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. (2022) NZ GREEN Grid Household Electricity Demand Data: EECA Data Analysis (Part B) Report v2.2, Centre for Sustainability, University of Otago: Dunedin.

1.2 Report circulation:

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

1.3 License

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1.4 History

You may not be reading the most recent version of this report. Please check:

the github R code repository;
our issues list for any unfixed problems;
our project documentation site and specifically;
this report’s edit history

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)

Note that the mean kWh values are substantially different from the medians indicating a skewed distribution.

Table 3.1: Descriptive statistics for power data (overall household total demand/energy use)
Season	Peak	N households	Mean half-hourly kW	s.d. (half-hourly kW)	Mean half-hourly kWh	Median half-hourly kWh	Mean total kWh for the period
Autumn	Off peak (day)	34	0.90	0.93	0.45	0.26	5.80
Autumn	Off peak (night)	34	0.68	0.75	0.34	0.20	5.68
Autumn	Peak (evening)	34	1.56	1.27	0.78	0.60	5.21
Autumn	Peak (morning)	34	1.39	1.34	0.69	0.45	2.28
Spring	Off peak (day)	27	0.88	0.91	0.44	0.26	6.40
Spring	Off peak (night)	27	0.73	0.82	0.37	0.20	6.87
Spring	Peak (evening)	27	1.54	1.28	0.77	0.59	5.76
Spring	Peak (morning)	27	1.39	1.31	0.70	0.47	2.57
Summer	Off peak (day)	32	0.74	0.74	0.37	0.23	3.50
Summer	Off peak (night)	32	0.53	0.54	0.27	0.18	3.29
Summer	Peak (evening)	32	1.01	0.88	0.51	0.36	2.45
Summer	Peak (morning)	32	0.95	0.98	0.48	0.29	1.14
Winter	Off peak (day)	31	1.13	1.12	0.57	0.35	7.82
Winter	Off peak (night)	31	0.94	0.99	0.47	0.26	8.38
Winter	Peak (evening)	31	2.22	1.52	1.11	0.98	7.87
Winter	Peak (morning)	31	1.79	1.60	0.90	0.67	3.16

The following table estimates the mean total kWh per period using a different method (i.e. directly from the half-hourly level data) as a cross-check.

Table 3.2: Mean household total kWh per period and season (alternative method)
season	ba_peak	mean_SumkWh
Autumn	Off peak (day)	6.76
Autumn	Off peak (night)	6.69
Autumn	Peak (evening)	6.09
Autumn	Peak (morning)	2.72
Spring	Off peak (day)	6.93
Spring	Off peak (night)	7.40
Spring	Peak (evening)	6.24
Spring	Peak (morning)	2.77
Summer	Off peak (day)	5.70
Summer	Off peak (night)	5.37
Summer	Peak (evening)	4.05
Summer	Peak (morning)	2.04
Winter	Off peak (day)	8.74
Winter	Off peak (night)	9.33
Winter	Peak (evening)	8.84
Winter	Peak (morning)	3.60

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.

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.

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.

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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

Figure 4.1: Mean 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 ~40% 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.

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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	3231.00	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).

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

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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.

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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

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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	Lighting	Other	Oven	Total
rf_01	2015	Winter	2015-06-03 17:30:00	3217.26	627.81	480.53	1520.99	5846.58
rf_01	2015	Winter	2015-06-03 18:00:00	2626.62	486.23	183.88	0.00	3296.74
rf_01	2015	Winter	2015-06-22 17:30:00	3672.64	568.55	593.82	284.81	5119.82
rf_01	2015	Winter	2015-06-22 18:00:00	3884.40	670.60	196.28	1227.56	5978.85
rf_01	2015	Winter	2015-06-22 18:30:00	3415.85	702.64	172.78	1255.81	5547.09
rf_01	2015	Winter	2015-06-23 17:30:00	4049.44	501.81	720.67	0.00	5271.92
rf_01	2015	Winter	2015-06-23 18:00:00	4404.86	346.77	419.84	0.00	5171.46
rf_01	2015	Winter	2015-06-23 18:30:00	5842.13	404.60	1360.91	0.00	7607.64
rf_01	2015	Winter	2015-06-24 17:30:00	4318.96	582.43	180.04	175.79	5257.22
rf_01	2015	Winter	2015-06-24 18:00:00	4126.43	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.

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

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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	94539.27	27	3501.45
Total	2015-06-24	Winter	2015	07:00:00	93517.79	28	3339.92
Total	2015-06-23	Winter	2015	18:00:00	91330.16	28	3261.79
Total	2015-08-21	Winter	2015	07:00:00	87393.28	27	3236.79
Total	2015-06-28	Winter	2015	18:30:00	83632.68	27	3097.51
Total	2015-06-23	Winter	2015	17:30:00	86435.42	28	3086.98
Total	2015-06-26	Winter	2015	07:00:00	86301.30	28	3082.19
Total	2015-06-23	Winter	2015	07:00:00	85940.64	28	3069.31
Total	2015-08-10	Winter	2015	20:00:00	82334.81	27	3049.44
Total	2015-08-12	Winter	2015	07:00:00	81883.67	27	3032.73

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.

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.

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

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

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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.

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.

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.

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.

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

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

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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.

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.

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:

Unidentified loads represented a significant contribution in the sample
Means calculated over the sample can significantly distort the results
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	1460383	0	0
Heat Pump$2092	51639	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$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$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$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$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$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	1361891
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$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$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	18346	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$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$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:

Table 8.2: Data summary
Name	powerDT
Number of rows	6339776
Number of columns	22
Key	date, obsHalfHour
_______________________
Column type frequency:
character	9
Date	1
difftime	1
numeric	9
POSIXct	2
________________________
Group variables	None

Variable type: character

skim_variable	n_missing	complete_rate	min	max	n_unique
linkID	0	1.00	5	6	37
circuit	0	1.00	9	37	89
season	116097	0.98	6	6	4
peak	116097	0.98	4	10	3
circuitLabel	116097	0.98	4	37	27
circuitID	2822274	0.55	4	4	87
eecaCircuit	0	1.00	4	20	6
eecaCircuitOrig	0	1.00	4	20	6
ba_peak	0	1.00	14	16	4

Variable type: Date

skim_variable	n_missing	complete_rate	min	max	median	n_unique
date	116097	0.98	2014-01-06	2018-08-01	2016-03-20	1613

Variable type: difftime

skim_variable	n_missing	complete_rate	min	max	median	n_unique
obsHalfHour	116097	0.98	0 secs	84600 secs	12:00:00	48

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
nObs	116097	0.98	29.98	0.61	1.00	30	30.00	30.00	60.00	▁▁▇▁▁
meanPowerW	197941	0.97	424.86	737.26	-2356.33	0	138.82	492.67	10981.59	▇▅▁▁▁
sdPowerW	1460654	0.77	184.43	373.88	0.00	0	0.72	109.57	5068.08	▇▁▁▁▁
minPowerW	1515182	0.76	195.84	512.82	0.00	0	0.00	163.82	9600.58	▇▁▁▁▁
maxPowerW	1487394	0.77	727.57	1293.36	0.00	0	18.44	791.49	27759.00	▇▁▁▁▁
month	116097	0.98	6.48	3.33	1.00	4	6.00	9.00	12.00	▇▆▆▆▇
year	0	1.00	2015.86	1.16	2014.00	2015	2016.00	2017.00	2018.00	▃▇▆▅▂
energyWh	197941	0.97	212.43	368.63	-1178.17	0	69.41	246.33	5490.79	▇▅▁▁▁
hour	0	1.00	11.50	6.92	0.00	6	12.00	18.00	23.00	▇▇▆▇▇

Variable type: POSIXct

skim_variable	n_missing	complete_rate	min	max	median	n_unique
r_dateTimeHalfHour	116097	0.98	2014-01-06 03:00:00	2018-08-01 11:30:00	2016-03-20 10:00:00	77345
r_dateTime_nz	0	1.00	2014-01-06 03:00:00	2018-08-01 11:30:00	2016-03-24 09:30:00	77345

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

## Warning in gmin(meanPowerW, na.rm = TRUE): No non-missing values found in at least one group. Returning 'Inf' for
## such groups to be consistent with base

## Warning in gmax(meanPowerW, na.rm = TRUE): No non-missing values found in at least one group. Returning '-Inf' for
## such groups to be consistent with base

Table 8.3: 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	NaN	Inf	-Inf	70291
Hot Water - Controlled$2102	Hot water	464.31	0	3196.6	70291

## Warning in gmin(meanPowerW, na.rm = TRUE): No non-missing values found in at least one group. Returning 'Inf' for
## such groups to be consistent with base

## Warning in gmin(meanPowerW, na.rm = TRUE): No non-missing values found in at least one group. Returning '-Inf' for
## such groups to be consistent with base

Table 8.3: 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	NaN	Inf	-Inf	45806
Heat Pump$4190	Heat Pump or Heating	51.10	0	3579.52	45806
Lighting$4189	Lighting	185.42	0	1760.21	18346

Table 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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	0.23	5541.26	70345

Table 8.3: 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 8.3: 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 8.3: rf_34: Mean of half-hourly mean power (W) by original circuit label & EECA circuit type
circuit	eecaCircuit	meanPowerW	maxPowerW	nObs
Calculated_other	Other	536.46	5381.39	24373
Heat Pump$4223	Heat Pump or Heating	196.47	4982.93	24373
Hot Water - Uncontrolled$4224	Hot water	329.87	3901.05	24373
Lighting$4222	Lighting	96.63	1078.36	24373
imputedTotalDemand_circuitsToSum_v1.1	Total	1159.43	9469.69	24373

Table 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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	7855.84	11618

Table 8.3: 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

Table 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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 8.3: 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

9 Runtime

Analysis completed in 78.33 seconds ( 1.31 minutes) using knitr in RStudio with R version 4.1.2 (2021-11-01) running on x86_64-apple-darwin17.0.

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 4.1.2 (2021-11-01)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Monterey 12.3.1
## 
## Matrix products: default
## LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] readr_2.1.2              dplyr_1.0.8              tidyr_1.2.0              skimr_2.1.4             
##  [5] hms_1.1.1                kableExtra_1.3.4         ggplot2_3.3.5            drake_7.13.3            
##  [9] bookdown_0.26            rmarkdown_2.13           GREENGridEECA_0.0.0.9000 GREENGridData_1.0       
## [13] lubridate_1.8.0          here_1.0.1               data.table_1.14.2       
## 
## loaded via a namespace (and not attached):
##  [1] httr_1.4.2        sass_0.4.1        jsonlite_1.8.0    viridisLite_0.4.0 R.utils_2.11.0    bslib_0.3.1      
##  [7] assertthat_0.2.1  highr_0.9         base64url_1.4     cellranger_1.1.0  yaml_2.3.5        progress_1.2.2   
## [13] pillar_1.7.0      backports_1.4.1   glue_1.6.2        digest_0.6.29     rvest_1.0.2       colorspace_2.0-3 
## [19] htmltools_0.5.2   R.oo_1.24.0       plyr_1.8.7        pkgconfig_2.0.3   purrr_0.3.4       scales_1.2.0     
## [25] webshot_0.5.3     svglite_2.1.0     tzdb_0.3.0        tibble_3.1.6      txtq_0.2.4        generics_0.1.2   
## [31] farver_2.1.0      ellipsis_0.3.2    withr_2.5.0       repr_1.1.4        cli_3.3.0         magrittr_2.0.3   
## [37] crayon_1.5.1      readxl_1.4.0      evaluate_0.15     storr_1.2.5       R.methodsS3_1.8.1 fansi_1.0.3      
## [43] xml2_1.3.3        tools_4.1.2       prettyunits_1.1.1 lifecycle_1.0.1   stringr_1.4.0     munsell_0.5.0    
## [49] compiler_4.1.2    jquerylib_0.1.4   systemfonts_1.0.4 rlang_1.0.2       grid_4.1.2        rstudioapi_0.13  
## [55] igraph_1.3.1      base64enc_0.1-3   labeling_0.4.2    gtable_0.3.0      DBI_1.1.2         curl_4.3.2       
## [61] reshape2_1.4.4    R6_2.5.1          knitr_1.38        fastmap_1.1.0     utf8_1.2.2        filelock_1.0.2   
## [67] rprojroot_2.0.3   stringi_1.7.6     parallel_4.1.2    Rcpp_1.0.8.3      vctrs_0.4.1       tidyselect_1.1.2 
## [73] xfun_0.30

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.

NZ GREEN Grid Household Electricity Demand Data

EECA Data Analysis (Part B) Report v2.2

Dortans, C., Anderson, B. and Jack, M.

Last run at: 2022-04-28 14:41:18 (Europe/London)