 0.00 799.90 2260.26 0.00 10145.16 0.00 0.70 0.08 0.00 0.22
rf_02 2014 Winter 2014-07-26 19:30:00 453.76 445.71 253.77 2152.72 NA 3305.96 0.13 0.14 0.08 NA 0.65
rf_06 2014 Winter 2014-06-23 18:30:00 NA 0.00 1209.60 1093.66 3231.01 5534.26 0.00 NA 0.22 0.58 0.20
rf_06 2015 Winter 2015-08-25 18:30:00 NA 1971.90 1231.02 2723.79 425.52 6352.23 0.31 NA 0.19 0.07 0.43
rf_06 2016 Winter 2016-07-23 18:00:00 NA 1967.20 926.78 755.23 1558.86 5208.08 0.38 NA 0.18 0.30 0.15
rf_06 2017 Winter 2017-08-13 18:00:00 NA 1963.50 632.05 2137.17 1725.01 6457.72 0.30 NA 0.10 0.27 0.33
rf_06 2018 Winter 2018-06-06 17:00:00 NA 1920.51 345.87 2975.69 1901.05 7143.13 0.27 NA 0.05 0.27 0.42
rf_07 2014 Winter 2014-07-16 17:00:00 NA NA NA 2483.62 1945.33 4428.95 NA NA NA 0.44 0.56
rf_07 2015 Winter 2015-06-23 17:00:00 NA NA NA 4393.48 1284.66 5678.14 NA NA NA 0.23 0.77

We have then used this data to calculate the mean contribution of each identifiable load to peak demand (time period 17:00-21:00) for each season and year across the sample.

Results for 2015 are shown in Figure 4.3 and Figure 4.4 (as percentage contribution).

Mean contribution to peak demand (17:00-21:00) per season in 2015

Figure 4.3: Mean contribution to peak demand (17:00-21:00) per season in 2015

Mean percentage contribution to peak demand (17:00-21:00) for each season in 2015

Figure 4.4: Mean percentage contribution to peak demand (17:00-21:00) for each season in 2015

Figure 4.3 shows the seasonal variation in power demand especially for heat pumps and lighting but also shows the relative constancy of hot water’s contribution across the seasons. As a consequence the percentage contribution of hot water slightly increases in summer whereas the contribution of heat pumps decreases (see Figure 4.4). Hot water is identified as the appliance that is contributing the most to peak demand in this case. It should be noted that these mean values will mask considerable day to day and inter/intra-household variation. Note also that ‘Other’ almost certainly contains some forms of heating as it is much lower in summer (see the coding definitions in Table 8.1).

4.3 Region/network coincident peak

In this section we focus on the contribution of these identifiable loads to regional peak demand. As 22 of the GREENGrid houses are based in Taranaki and 20 houses in Hawke’s Bay with further 2 pilot dwellings in Otago, we focus on the first two regions by separating the sample into the Hawke’s Bay and Taranaki sub-samples.

Within the Taranaki sample, 31% of the houses had heat pumps installed, 45% hot water cylinders, and 27% other heat sources. In contrast, the Hawke’s Bay sub-sample 90% had heat pumps, 90% hot water cylinder, and 36% other heat sources. The very small sample sizes and recruiting approaches limit the representativeness of the sample.

Footnote: For further details see https://cfsotago.github.io/GREENGridData/householdAttributeProcessingReport_v1.0.html#51_main_heat_source and also ref to Part C

To determine the timing of the matching regional peaks, data on regional demand for the Hawke’s Bay and Taranaki Grid Exit Points (GXPs - see Table 4.3) was obtained from the Electricity Authority and for each GXP, the timestamps of the 100 half hours with the highest demand were identified. We then extracted the power demand of each dwelling in each of the two regions during these 100 half hours for analysis.

Table 4.3: GXPs used
node region name
CST0331 Taranaki
HUI0331 Taranaki
HWA0331 Taranaki
NPL0331 Taranaki
OPK0331 Taranaki
SFD0331 Taranaki
WGN0331 Taranaki
FHL0331 Hawke’s bay
RDF0331 Hawke’s bay
WTU0331 Hawke’s bay
## Date in ISO8601 format; converting timezone from UTC to "Pacific/Auckland".
## Date in ISO8601 format; converting timezone from UTC to "Pacific/Auckland".

4.3.1 Hawke’s Bay

Table 4.4 presents example data of the extracted peak half-hours by circuit for 2015 for a Hawke’s Bay dwellings. The complete data table is saved as “Extracted peak load half-hour circuits for Hawke’s Bay.csv” and is supplied with the report.

Table 4.4: Example data: Extracted peak load half-hour circuits for Hawke’s Bay (NaN indicates no such circuit)
linkID year season r_dateTime_nz Heat Pump or Heating Hot water Lighting Other Oven Total
rf_01 2015 Winter 2015-06-05 17:30:00 3276.65 0.00 354.83 306.55 0.00 3938.03
rf_01 2015 Winter 2015-06-08 17:30:00 3265.45 0.00 133.31 221.43 0.00 3620.19
rf_01 2015 Winter 2015-06-08 19:00:00 3377.16 0.00 157.63 282.54 0.00 3817.33
rf_01 2015 Winter 2015-06-15 17:30:00 4232.71 0.00 382.41 310.89 825.96 5751.97
rf_01 2015 Winter 2015-06-15 18:00:00 4064.93 0.00 328.44 297.37 128.42 4819.17
rf_01 2015 Winter 2015-06-16 17:30:00 4196.80 813.33 326.00 1098.91 6.66 6441.70
rf_01 2015 Winter 2015-06-17 17:30:00 3993.92 1042.07 319.77 132.13 0.00 5487.88
rf_01 2015 Winter 2015-06-17 18:30:00 4416.28 0.00 453.21 1058.01 605.07 6532.57
rf_01 2015 Winter 2015-06-17 19:30:00 3813.54 0.00 201.17 251.09 0.00 4265.79
rf_01 2015 Winter 2015-06-22 17:00:00 3866.76 0.00 434.06 319.35 0.00 4620.17

The mean contribution of each identifiable load to the Hawke’s Bay regional peak demand (100 half hours with the highest demand at Hawke’s Bay GXP) across the sample is shown in Figure 4.5. Hot Water and Heat Pumps contribute a mean of 682 Watts and 672 Watts respectively but ‘Other’ (which will include some heating see Table 8.1) contributes 792 W. Figure 4.6 shows the percentage contribution of each identifiable load to the regional peak. Heat Pumps and Hot Water contributed almost equally to regional network peak demand in Hawke’s Bay (27% and 28%), followed by Lighting (10%) and Oven (3%). ‘Other’ demand contributed 32%. It should be noted that the inherent bias in the sample, and the very small sample size in each region means that these % results are almost certainly not representative of a larger population.

Mean contribution of each identifiable load in the sample to the Hawke’s bay regional peak (100 half hours with the highest demand at Hawkes Bay GXP) for 2015

Figure 4.5: Mean contribution of each identifiable load in the sample to the Hawke’s bay regional peak (100 half hours with the highest demand at Hawkes Bay GXP) for 2015

Percentage contribution to peak demand for top 100 GXP half hours in Hawkes Bay for 2015

Figure 4.6: Percentage contribution to peak demand for top 100 GXP half hours in Hawkes Bay for 2015

4.3.2 Taranaki

Table 4.5 presents example data of the extracted peak half-hours by circuit for 2015 for the Taranaki houses. The complete data table is saved as “Extracted peak load half-hour circuits for Taranaki.csv” and is supplied with the report.

Table 4.5: Example data: Extracted peak load half-hour circuits (NaN indicates no such circuit)
linkID year season r_dateTime_nz Heat Pump or Heating Hot water Lighting Other Oven Total
rf_01 2015 Winter 2015-06-03 17:30:00 3217.26 0 627.81 480.53 1520.99 5846.57
rf_01 2015 Winter 2015-06-03 18:00:00 2626.62 0 486.23 183.88 0.00 3296.74
rf_01 2015 Winter 2015-06-22 17:30:00 3672.64 0 568.55 593.82 284.81 5119.82
rf_01 2015 Winter 2015-06-22 18:00:00 3884.40 0 670.60 196.28 1227.56 5978.85
rf_01 2015 Winter 2015-06-22 18:30:00 3415.85 0 702.64 172.78 1255.81 5547.09
rf_01 2015 Winter 2015-06-23 17:30:00 4049.44 0 501.81 720.67 0.00 5271.92
rf_01 2015 Winter 2015-06-23 18:00:00 4404.86 0 346.77 419.84 0.00 5171.47
rf_01 2015 Winter 2015-06-23 18:30:00 5842.13 0 404.60 1360.91 0.00 7607.64
rf_01 2015 Winter 2015-06-24 17:30:00 4318.96 0 582.43 180.04 175.79 5257.22
rf_01 2015 Winter 2015-06-24 18:00:00 4126.43 0 579.92 571.14 843.46 6120.95

The mean contribution by identifiable load to the regional peak across the sample is presented in Figure 4.7. Figure 4.8 shows the percentage contribution to peak demand. Lighting contributes the most to peak demand with 25%, followed by Heat Pumps (23%), Hot Water (14%), and Oven (8%). ‘Other’ loads contribute 30% to peak demand in Taranaki.

Mean contribution of each identifiable load to peak demand in Taranaki in 2015

Figure 4.7: Mean contribution of each identifiable load to peak demand in Taranaki in 2015

Percentage contribution to demand during top 100 GXP half hours in Taranaki for 2015

Figure 4.8: Percentage contribution to demand during top 100 GXP half hours in Taranaki for 2015

4.4 Sample coincident peak

In this section the sum of half-hourly demand over all dwellings in the GREENGrid sample is used to define peak demand. We define the peak as the 20 half hours with the highest total half-hourly demand summed across all dwellings, which we refer to as the sample coincident peak. This is in contrast to Section 4.1 where peak demand was predefined as the time between 17:00 and 21:00 in winter and section 4.2 where peak demand was predefined as the 100 half hours with the largest demand based on regional GXP data.

Table 4.6 identifies the half hours of highest overall demand in 2015 using the sum of the half-hourly mean power values (sumOfmeanPowerW). As we can see the number of dwellings contributing to this sum is between 31 and 33 in each half hour and the table is sorted in descending order of the mean total power across all contributing dwellings. We control for ‘missing dwellings’ by sorting by and using the mean total power (last column) as our indicator. The complete data table is saved as “Extracted winter peak load half-hours in descending order for 2015” and is supplied with the report.

Table 4.6: Example data: Extracted winter peak load half-hours in descending order for 2015
eecaCircuit date season year obsHalfHour sumOfmeanPowerW nDwellings averagePowerW
Total 2015-06-28 Winter 2015 18:00:00 104001.93 32 3250.06
Total 2015-08-21 Winter 2015 07:00:00 98248.54 31 3169.31
Total 2015-06-23 Winter 2015 18:00:00 104026.60 33 3152.32
Total 2015-06-24 Winter 2015 07:00:00 103284.24 33 3129.83
Total 2015-05-29 Autumn 2015 07:00:00 104143.56 35 2975.53
Total 2015-06-17 Winter 2015 07:00:00 97474.05 33 2953.76
Total 2015-08-12 Winter 2015 07:00:00 91424.73 31 2949.18
Total 2015-06-23 Winter 2015 17:30:00 97292.94 33 2948.27
Total 2015-06-26 Winter 2015 07:00:00 97153.23 33 2944.04
Total 2015-06-25 Winter 2015 07:30:00 96818.35 33 2933.89

Figure 4.9 shows the mean contribution of each identifiable load for the sample to the top 20 identified peak half hours cross the sample. The results show that on average Heat Pumps contribute the most, followed by Hot Water and Lighting. The plot also shows that ‘Other’ has a large contribution. Again, these results should be viewed with some caution due to the non-representative nature of the GREEN Grid sample. While they represent the sample co-incident peak contributions, we cannot assume that this is representative of all New Zealand dwellings.

Mean appliance contribution to peak demand for the top 20 half hours in the sample (ordered by total load)

Figure 4.9: Mean appliance contribution to peak demand for the top 20 half hours in the sample (ordered by total load)

5 Annual Contribution

This section presents annual and seasonal energy consumption (in kWh) for each identifiable load. This analysis considers the year 2015. Figure 5.1 shows the annual total energy consumption (in kWh) for the identifiable loads in a box and whisker plot to show the median, 25%/75% quantiles, whiskers and outliers. Hot Water consumes the most energy per year with a pronounced variation between houses. Lighting, Heat Pump, and Oven follow. “Other” clearly drive large inter-household variation and, as noted above, should be a focus of further work.

Box and whisker plot of annual energy consumption (per house) of each identifiable load for 2015

Figure 5.1: Box and whisker plot of annual energy consumption (per house) of each identifiable load for 2015

Figure 5.1 conceals the significant variation in demand between seasons and in the following we use density plots to show the shape of the distribution for each circuit by season.

Figure 5.2 shows the distribution of seasonal energy consumption in kWh across all houses for Hot Water in 2015 using a density plot. This shows that most energy consumption for Hot Water is in winter, followed by spring and autumn. Energy consumption for hot water in summer is substantially lower with a distinctively different pattern to both the spring/autumn seasons and winter.

Example histogram saved as .png

Distribution of seasonal energy consumption for Hot Water for all houses for 2015

Figure 5.2: Distribution of seasonal energy consumption for Hot Water for all houses for 2015

## Saving 6 x 5 in image
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

In contrast, Figure 5.3 presents a similar density plot for Heat Pumps. As expected, most energy consumption is in winter. In summer, total energy consumption is mostly 0 (appliance is turned off). Only a few observations registered energy consumption in summer which may be cooling.

Distribution of seasonal energy consumption for Heat Pumps for all houses for 2015

Figure 5.3: Distribution of seasonal energy consumption for Heat Pumps for all houses for 2015

Energy consumption of Lighting is particularly apparent in spring, autumn, and winter as presented in Figure 5.4. Less energy consumption is identified in summer.

Distribution of seasonal energy consumption for Lighting for all houses for 2015

Figure 5.4: Distribution of seasonal energy consumption for Lighting for all houses for 2015

For ovens, there is less seasonal variation in seasonal energy consumption as shown in Figure 5.5. Again, energy consumption in summer is less than in other seasons.

Distribution of seasonal energy consumption for Ovens for all houses for 2015

Figure 5.5: Distribution of seasonal energy consumption for Ovens for all houses for 2015

For “Other”, there is a lot of seasonal variation in seasonal energy consumption as shown in Figure 5.6. As this circuit contains appliances not further specified it is difficult to identify the appliance causing this energy consumption, particularly in summer. Therefore, further research is necessary.

Distribution of seasonal energy consumption for Other for all houses for 2015

Figure 5.6: Distribution of seasonal energy consumption for Other for all houses for 2015

Distribution of winter 2015 total energy consumption for all circuits for all houses

Figure 5.7: Distribution of winter 2015 total energy consumption for all circuits for all houses

Finally, Figure 5.7 shows the variation in all circuits for winter 2015. On average, Hot Water used the most energy, followed by Heat Pumps, Lighting, and Ovens but ‘Other’ shows a wide variation which again warrants further investigation.

6 Load Factor

The Load Factor (LF) is defined as the ratio of mean demand (W) and the peak demand (W) for each load. In this section we define peak demand to be the mean demand between 17:00-21:00 in winter. The LF provides a measure of how much the load contributes to peak. If the LF for a particular load is 1 then the load is flat. If the LF is less than 1 this shows that the load disproportionately contributes to the peak. Note that values greater than 1 indicate that demand during the peak is reduced below the mean. An alternative measure is given by the conservation load factor defined by:

CLF = Peak W/((Average W*8760)/1000)

The CLF represents the ratio of the power demand at peak to the annual energy consumption over the year (in W/kWh). The advantage of the CLF is that is gives a larger value when the load makes larger contribution to the peak. Table 6.1 shows the first rows of our calculation of LF and CLF.

Table 6.1: Example data: Extracted load factor by household and circuit
linkID eecaCircuit avgPeakDemandW avgDemandW LoadFactor CLF
rf_06 Hot water 462.73 405.74 0.88 0.13
rf_06 Lighting 416.24 161.38 0.39 0.29
rf_06 Other 505.42 437.39 0.87 0.13
rf_06 Oven 144.91 24.02 0.17 0.69
rf_06 Total 1539.35 1049.32 0.68 0.17
rf_13 Heat Pump or Heating 972.10 179.94 0.19 0.62

The full data table containing LFs and CLFs (if available) for each house is saved as “Extracted load factor by household and circuit.csv” and supplied with the report.

Figure 6.1 shows the Conservation Load Factor (CLF) for each identifiable load averaged over all houses in the sample. Results show that the CLF for Heat Pumps (0.55) is the highest, followed by Oven (0.43), Lighting (0.38), and Hot Water (0.17). ‘Other’ had a CLF of 0.24.

Mean Conservation Load Factor by circuit for peak demand (17:00-21:00) in winter 2015

Figure 6.1: Mean Conservation Load Factor by circuit for peak demand (17:00-21:00) in winter 2015

Note that these numbers are means over all households, dates, and times for 2015. This means that each household contributes equally to the mean and it is not weighted by its total demand. For example, the load factor from households with very low hot water demand will contribute equally to the mean.

In addition, it is clear that the mean CLF over all houses is skewed by some houses with CLF > 0.9 as Figure 6.2 shows.

Box and whiskers plot of Conservation Load Factor distribution by circuit for peak demand (17:00-21:00) in winter 2015

Figure 6.2: Box and whiskers plot of Conservation Load Factor distribution by circuit for peak demand (17:00-21:00) in winter 2015

7 Summary

This report has used the GREEN Grid sample of circuit-level household electricity demand data to analyse the contribution of heat pumps, hot water, lighting, and ovens to peak demand. Calculations have been carried out using a variety of definitions of “peak”. In addition, we also calculated the annual energy consumption of each identifiable load in the sample and a conservation load factor which is a measure of peak demand to annual energy consumption for each identifiable load.

The results show plausible results, however there are a number of key considerations in extrapolating these results:

  1. Unidentified loads represented a significant contribution in the sample

  2. Means calculated over the sample can significantly distort the results

  3. The non-representative nature of the sample means that the results cannot be considered to be representative of New Zealand households

These short comings suggest that future work should focus on (1) collecting data from a more representative sample of New Zealand households, (2) ensuring that appliances are identified on circuits (especially electric heaters); (3) variation across the sample be accounted for in any results.

8 Data Annex

8.1 Categorised circuits

Table 8.1 shows the categorised circuit labels used in this analysis. It would be relatively easy to adjust these definitions in future work if required.

Table 8.1: Definition of ‘eeca circuits’ (columns) based on original circuits (rows). Values are the count of half-hours in the complete power data
Heat Pump or Heating Hot water Lighting Other Oven Total
Calculated_other 0 0 0 1545817 0 0
Heat Pump$2092 51639 0 0 0 0 0
Heat Pump$2148 32019 0 0 0 0 0
Heat Pump$2598 60754 0 0 0 0 0
Heat Pump$2826 30311 0 0 0 0 0
Heat Pump$4124 26083 0 0 0 0 0
Heat Pump$4130 32529 0 0 0 0 0
Heat Pump$4134 58798 0 0 0 0 0
Heat Pump$4150 53554 0 0 0 0 0
Heat Pump$4154 58753 0 0 0 0 0
Heat Pump$4160 27332 0 0 0 0 0
Heat Pump$4175 29556 0 0 0 0 0
Heat Pump$4190 45806 0 0 0 0 0
Heat Pump$4196 18044 0 0 0 0 0
Heat Pump$4204 58693 0 0 0 0 0
Heat Pump$4219 2885 0 0 0 0 0
Heat Pump$4223 24373 0 0 0 0 0
Heating$1576 19412 0 0 0 0 0
Heating$1633 28401 0 0 0 0 0
Hot Water (2 elements)$4247 0 51274 0 0 0 0
Hot Water - Controlled (HEMS)$2081 0 72954 0 0 0 0
Hot Water - Controlled$2094 0 51639 0 0 0 0
Hot Water - Controlled$2102 0 70291 0 0 0 0
Hot Water - Controlled$2110 0 18124 0 0 0 0
Hot Water - Controlled$2129 0 18032 0 0 0 0
Hot Water - Controlled$2150 0 32019 0 0 0 0
Hot Water - Controlled$2208 0 72683 0 0 0 0
Hot Water - Controlled$2236 0 62880 0 0 0 0
Hot Water - Controlled$2248 0 62810 0 0 0 0
Hot Water - Controlled$2679 0 12416 0 0 0 0
Hot Water - Controlled$2825 0 30311 0 0 0 0
Hot Water - Controlled$4135 0 58798 0 0 0 0
Hot Water - Controlled$4144 0 53402 0 0 0 0
Hot Water - Controlled$4155 0 58753 0 0 0 0
Hot Water - Controlled$4158 0 27332 0 0 0 0
Hot Water - Controlled$4167 0 11618 0 0 0 0
Hot Water - Controlled$4178 0 29556 0 0 0 0
Hot Water - Controlled$4184 0 58353 0 0 0 0
Hot Water - Controlled$4198 0 18044 0 0 0 0
Hot Water - Controlled$4200 0 58693 0 0 0 0
Hot Water - Controlled$4238 0 24801 0 0 0 0
Hot Water - Uncontrolled$4125 0 26083 0 0 0 0
Hot Water - Uncontrolled$4131 0 32529 0 0 0 0
Hot Water - Uncontrolled$4147 0 53554 0 0 0 0
Hot Water - Uncontrolled$4224 0 24373 0 0 0 0
Hot Water Cpbd Heater- Cont$2586 0 70927 0 0 0 0
Hot Water$1574 0 19412 0 0 0 0
Hot water$1636 0 28401 0 0 0 0
Hot Water$3952 0 13040 0 0 0 0
imputedTotalDemand_circuitsToSum_v1.1 0 0 0 0 0 1563422
Incomer 1 - Hot Water - Cont$2626 0 13310 0 0 0 0
Lighting (inc heat lamps)$4129 0 0 32529 0 0 0
Lighting & 2 Towel Rail$4245 0 0 51274 0 0 0
Lighting 1/2$5623 0 0 9153 0 0 0
Lighting 2/2$5622 0 0 9153 0 0 0
Lighting$2232 0 0 62880 0 0 0
Lighting$2244 0 0 62810 0 0 0
Lighting$4123 0 0 26083 0 0 0
Lighting$4133 0 0 58798 0 0 0
Lighting$4142 0 0 53402 0 0 0
Lighting$4149 0 0 53554 0 0 0
Lighting$4153 0 0 58753 0 0 0
Lighting$4159 0 0 27332 0 0 0
Lighting$4165 0 0 11618 0 0 0
Lighting$4172 0 0 19625 0 0 0
Lighting$4176 0 0 29556 0 0 0
Lighting$4183 0 0 58353 0 0 0
Lighting$4189 0 0 45806 0 0 0
Lighting$4197 0 0 18044 0 0 0
Lighting$4203 0 0 58693 0 0 0
Lighting$4218 0 0 2885 0 0 0
Lighting$4222 0 0 24373 0 0 0
Lighting$4236 0 0 24801 0 0 0
Lights$1577 0 0 19412 0 0 0
Lights$1635 0 0 28401 0 0 0
Oven & Hob$2091 0 0 0 0 51639 0
Oven & Hob$2103 0 0 0 0 70291 0
Oven & Hob$2210 0 0 0 0 72683 0
Oven & Hob$2247 0 0 0 0 62810 0
Oven & Hobb$4237 0 0 0 0 24801 0
Oven & Kitchen Appliances$2108 0 0 0 0 18124 0
Oven & Oven Wall Appliances$2827 0 0 0 0 30311 0
Oven, Hob & Microwave$4141 0 0 0 0 53402 0
Oven$2085 0 0 0 0 72954 0
Oven$2132 0 0 0 0 18032 0
Oven$2235 0 0 0 0 62880 0
Oven$2600 0 0 0 0 60754 0
Oven$2629 0 0 0 0 13310 0
Oven$2724 0 0 0 0 67153 0
Oven$2736 0 0 0 0 70345 0
Oven$2749 0 0 0 0 33684 0
Oven$3953 0 0 0 0 13040 0
Oven$4182 0 0 0 0 58353 0
Oven$4191 0 0 0 0 45806 0
Oven$4246 0 0 0 0 51274 0
Range$1637 0 0 0 0 28401 0
Theatre Heat Pump$2740 70345 0 0 0 0 0
Upstairs Heat Pumps$2211 72683 0 0 0 0 0
Wall Oven$4169 0 0 0 0 19625 0

8.2 Original data description

Descriptive statistics for aggregate half hourly power data for all households and all circuits:

## Skim summary statistics
##  n obs: 6994581 
##  n variables: 23 
## 
## ── Variable type:character ──────────────────────────────────────────────────────────────────────
##            variable missing complete       n min max empty n_unique
##             ba_peak       0  6994581 6994581  14  16     0        4
##             circuit       0  6994581 6994581   9  37     0       99
##           circuitID 3109239  3885342 6994581   4   4     0       97
##        circuitLabel       0  6994581 6994581   4  37     0       27
##         eecaCircuit       0  6994581 6994581   4  20     0        6
##     eecaCircuitOrig       0  6994581 6994581   4  20     0        6
##              linkID       0  6994581 6994581   5   6     0       40
##                peak       0  6994581 6994581   4  10     0        3
##  r_dateTimeHalfHour       0  6994581 6994581  20  20     0    77345
##              season       0  6994581 6994581   6   6     0        4
## 
## ── Variable type:Date ───────────────────────────────────────────────────────────────────────────
##  variable missing complete       n        min        max     median
##      date       0  6994581 6994581 2014-01-06 2018-08-01 2016-03-21
##  n_unique
##      1613
## 
## ── Variable type:difftime ───────────────────────────────────────────────────────────────────────
##     variable missing complete       n    min        max   median n_unique
##  obsHalfHour       0  6994581 6994581 0 secs 84600 secs 12:00:00       48
## 
## ── Variable type:integer ────────────────────────────────────────────────────────────────────────
##  variable missing complete       n  mean   sd p0 p25 p50 p75 p100     hist
##      hour       0  6994581 6994581 11.5  6.92  0   6  12  18   23 ▇▇▇▇▇▇▇▇
##      nObs       0  6994581 6994581 29.98 0.6   1  30  30  30   62 ▁▁▁▇▁▁▁▁
## 
## ── Variable type:numeric ────────────────────────────────────────────────────────────────────────
##       variable missing complete       n       mean         sd       p0
##      maxPowerW 1585024  5409557 6994581     724.64    1291.09     0   
##   meanEnergyWh  122032  6872549 6994581     210.04     365.81 -1897.14
##     meanPowerW  122032  6872549 6994581     420.09     731.62 -3794.28
##      minPowerW 1627148  5367433 6994581     193.51     507.04     0   
##          month       0  6994581 6994581       6.49       3.33     1   
##       sdPowerW 1546109  5448472 6994581     185.37     375.63     0   
##  totalEnergyWh       0  6994581 6994581 2879611.11 3059523.96     0   
##           year       0  6994581 6994581    2015.85       1.15  2014   
##        p25        p50        p75        p100     hist
##       0         17.54     777.52    27759    ▇▁▁▁▁▁▁▁
##       0         69.21     244.88     5490.79 ▁▁▇▁▁▁▁▁
##       0        138.42     489.77    10981.59 ▁▁▇▁▁▁▁▁
##       0          0        160.49     9600.58 ▇▁▁▁▁▁▁▁
##       4          6          9          12    ▆▃▇▅▅▇▃▆
##       0          0.72     109.08     5068.08 ▇▁▁▁▁▁▁▁
##  519127.83 1943378.84 4192192.63 15455703.3  ▇▃▂▁▁▁▁▁
##    2015       2016       2017        2018    ▃▇▁▆▁▅▁▂
## 
## ── Variable type:POSIXct ────────────────────────────────────────────────────────────────────────
##       variable missing complete       n        min        max     median
##  r_dateTime_nz       0  6994581 6994581 2014-01-06 2018-08-01 2016-03-21
##  n_unique
##     77345

The following tables show descriptive statistics for the meanPowerW values for each circuit by household.

Table 8.2: rf_01: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 327.52 35.63 4263.54 28401
Heating$1633 Heat Pump or Heating 960.24 0.00 7084.99 28401
Hot water$1636 Hot water 216.75 0.00 1874.65 28401
Lights$1635 Lighting 118.30 0.00 1102.66 28401
Range$1637 Oven 39.21 0.00 3550.98 28401
imputedTotalDemand_circuitsToSum_v1.1 Total 1662.02 90.72 10981.59 28401
Table 8.2: rf_02: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 302.54 -11.91 3923.84 19412
Heating$1576 Heat Pump or Heating 160.75 0.00 3360.73 19412
Hot Water$1574 Hot water 234.30 0.00 2215.74 19412
Lights$1577 Lighting 23.67 0.00 559.34 19412
imputedTotalDemand_circuitsToSum_v1.1 Total 721.26 25.47 7427.87 19412
Table 8.2: rf_06: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 449.68 -1293.19 3121.98 62810
Hot Water - Controlled$2248 Hot water 413.59 0.00 2055.40 62810
Lighting$2244 Lighting 117.44 0.00 2160.54 62810
Oven & Hob$2247 Oven 20.30 0.00 3919.07 62810
imputedTotalDemand_circuitsToSum_v1.1 Total 1069.98 0.15 7143.13 62810
Table 8.2: rf_07: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 500.27 20.43 4603.19 67153
Oven$2724 Oven 104.30 0.00 3399.99 67153
imputedTotalDemand_circuitsToSum_v1.1 Total 604.57 20.43 5912.32 67153
Table 8.2: rf_08: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 657.29 160.3 5419.33 51639
Heat Pump$2092 Heat Pump or Heating 67.13 0.0 2036.82 51639
Hot Water - Controlled$2094 Hot water 272.31 0.0 2366.14 51639
Oven & Hob$2091 Oven 48.22 0.0 3480.85 51639
imputedTotalDemand_circuitsToSum_v1.1 Total 1044.94 244.9 7882.45 51639
Table 8.2: rf_09: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
imputedTotalDemand_circuitsToSum_v1.1 Total 648.59 13.82 5490.64 17605
Table 8.2: rf_10: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 518.96 89.53 4936.06 60754
Heat Pump$2598 Heat Pump or Heating 48.32 0.00 2510.32 60754
Oven$2600 Oven 28.89 0.00 2444.98 60754
imputedTotalDemand_circuitsToSum_v1.1 Total 596.17 89.53 6202.29 60754
Table 8.2: rf_11: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 469.03 -35.53 8647.10 70927
Hot Water Cpbd Heater- Cont$2586 Hot water 76.91 0.00 1955.71 70927
imputedTotalDemand_circuitsToSum_v1.1 Total 545.94 22.53 8698.01 70927
Table 8.2: rf_12: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 255.26 3.26 2551.36 13310
Incomer 1 - Hot Water - Cont$2626 Hot water 431.69 0.00 3057.67 13310
Oven$2629 Oven 93.48 0.00 3676.90 13310
imputedTotalDemand_circuitsToSum_v1.1 Total 780.43 48.00 6001.54 13310
Table 8.2: rf_13: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 1003.64 141.73 6217.79 72683
Hot Water - Controlled$2208 Hot water 198.86 0.00 2311.01 72683
Oven & Hob$2210 Oven 107.58 0.00 3689.63 72683
Upstairs Heat Pumps$2211 Heat Pump or Heating 150.10 0.00 2762.93 72683
imputedTotalDemand_circuitsToSum_v1.1 Total 1455.80 141.73 9575.83 72683
Table 8.2: rf_15b: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 813.38 -341.47 5778.82 13040
Hot Water$3952 Hot water 411.25 0.00 1998.15 13040
Oven$3953 Oven 31.02 0.00 1648.31 13040
imputedTotalDemand_circuitsToSum_v1.1 Total 1255.78 28.38 7318.50 13040
Table 8.2: rf_16: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 238.69 22.81 3447.71 12416
Hot Water - Controlled$2679 Hot water 299.69 0.00 2327.90 12416
imputedTotalDemand_circuitsToSum_v1.1 Total 538.38 23.86 4486.01 12416
Table 8.2: rf_17a: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 412.59 0.22 5095.52 32019
Heat Pump$2148 Heat Pump or Heating 25.98 0.00 3489.12 32019
Hot Water - Controlled$2150 Hot water 88.40 0.00 2056.73 32019
imputedTotalDemand_circuitsToSum_v1.1 Total 526.98 0.22 7611.20 32019
Table 8.2: rf_17b: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 294.45 42.6 2674.32 9153
Lighting 1/2$5623 Lighting 0.00 0.0 14.60 9153
Lighting 2/2$5622 Lighting 7.88 0.0 166.44 9153
imputedTotalDemand_circuitsToSum_v1.1 Total 353.67 42.6 3819.87 9153
Table 8.2: rf_18: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 1053.84 34.91 7510.38 18032
Hot Water - Controlled$2129 Hot water 348.43 0.00 2107.45 18032
Oven$2132 Oven 36.55 0.00 2143.60 18032
imputedTotalDemand_circuitsToSum_v1.1 Total 1444.29 34.91 10051.11 18032
Table 8.2: rf_19: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 589.51 -433.60 5541.26 70345
Oven$2736 Oven 0.35 0.00 1698.06 70345
Theatre Heat Pump$2740 Heat Pump or Heating 3.03 0.00 999.09 70345
imputedTotalDemand_circuitsToSum_v1.1 Total 593.80 0.24 5541.26 70345
Table 8.2: rf_20: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 277.20 -321.81 3179.27 18124
Hot Water - Controlled$2110 Hot water 274.16 0.00 3163.17 18124
Oven & Kitchen Appliances$2108 Oven 262.49 39.13 3397.60 18124
imputedTotalDemand_circuitsToSum_v1.1 Total 814.12 4.67 7239.91 18124
Table 8.2: rf_21: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 456.46 56.12 5653.11 33684
Oven$2749 Oven 26.93 0.00 2183.97 33684
imputedTotalDemand_circuitsToSum_v1.1 Total 483.39 56.12 5653.11 33684
Table 8.2: rf_22: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 603.91 -96.01 4462.45 62880
Hot Water - Controlled$2236 Hot water 355.44 0.00 2050.54 62880
Lighting$2232 Lighting 300.74 0.00 3411.40 62880
Oven$2235 Oven 31.57 0.00 2339.33 62880
imputedTotalDemand_circuitsToSum_v1.1 Total 1291.68 61.51 8019.17 62880
Table 8.2: rf_23: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 848.70 -984.17 5256.37 72954
Hot Water - Controlled (HEMS)$2081 Hot water 256.58 0.00 1459.96 72954
Oven$2085 Oven 38.78 0.00 3301.91 72954
imputedTotalDemand_circuitsToSum_v1.1 Total 1161.19 0.06 6676.90 72954
Table 8.2: rf_24: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 111.57 -3794.28 2180.49 70291
Hot Water - Controlled$2102 Hot water 464.31 0.00 3196.60 70291
Oven & Hob$2103 Oven 47.12 0.00 3357.08 70291
imputedTotalDemand_circuitsToSum_v1.1 Total 710.17 0.01 6319.66 70291
Table 8.2: rf_27: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 663.59 -46.69 5195.86 30311
Heat Pump$2826 Heat Pump or Heating 138.45 0.00 2457.08 30311
Hot Water - Controlled$2825 Hot water 278.22 0.00 1625.14 30311
Oven & Oven Wall Appliances$2827 Oven 38.18 0.00 2495.70 30311
imputedTotalDemand_circuitsToSum_v1.1 Total 1118.45 138.39 6806.33 30311
Table 8.2: rf_28: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 241.01 -802.87 3598.54 2885
Heat Pump$4219 Heat Pump or Heating 51.90 0.00 2463.96 2885
Lighting$4218 Lighting 32.80 0.00 226.41 2885
imputedTotalDemand_circuitsToSum_v1.1 Total 352.21 0.79 4676.19 2885
Table 8.2: rf_29: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 1150.31 133.32 4942.40 58353
Hot Water - Controlled$4184 Hot water 341.67 0.00 3242.10 58353
Lighting$4183 Lighting 87.80 0.00 740.62 58353
Oven$4182 Oven 26.90 0.00 3484.20 58353
imputedTotalDemand_circuitsToSum_v1.1 Total 1606.68 136.15 8395.40 58353
Table 8.2: rf_30: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 411.64 -336.41 3460.16 24801
Hot Water - Controlled$4238 Hot water 190.49 0.00 1473.25 24801
Lighting$4236 Lighting 114.89 0.00 1440.13 24801
Oven & Hobb$4237 Oven 26.52 0.00 2908.37 24801
imputedTotalDemand_circuitsToSum_v1.1 Total 743.54 115.76 5173.55 24801
Table 8.2: rf_31: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 381.53 -31.36 5846.41 58693
Heat Pump$4204 Heat Pump or Heating 127.50 0.00 2462.60 58693
Hot Water - Controlled$4200 Hot water 59.08 0.00 1917.64 58693
Lighting$4203 Lighting 74.21 0.00 1299.30 58693
imputedTotalDemand_circuitsToSum_v1.1 Total 642.32 39.79 7101.95 58693
Table 8.2: rf_32: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 303.81 -2356.33 5375.93 18044
Heat Pump$4196 Heat Pump or Heating 67.81 0.00 2470.51 18044
Hot Water - Controlled$4198 Hot water 283.86 0.00 1480.45 18044
Lighting$4197 Lighting 22.24 0.00 751.78 18044
imputedTotalDemand_circuitsToSum_v1.1 Total 677.71 0.00 7882.02 18044
Table 8.2: rf_33: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 463.38 143.76 4612.96 53402
Hot Water - Controlled$4144 Hot water 288.82 0.00 2147.54 53402
Lighting$4142 Lighting 24.98 0.00 731.35 53402
Oven, Hob & Microwave$4141 Oven 37.42 0.00 3614.15 53402
imputedTotalDemand_circuitsToSum_v1.1 Total 814.59 143.76 7016.92 53402
Table 8.2: rf_34: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 536.46 0 5381.39 24373
Heat Pump$4223 Heat Pump or Heating 196.47 0 4982.93 24373
Hot Water - Uncontrolled$4224 Hot water 329.87 0 3901.05 24373
Lighting$4222 Lighting 96.63 0 1078.36 24373
imputedTotalDemand_circuitsToSum_v1.1 Total 1159.43 0 9469.69 24373
Table 8.2: rf_35: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 968.25 79.66 4605.89 26083
Heat Pump$4124 Heat Pump or Heating 58.92 0.00 1329.50 26083
Hot Water - Uncontrolled$4125 Hot water 238.40 0.00 2967.40 26083
Lighting$4123 Lighting 74.64 0.00 869.86 26083
imputedTotalDemand_circuitsToSum_v1.1 Total 1340.14 118.81 7202.18 26083
Table 8.2: rf_36: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 379.30 19.25 6330.17 53554
Heat Pump$4150 Heat Pump or Heating 104.85 0.00 2566.76 53554
Hot Water - Uncontrolled$4147 Hot water 296.37 0.00 3137.19 53554
Lighting$4149 Lighting 49.73 0.00 677.31 53554
imputedTotalDemand_circuitsToSum_v1.1 Total 830.32 20.04 9557.46 53554
Table 8.2: rf_37: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 230.49 64.58 3092.90 58798
Heat Pump$4134 Heat Pump or Heating 49.80 0.00 2224.39 58798
Hot Water - Controlled$4135 Hot water 287.49 0.00 3152.76 58798
Lighting$4133 Lighting 15.30 0.00 520.41 58798
imputedTotalDemand_circuitsToSum_v1.1 Total 583.08 68.56 5955.63 58798
Table 8.2: rf_38: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 268.71 52.30 3196.98 29556
Heat Pump$4175 Heat Pump or Heating 248.58 0.00 2451.64 29556
Hot Water - Controlled$4178 Hot water 486.41 0.00 3058.45 29556
Lighting$4176 Lighting 53.77 0.00 728.80 29556
imputedTotalDemand_circuitsToSum_v1.1 Total 1058.88 53.87 6621.28 29556
Table 8.2: rf_39: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 1195.70 141.60 7087.00 51274
Hot Water (2 elements)$4247 Hot water 394.89 0.00 3317.47 51274
Lighting & 2 Towel Rail$4245 Lighting 278.26 0.00 2101.95 51274
Oven$4246 Oven 51.45 0.00 3053.34 51274
imputedTotalDemand_circuitsToSum_v1.1 Total 1920.30 142.29 10760.55 51274
Table 8.2: rf_40: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 710.94 45.52 6830.30 11618
Hot Water - Controlled$4167 Hot water 336.39 0.00 1991.92 11618
Lighting$4165 Lighting 144.25 0.00 792.75 11618
imputedTotalDemand_circuitsToSum_v1.1 Total 1191.58 46.73 7855.85 11618
Table 8.2: rf_41: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 779.07 93.28 6670.59 45806
Heat Pump$4190 Heat Pump or Heating 51.10 0.00 3579.52 45806
Lighting$4189 Lighting 149.18 0.00 1783.12 45806
Oven$4191 Oven 35.12 0.00 2443.12 45806
imputedTotalDemand_circuitsToSum_v1.1 Total 1014.47 100.08 7580.26 45806
Table 8.2: rf_42: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 455.56 49.21 4106.38 32529
Heat Pump$4130 Heat Pump or Heating 44.58 0.00 2394.09 32529
Hot Water - Uncontrolled$4131 Hot water 369.39 0.00 3082.22 32529
Lighting (inc heat lamps)$4129 Lighting 361.13 0.00 3528.91 32529
imputedTotalDemand_circuitsToSum_v1.1 Total 1230.65 78.11 9511.44 32529
Table 8.2: rf_44: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 409.63 77.38 4375.47 58753
Heat Pump$4154 Heat Pump or Heating 97.92 0.00 2088.85 58753
Hot Water - Controlled$4155 Hot water 477.60 0.00 3317.72 58753
Lighting$4153 Lighting 94.66 0.00 1485.10 58753
imputedTotalDemand_circuitsToSum_v1.1 Total 1079.81 77.38 9833.22 58753
Table 8.2: rf_45: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 278.00 30.58 3408.98 27332
Heat Pump$4160 Heat Pump or Heating 94.24 0.00 2654.29 27332
Hot Water - Controlled$4158 Hot water 316.90 0.00 3096.38 27332
Lighting$4159 Lighting 82.99 0.00 1686.92 27332
imputedTotalDemand_circuitsToSum_v1.1 Total 772.13 30.58 7298.49 27332
Table 8.2: rf_47: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit eecaCircuit meanPowerW minPowerW maxPowerW nObs
Calculated_other Other 361.17 67.95 4171.83 19625
Lighting$4172 Lighting 22.70 0.00 1089.85 19625
Wall Oven$4169 Oven 26.47 0.00 2473.26 19625
imputedTotalDemand_circuitsToSum_v1.1 Total 415.53 67.95 6192.58 19625

9 Runtime

Analysis completed in 111.89 seconds ( 1.86 minutes) using knitr in RStudio with R version 3.5.2 (2018-12-20) running on x86_64-apple-darwin15.6.0.

10 R environment

10.1 R packages used

  • base R (R Core Team 2016)
  • bookdown (Xie 2016a)
  • data.table (Dowle et al. 2015)
  • ggplot2 (Wickham 2009)
  • kableExtra (Zhu 2018)
  • knitr (Xie 2016b)
  • lubridate (Grolemund and Wickham 2011)
  • rmarkdown (Allaire et al. 2018)

10.2 Session info

## R version 3.5.2 (2018-12-20)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS High Sierra 10.13.6
## 
## Matrix products: default
## BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_NZ.UTF-8/en_NZ.UTF-8/en_NZ.UTF-8/C/en_NZ.UTF-8/en_NZ.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] readr_1.3.1              dplyr_0.8.3             
##  [3] tidyr_1.0.0              skimr_1.0.7             
##  [5] hms_0.5.1                kableExtra_1.1.0        
##  [7] ggplot2_3.2.1            drake_7.7.0             
##  [9] bookdown_0.14            rmarkdown_1.16          
## [11] GREENGridEECA_0.0.0.9000 GREENGridData_1.0       
## [13] lubridate_1.7.4          here_0.1                
## [15] data.table_1.12.6       
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.2        txtq_0.2.0        prettyunits_1.0.2
##  [4] assertthat_0.2.1  zeallot_0.1.0     rprojroot_1.3-2  
##  [7] digest_0.6.22     packrat_0.5.0     utf8_1.1.4       
## [10] R6_2.4.0          cellranger_1.1.0  plyr_1.8.4       
## [13] backports_1.1.5   evaluate_0.14     httr_1.4.1       
## [16] highr_0.8         pillar_1.4.2      rlang_0.4.1      
## [19] progress_1.2.2    lazyeval_0.2.2    readxl_1.3.1     
## [22] rstudioapi_0.10   R.utils_2.9.0     R.oo_1.22.0      
## [25] labeling_0.3      webshot_0.5.1     stringr_1.4.0    
## [28] igraph_1.2.4.1    munsell_0.5.0     compiler_3.5.2   
## [31] xfun_0.10         pkgconfig_2.0.3   htmltools_0.4.0  
## [34] tidyselect_0.2.5  tibble_2.1.3      fansi_0.4.0      
## [37] viridisLite_0.3.0 crayon_1.3.4      withr_2.1.2      
## [40] R.methodsS3_1.7.1 grid_3.5.2        gtable_0.3.0     
## [43] lifecycle_0.1.0   magrittr_1.5      storr_1.2.1      
## [46] scales_1.0.0      cli_1.1.0         stringi_1.4.3    
## [49] reshape2_1.4.3    xml2_1.2.2        ellipsis_0.3.0   
## [52] filelock_1.0.2    vctrs_0.2.0       forcats_0.4.0    
## [55] tools_3.5.2       glue_1.3.1        purrr_0.3.3      
## [58] yaml_2.2.0        colorspace_1.4-1  base64url_1.4    
## [61] rvest_0.3.4       knitr_1.25

References

Allaire, JJ, Yihui Xie, Jonathan McPherson, Javier Luraschi, Kevin Ushey, Aron Atkins, Hadley Wickham, Joe Cheng, and Winston Chang. 2018. Rmarkdown: Dynamic Documents for R. https://CRAN.R-project.org/package=rmarkdown.

Dowle, M, A Srinivasan, T Short, S Lianoglou with contributions from R Saporta, and E Antonyan. 2015. Data.table: Extension of Data.frame. https://CRAN.R-project.org/package=data.table.

Grolemund, Garrett, and Hadley Wickham. 2011. “Dates and Times Made Easy with lubridate.” Journal of Statistical Software 40 (3): 1–25. http://www.jstatsoft.org/v40/i03/.

R Core Team. 2016. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

Stephenson, Janet, Rebecca Ford, Nirmal-Kumar Nair, Neville Watson, Alan Wood, and Allan Miller. 2017. “Smart Grid Research in New Zealand–A Review from the GREEN Grid Research Programme.” Renewable and Sustainable Energy Reviews 82 (1): 1636–45. https://doi.org/10.1016/j.rser.2017.07.010.

Wickham, Hadley. 2009. Ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. http://ggplot2.org.

Xie, Yihui. 2016a. Bookdown: Authoring Books and Technical Documents with R Markdown. Boca Raton, Florida: Chapman; Hall/CRC. https://github.com/rstudio/bookdown.

———. 2016b. Knitr: A General-Purpose Package for Dynamic Report Generation in R. https://CRAN.R-project.org/package=knitr.

Zhu, Hao. 2018. KableExtra: Construct Complex Table with ’Kable’ and Pipe Syntax. https://CRAN.R-project.org/package=kableExtra.