NZ GREEN Grid Household Electricity Demand Data
EECA Data Analysis (Part B) GXP Data Report v0.5
Ben Anderson
Last run at: 2019-10-20 21:38:27 (Pacific/Auckland)
1 About
1.1 Citation
If you wish to use any of the material from this report please cite as:
- Ben Anderson (2019) NZ GREEN Grid Household Electricity Demand Data: EECA Data Analysis (Part B) GXP Data Report v0.5, Centre for Sustainability, University of Otago: Dunedin.
This work is (c) 2019 the authors. Usage right are specified in the License section (1.3).
1.2 Report circulation
- Public – this report is intended for publication following EECA approval.
1.3 License
This work is made available under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) License.
This means you are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
- You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.
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For the avoidance of doubt and explanation of terms please refer to the full license notice and legal code.
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 Electricity Authority EMI grid export database to:
- explore the GXP data
- identify system peak half-hours for the regions of Taranaki and Hawke’s Bay in 2015 for use in the Part B data analysis
This report describes the results of this work and directs the reader to relevant R code where necessary.
All code used to create this report is available from:
The archived and most recent version of the report is available from:
3 Data
4 Grid exit point (GXP)
A grid exit point (GXP) is defined in Part 1 of the Code and means any point of connection on the grid at which electricity predominantly flows out of the grid or is determined as being such by the Authority following an application in accordance with clause 13.28. Any such point of connection may, at any given time, be a GXP or a GIP, but may not be both at the same time."
For (very little) further information see the EMI glossary.
## Matched regions:##
## Hawke's bay Taranaki <NA>
## 107310 286160 8296435Start date: 2013-01-01
End date: 2015-12-31
| 2013 | 2015 |
|---|---|
| 360096 | 366048 |
| 325248 | 329760 |
| 362448 | 361584 |
| 355927 | 340076 |
| 365424 | 352128 |
| 354240 | 341280 |
| 369024 | 352656 |
| 369024 | 353664 |
| 357564 | 341768 |
| 370512 | 354144 |
| 358560 | 343584 |
| 370512 | 355824 |
5 Explore GXP data
Figure 5.1 shows the mean total network electricity export by season and year for all regions combined as a data sense-check.
Figure 5.1: Mean total kWh per half hour by season
Next we use the GXP data to identify local (regional) system peak load half-hours for Hawke’s Bay and Taranaki as this matches the GREEN Grid household sample location. Selected GXPs for the regions we are interested in:
| regionName | node | NWK_Code | year | nHalfHours | meanMWh |
|---|---|---|---|---|---|
| Hawke’s bay | FHL0331 | HAWK | 2013 | 17517 | 14.04 |
| Hawke’s bay | FHL0331 | HAWK | 2015 | 17517 | 14.90 |
| Hawke’s bay | RDF0331 | HAWK | 2013 | 17517 | 16.16 |
| Hawke’s bay | RDF0331 | HAWK | 2015 | 17517 | 15.67 |
| Hawke’s bay | WTU0331 | HAWK | 2013 | 17517 | 24.22 |
| Hawke’s bay | WTU0331 | HAWK | 2015 | 17517 | 24.18 |
| Taranaki | CST0331 | POCO | 2013 | 17517 | 14.68 |
| Taranaki | CST0331 | POCO | 2015 | 17517 | 15.64 |
| Taranaki | HUI0331 | POCO | 2013 | 17517 | 5.36 |
| Taranaki | HUI0331 | POCO | 2015 | 17517 | 6.67 |
| Taranaki | HWA0331 | POCO | 2013 | 17517 | 8.80 |
| Taranaki | HWA0331 | POCO | 2015 | 17517 | 9.64 |
| Taranaki | NPL0331 | CTCT | 2013 | 8689 | 0.15 |
| Taranaki | NPL0331 | POCO | 2013 | 17517 | 4.96 |
| Taranaki | NPL0331 | POCO | 2015 | 17517 | 4.80 |
| Taranaki | NPL0331 | PTNP | 2013 | 8828 | 0.11 |
| Taranaki | NPL0331 | PTNP | 2015 | 17517 | 0.04 |
| Taranaki | OPK0331 | POCO | 2013 | 17517 | 2.70 |
| Taranaki | OPK0331 | POCO | 2015 | 17517 | 2.83 |
| Taranaki | SFD0331 | POCO | 2013 | 17517 | 7.19 |
| Taranaki | SFD0331 | POCO | 2015 | 17517 | 7.43 |
| Taranaki | WGN0331 | POCO | 2013 | 17517 | 7.99 |
| Taranaki | WGN0331 | POCO | 2015 | 17517 | 7.80 |
Note that NPL0331 in Taranaki has two network codes - presumably it feeds two networks? In what follows we simply sum the kWh for all half-hours for all nodes for each region.
Figure 5.2 shows the same results as above but only for the regions of interest: Taranaki and Hawke’s Bay.
Figure 5.2: Mean total kWh per half hour by season and region
6 Top 100 ‘peaks’ in 2015
Extract data for winter (Jun - August) 2015 as per original EECA file. Aggregate to region level and select the top 100 half hours for each region.
## node region region name
## Length:1047600 Length:1047600 Length:1047600
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## X Y OBJECTID MXLOCATION
## Min. :1153139 Min. :4830103 Min. : 1.00 Length:1047600
## 1st Qu.:1504449 1st Qu.:5209968 1st Qu.: 48.00 Class :character
## Median :1753729 Median :5615041 Median : 94.00 Mode :character
## Mean :1678574 Mean :5513596 Mean : 97.12
## 3rd Qu.:1831847 3rd Qu.:5779107 3rd Qu.:144.00
## Max. :1968014 Max. :6082717 Max. :293.00
## NA's :4416 NA's :4416 NA's :4416
## type status description
## Length:1047600 Length:1047600 Length:1047600
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## GlobalID NWK_Code GENERATION_TYPE
## Length:1047600 Length:1047600 Length:1047600
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## TRADER TRADING_DATE UNIT_MEASURE
## Length:1047600 Length:1047600 Length:1047600
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## FLOW_DIRECTION STATUS Time_Period kWh
## Length:1047600 Length:1047600 Length:1047600 Min. : 0
## Class :character Class :character Class :character 1st Qu.: 47
## Mode :character Mode :character Mode :character Median : 2772
## Mean : 9813
## 3rd Qu.: 11472
## Max. :290737
##
## t tp mins hours
## Length:1047600 Min. : 1.00 Min. : 0 Min. : 0.00
## Class :character 1st Qu.:12.75 1st Qu.: 0 1st Qu.: 5.75
## Mode :character Median :24.50 Median :15 Median :11.50
## Mean :24.50 Mean :15 Mean :11.50
## 3rd Qu.:36.25 3rd Qu.:30 3rd Qu.:17.25
## Max. :48.00 Max. :30 Max. :23.00
##
## strTime rTime rDate
## Length:1047600 Min. : 0 Length:1047600
## Class :character 1st Qu.:21150 Class :character
## Mode :character Median :42300 Mode :character
## Mean :42300
## 3rd Qu.:63450
## Max. :84600
##
## rDateTime date month
## Min. :2015-06-01 00:00:00 Min. :2015-06-01 Min. :6.000
## 1st Qu.:2015-06-24 00:30:00 1st Qu.:2015-06-24 1st Qu.:6.000
## Median :2015-07-17 01:00:00 Median :2015-07-17 Median :7.000
## Mean :2015-07-17 00:34:11 Mean :2015-07-16 Mean :7.012
## 3rd Qu.:2015-08-09 01:30:00 3rd Qu.:2015-08-09 3rd Qu.:8.000
## Max. :2015-08-31 23:30:00 Max. :2015-08-31 Max. :8.000
##
## day_of_week hms halfHour weekdays
## Sun:148032 Length:1047600 Length:1047600 Length:1047600
## Mon:159408 Class1:hms Class1:hms Class :character
## Tue:148032 Class2:difftime Class2:difftime Mode :character
## Wed:148032 Mode :numeric Mode :numeric
## Thu:148032
## Fri:148032
## Sat:148032
## regionName peakPeriod year season
## Length:1047600 Early morning:305550 Min. :2015 Spring: 0
## Class :character Morning peak : 87300 1st Qu.:2015 Summer: 0
## Mode :character Day time :349200 Median :2015 Autumn: 0
## Evening peak :174600 Mean :2015 Winter:1047600
## Late evening :130950 3rd Qu.:2015
## Max. :2015
## ## Empty data.table (0 rows and 4 cols): node,Time_Period,rDateTime,kWh## node Time_Period rDateTime kWh
## Length:0 Length:0 Min. :NA Min. : NA
## Class :character Class :character 1st Qu.:NA 1st Qu.: NA
## Mode :character Mode :character Median :NA Median : NA
## Mean :NA Mean :NaN
## 3rd Qu.:NA 3rd Qu.: NA
## Max. :NA Max. : NA##
## Hawke's bay Taranaki <NA>
## CST0331 0 4416 0
## FHL0331 4416 0 0
## HUI0331 0 4416 0
## HWA0331 0 4416 0
## NPL0331 0 8832 0
## OPK0331 0 4416 0
## RDF0331 4416 0 0
## SFD0331 0 4416 0
## WGN0331 0 4416 0
## WTU0331 4416 0 0
## <NA> 0 0 0##
## HAWK POCO PTNP <NA>
## CST0331 0 4416 0 0
## FHL0331 4416 0 0 0
## HUI0331 0 4416 0 0
## HWA0331 0 4416 0 0
## NPL0331 0 4416 4416 0
## OPK0331 0 4416 0 0
## RDF0331 4416 0 0 0
## SFD0331 0 4416 0 0
## WGN0331 0 4416 0 0
## WTU0331 4416 0 0 0
## <NA> 0 0 0 0## Skim summary statistics
## n obs: 48576
## n variables: 38
##
## ── Variable type:character ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n min max empty n_unique
## description 0 48576 48576 6 17 0 10
## FLOW_DIRECTION 0 48576 48576 1 1 0 1
## GENERATION_TYPE 0 48576 48576 2 2 0 2
## GlobalID 0 48576 48576 36 36 0 10
## MXLOCATION 0 48576 48576 3 3 0 10
## node 0 48576 48576 7 7 0 10
## NWK_Code 0 48576 48576 4 4 0 3
## rDate 0 48576 48576 10 10 0 92
## region 0 48576 48576 1 1 0 2
## region name 0 48576 48576 8 11 0 2
## regionName 0 48576 48576 8 11 0 2
## status 0 48576 48576 12 12 0 1
## STATUS 0 48576 48576 5 5 0 1
## strTime 0 48576 48576 7 8 0 48
## t 0 48576 48576 1 1 0 1
## Time_Period 0 48576 48576 3 4 0 48
## TRADER 0 48576 48576 4 4 0 1
## TRADING_DATE 0 48576 48576 10 10 0 92
## type 0 48576 48576 5 5 0 1
## UNIT_MEASURE 0 48576 48576 3 3 0 1
## weekdays 0 48576 48576 8 8 0 2
##
## ── Variable type:Date ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n min max median n_unique
## date 0 48576 48576 2015-06-01 2015-08-31 2015-07-16 92
##
## ── Variable type:difftime ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n min max median n_unique
## halfHour 0 48576 48576 0 secs 84600 secs 42300 secs 48
## hms 0 48576 48576 0 secs 84600 secs 42300 secs 48
##
## ── Variable type:factor ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n n_unique
## day_of_week 0 48576 48576 7
## peakPeriod 0 48576 48576 5
## season 0 48576 48576 1
## top_counts ordered
## Mon: 7392, Sun: 6864, Tue: 6864, Wed: 6864 TRUE
## Day: 16192, Ear: 14168, Eve: 8096, Lat: 6072 FALSE
## Win: 48576, Spr: 0, Sum: 0, Aut: 0 FALSE
##
## ── Variable type:integer ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n mean sd p0 p25 p50
## hours 0 48576 48576 11.5 6.92 0 5.75 11.5
## mins 0 48576 48576 15 15 0 0 15
## OBJECTID 0 48576 48576 102.27 48.03 32 59 102
## rTime 0 48576 48576 42300 24936.38 0 21150 42300
## tp 0 48576 48576 24.5 13.85 1 12.75 24.5
## p75 p100 hist
## 17.25 23 ▇▇▇▇▇▇▇▇
## 30 30 ▇▁▁▁▁▁▁▇
## 138 184 ▇▇▁▇▇▃▁▇
## 63450 84600 ▇▇▇▇▇▇▇▇
## 36.25 48 ▇▇▇▇▇▇▇▇
##
## ── Variable type:numeric ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n mean sd p0 p25
## kWh 0 48576 48576 10642.28 8412.86 27 4909.75
## month 0 48576 48576 7.01 0.81 6 6
## X 0 48576 48576 1768252.09 1e+05 1679853 1688836
## Y 0 48576 48576 5638053 33117.13 5576956 5609948
## year 0 48576 48576 2015 0 2015 2015
## p50 p75 p100 hist
## 8321 15766 45281 ▇▇▃▃▁▁▁▁
## 7 8 8 ▇▁▁▇▁▁▁▇
## 1712536 1923083 1933253 ▇▃▁▂▁▁▁▅
## 5639246 5676251 5677676 ▂▁▃▃▂▂▁▇
## 2015 2015 2015 ▁▁▁▇▁▁▁▁
##
## ── Variable type:POSIXct ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n min max median
## rDateTime 0 48576 48576 2015-06-01 2015-08-31 2015-07-16
## n_unique
## 4416##
## HAWK POCO PTNP
## 13248 30912 4416##
## X
## 48576##
## GD GN
## 4416 44160##
## TPNZ
## 48576## node region region name
## Length:48576 Length:48576 Length:48576
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## X Y OBJECTID MXLOCATION
## Min. :1679853 Min. :5576956 Min. : 32.0 Length:48576
## 1st Qu.:1688836 1st Qu.:5609948 1st Qu.: 59.0 Class :character
## Median :1712536 Median :5639246 Median :102.0 Mode :character
## Mean :1768252 Mean :5638053 Mean :102.3
## 3rd Qu.:1923083 3rd Qu.:5676251 3rd Qu.:138.0
## Max. :1933253 Max. :5677676 Max. :184.0
##
## type status description
## Length:48576 Length:48576 Length:48576
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## GlobalID NWK_Code GENERATION_TYPE
## Length:48576 Length:48576 Length:48576
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## TRADER TRADING_DATE UNIT_MEASURE
## Length:48576 Length:48576 Length:48576
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## FLOW_DIRECTION STATUS Time_Period kWh
## Length:48576 Length:48576 Length:48576 Min. : 27
## Class :character Class :character Class :character 1st Qu.: 4910
## Mode :character Mode :character Mode :character Median : 8321
## Mean :10642
## 3rd Qu.:15766
## Max. :45281
##
## t tp mins hours
## Length:48576 Min. : 1.00 Min. : 0 Min. : 0.00
## Class :character 1st Qu.:12.75 1st Qu.: 0 1st Qu.: 5.75
## Mode :character Median :24.50 Median :15 Median :11.50
## Mean :24.50 Mean :15 Mean :11.50
## 3rd Qu.:36.25 3rd Qu.:30 3rd Qu.:17.25
## Max. :48.00 Max. :30 Max. :23.00
##
## strTime rTime rDate
## Length:48576 Min. : 0 Length:48576
## Class :character 1st Qu.:21150 Class :character
## Mode :character Median :42300 Mode :character
## Mean :42300
## 3rd Qu.:63450
## Max. :84600
##
## rDateTime date month
## Min. :2015-06-01 00:00:00 Min. :2015-06-01 Min. :6.000
## 1st Qu.:2015-06-23 23:52:30 1st Qu.:2015-06-23 1st Qu.:6.000
## Median :2015-07-16 23:45:00 Median :2015-07-16 Median :7.000
## Mean :2015-07-16 23:45:00 Mean :2015-07-16 Mean :7.011
## 3rd Qu.:2015-08-08 23:37:30 3rd Qu.:2015-08-08 3rd Qu.:8.000
## Max. :2015-08-31 23:30:00 Max. :2015-08-31 Max. :8.000
##
## day_of_week hms halfHour weekdays
## Sun:6864 Length:48576 Length:48576 Length:48576
## Mon:7392 Class1:hms Class1:hms Class :character
## Tue:6864 Class2:difftime Class2:difftime Mode :character
## Wed:6864 Mode :numeric Mode :numeric
## Thu:6864
## Fri:6864
## Sat:6864
## regionName peakPeriod year season
## Length:48576 Early morning:14168 Min. :2015 Spring: 0
## Class :character Morning peak : 4048 1st Qu.:2015 Summer: 0
## Mode :character Day time :16192 Median :2015 Autumn: 0
## Evening peak : 8096 Mean :2015 Winter:48576
## Late evening : 6072 3rd Qu.:2015
## Max. :2015
## ## Empty data.table (0 rows and 38 cols): node,region,region name,X,Y,OBJECTID...## region regionName Time_Period hours
## Length:8832 Length:8832 Length:8832 Min. : 0.00
## Class :character Class :character Class :character 1st Qu.: 5.75
## Mode :character Mode :character Mode :character Median :11.50
## Mean :11.50
## 3rd Qu.:17.25
## Max. :23.00
##
## rDateTime weekdays peakPeriod
## Min. :2015-06-01 00:00:00 Length:8832 Early morning:2576
## 1st Qu.:2015-06-23 23:52:30 Class :character Morning peak : 736
## Median :2015-07-16 23:45:00 Mode :character Day time :2944
## Mean :2015-07-16 23:45:00 Evening peak :1472
## 3rd Qu.:2015-08-08 23:37:30 Late evening :1104
## Max. :2015-08-31 23:30:00
##
## sumkWh nObs nRegions nLocations nNetworks
## Min. :31040 Min. :3.0 Min. :1 Min. :3 Min. :1.0
## 1st Qu.:46001 1st Qu.:3.0 1st Qu.:1 1st Qu.:3 1st Qu.:1.0
## Median :59527 Median :5.5 Median :1 Median :5 Median :1.5
## Mean :58533 Mean :5.5 Mean :1 Mean :5 Mean :1.5
## 3rd Qu.:68452 3rd Qu.:8.0 3rd Qu.:1 3rd Qu.:7 3rd Qu.:2.0
## Max. :95432 Max. :8.0 Max. :1 Max. :7 Max. :2.0
##
## nGenTypes month hms
## Min. :1.0 Jul :2976 Length:8832
## 1st Qu.:1.0 Aug :2976 Class1:hms
## Median :1.5 Jun :2880 Class2:difftime
## Mean :1.5 Jan : 0 Mode :numeric
## 3rd Qu.:2.0 Feb : 0
## Max. :2.0 Mar : 0
## (Other): 0##
## Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
## Early morning 0 0 0 0 0 0 0 0 0 0 0 0
## Morning peak 0 0 0 0 0 0 0 25 0 0 0 0
## Day time 0 0 0 0 0 0 0 5 0 0 0 0
## Evening peak 0 0 0 0 0 13 13 44 0 0 0 0
## Late evening 0 0 0 0 0 0 0 0 0 0 0 0## regionName hours Time_Period nPeaks
## 1: Taranaki 7 TP15 3
## 2: Taranaki 7 TP16 11
## 3: Taranaki 8 TP17 9
## 4: Taranaki 8 TP18 2
## 5: Taranaki 16 TP34 5
## 6: Taranaki 17 TP35 3
## 7: Taranaki 17 TP36 24
## 8: Taranaki 18 TP37 28
## 9: Taranaki 18 TP38 12
## 10: Taranaki 19 TP39 2
## 11: Taranaki 19 TP40 1##
## Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
## Early morning 0 0 0 0 0 0 0 0 0 0 0 0
## Morning peak 0 0 0 0 0 10 5 1 0 0 0 0
## Day time 0 0 0 0 0 8 24 1 0 0 0 0
## Evening peak 0 0 0 0 0 32 17 0 0 0 0 0
## Late evening 0 0 0 0 0 0 2 0 0 0 0 0## regionName hours Time_Period nPeaks
## 1: Hawke's bay 7 TP16 6
## 2: Hawke's bay 8 TP17 5
## 3: Hawke's bay 8 TP18 5
## 4: Hawke's bay 9 TP19 4
## 5: Hawke's bay 9 TP20 5
## 6: Hawke's bay 10 TP21 3
## 7: Hawke's bay 10 TP22 6
## 8: Hawke's bay 11 TP23 3
## 9: Hawke's bay 11 TP24 2
## 10: Hawke's bay 12 TP25 3
## 11: Hawke's bay 12 TP26 2
## 12: Hawke's bay 13 TP27 1
## 13: Hawke's bay 16 TP33 1
## 14: Hawke's bay 16 TP34 3
## 15: Hawke's bay 17 TP35 6
## 16: Hawke's bay 17 TP36 12
## 17: Hawke's bay 18 TP37 9
## 18: Hawke's bay 18 TP38 5
## 19: Hawke's bay 19 TP39 6
## 20: Hawke's bay 19 TP40 5
## 21: Hawke's bay 20 TP41 4
## 22: Hawke's bay 20 TP42 2
## 23: Hawke's bay 21 TP43 1
## 24: Hawke's bay 21 TP44 1
## regionName hours Time_Period nPeaks6.1 Hawke’s Bay
Figure 6.1 shows the total network electricity export in this region as a data sense-check.
Figure 6.1: Hawke’s Bay: Total MWh per half hour
Table 6.1 shows the top 10 peak demand periods.
| regionName | Time_Period | hms | rDateTime | weekdays | peakPeriod | sumkWh |
|---|---|---|---|---|---|---|
| Hawke’s bay | TP23 | 11:00:00 | 2015-07-10 11:00:00 | Weekdays | Day time | 95432 |
| Hawke’s bay | TP36 | 17:30:00 | 2015-07-09 17:30:00 | Weekdays | Evening peak | 94725 |
| Hawke’s bay | TP24 | 11:30:00 | 2015-07-10 11:30:00 | Weekdays | Day time | 94214 |
| Hawke’s bay | TP20 | 09:30:00 | 2015-06-26 09:30:00 | Weekdays | Day time | 94115 |
| Hawke’s bay | TP36 | 17:30:00 | 2015-06-23 17:30:00 | Weekdays | Evening peak | 94018 |
| Hawke’s bay | TP23 | 11:00:00 | 2015-07-09 11:00:00 | Weekdays | Day time | 93898 |
| Hawke’s bay | TP22 | 10:30:00 | 2015-07-14 10:30:00 | Weekdays | Day time | 93834 |
| Hawke’s bay | TP18 | 08:30:00 | 2015-07-31 08:30:00 | Weekdays | Morning peak | 93627 |
| Hawke’s bay | TP37 | 18:00:00 | 2015-07-09 18:00:00 | Weekdays | Evening peak | 93603 |
| Hawke’s bay | TP19 | 09:00:00 | 2015-07-21 09:00:00 | Weekdays | Day time | 92724 |
Table 6.2 shows when the top 100 peak demand periods occured.
| Time_Period | hms | weekdays | peakPeriod | nHalfHours |
|---|---|---|---|---|
| TP36 | 17:30:00 | Weekdays | Evening peak | 12 |
| TP37 | 18:00:00 | Weekdays | Evening peak | 9 |
| TP16 | 07:30:00 | Weekdays | Morning peak | 6 |
| TP22 | 10:30:00 | Weekdays | Day time | 6 |
| TP35 | 17:00:00 | Weekdays | Evening peak | 6 |
| TP39 | 19:00:00 | Weekdays | Evening peak | 6 |
| TP17 | 08:00:00 | Weekdays | Morning peak | 5 |
| TP18 | 08:30:00 | Weekdays | Morning peak | 5 |
| TP20 | 09:30:00 | Weekdays | Day time | 5 |
| TP38 | 18:30:00 | Weekdays | Evening peak | 5 |
| TP40 | 19:30:00 | Weekdays | Evening peak | 5 |
| TP19 | 09:00:00 | Weekdays | Day time | 4 |
| TP41 | 20:00:00 | Weekdays | Evening peak | 4 |
| TP21 | 10:00:00 | Weekdays | Day time | 3 |
| TP23 | 11:00:00 | Weekdays | Day time | 3 |
| TP25 | 12:00:00 | Weekdays | Day time | 3 |
| TP34 | 16:30:00 | Weekdays | Day time | 3 |
| TP24 | 11:30:00 | Weekdays | Day time | 2 |
| TP26 | 12:30:00 | Weekdays | Day time | 2 |
| TP42 | 20:30:00 | Weekdays | Evening peak | 2 |
| TP27 | 13:00:00 | Weekdays | Day time | 1 |
| TP33 | 16:00:00 | Weekdays | Day time | 1 |
| TP43 | 21:00:00 | Weekdays | Late evening | 1 |
| TP44 | 21:30:00 | Weekdays | Late evening | 1 |
6.2 Taranaki
Figure 6.2 shows the total network electricity export in this region as a data sense-check.
Figure 6.2: Taranaki: Total MWh per half hour
Table 6.3 shows the top 10 peak demand periods.
| regionName | Time_Period | hms | rDateTime | weekdays | peakPeriod | sumkWh |
|---|---|---|---|---|---|---|
| Taranaki | TP37 | 18:00:00 | 2015-08-11 18:00:00 | Weekdays | Evening peak | 83244 |
| Taranaki | TP38 | 18:30:00 | 2015-08-11 18:30:00 | Weekdays | Evening peak | 82281 |
| Taranaki | TP37 | 18:00:00 | 2015-08-10 18:00:00 | Weekdays | Evening peak | 81820 |
| Taranaki | TP37 | 18:00:00 | 2015-08-18 18:00:00 | Weekdays | Evening peak | 81664 |
| Taranaki | TP36 | 17:30:00 | 2015-08-18 17:30:00 | Weekdays | Evening peak | 81582 |
| Taranaki | TP36 | 17:30:00 | 2015-06-22 17:30:00 | Weekdays | Evening peak | 81563 |
| Taranaki | TP36 | 17:30:00 | 2015-08-31 17:30:00 | Weekdays | Evening peak | 81461 |
| Taranaki | TP36 | 17:30:00 | 2015-08-24 17:30:00 | Weekdays | Evening peak | 80993 |
| Taranaki | TP36 | 17:30:00 | 2015-06-23 17:30:00 | Weekdays | Evening peak | 80841 |
| Taranaki | TP37 | 18:00:00 | 2015-08-24 18:00:00 | Weekdays | Evening peak | 80661 |
Table 6.4 shows when the 100 peak demand periods occured.
| Time_Period | hms | weekdays | peakPeriod | nHalfHours |
|---|---|---|---|---|
| TP37 | 18:00:00 | Weekdays | Evening peak | 26 |
| TP36 | 17:30:00 | Weekdays | Evening peak | 24 |
| TP38 | 18:30:00 | Weekdays | Evening peak | 12 |
| TP16 | 07:30:00 | Weekdays | Morning peak | 11 |
| TP17 | 08:00:00 | Weekdays | Morning peak | 9 |
| TP34 | 16:30:00 | Weekdays | Day time | 5 |
| TP15 | 07:00:00 | Weekdays | Morning peak | 3 |
| TP35 | 17:00:00 | Weekdays | Evening peak | 3 |
| TP18 | 08:30:00 | Weekdays | Morning peak | 2 |
| TP37 | 18:00:00 | Weekends | Evening peak | 2 |
| TP39 | 19:00:00 | Weekdays | Evening peak | 2 |
| TP40 | 19:30:00 | Weekdays | Evening peak | 1 |
7 Summary
This report used the EA EMI GXP data to:
- identify the ‘peak’ demand half hours in the two regions under study.
This report described the results of this work and directed the reader to relevant R code where necessary.
All code used to create this report is available from:
The archived and most recent version of the report is available from:
The selected half-hours can be found in the github repo.
8 Data Annex
8.1 GXP summary
Descriptive statistics for original EA GXP data:
## Skim summary statistics
## n obs: 8511095
## n variables: 38
##
## ── Variable type:character ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n min max empty n_unique
## description 205843 8305252 8511095 4 20 0 167
## FLOW_DIRECTION 0 8511095 8511095 1 1 0 1
## GENERATION_TYPE 0 8511095 8511095 2 2 0 3
## GlobalID 205843 8305252 8511095 36 36 0 167
## MXLOCATION 0 8511095 8511095 3 3 0 176
## node 0 8511095 8511095 7 7 0 239
## NWK_Code 0 8511095 8511095 4 4 0 57
## rDate 0 8511095 8511095 10 10 0 730
## region 8125721 385374 8511095 1 1 0 2
## region name 8125721 385374 8511095 8 11 0 2
## regionName 8125721 385374 8511095 8 11 0 2
## status 205843 8305252 8511095 12 12 0 1
## STATUS 0 8511095 8511095 1 5 0 3
## strTime 0 8511095 8511095 7 8 0 49
## t 0 8511095 8511095 1 1 0 1
## Time_Period 0 8511095 8511095 3 4 0 49
## TRADER 0 8511095 8511095 4 4 0 9
## TRADING_DATE 0 8511095 8511095 10 10 0 730
## type 205843 8305252 8511095 3 5 0 3
## UNIT_MEASURE 0 8511095 8511095 3 3 0 1
## weekdays 0 8511095 8511095 8 8 0 2
##
## ── Variable type:Date ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n min max median
## date 0 8511095 8511095 2013-01-01 2015-12-31 2013-12-26
## n_unique
## 730
##
## ── Variable type:difftime ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n min max median n_unique
## halfHour 0 8511095 8511095 0 secs 84600 secs 11:30:00 48
## hms 0 8511095 8511095 0 secs 84600 secs 11:30:00 48
##
## ── Variable type:factor ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n n_unique
## day_of_week 0 8511095 8511095 7
## peakPeriod 0 8511095 8511095 5
## season 0 8511095 8511095 4
## top_counts ordered
## Tue: 1224672, Thu: 1224144, Mon: 1213443, Fri: 1212816 TRUE
## Day: 2837520, Ear: 2482339, Eve: 1418760, Lat: 1063096 FALSE
## Win: 2139888, Aut: 2137587, Spr: 2126132, Sum: 2107488 FALSE
##
## ── Variable type:integer ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n mean sd p0 p25 p50 p75
## hours 0 8511095 8511095 11.5 6.92 0 6 12 17
## mins 0 8511095 8511095 15 15 0 0 0 30
## OBJECTID 205843 8305252 8511095 96.97 60.04 1 47 94 144
## rTime 0 8511095 8511095 42301.68 24933.86 0 21600 43200 63000
## tp 0 8511095 8511095 24.5 13.85 1 13 25 36
## p100 hist
## 24 ▇▆▆▆▆▆▆▃
## 30 ▇▁▁▁▁▁▁▇
## 293 ▇▇▅▇▆▁▁▁
## 86400 ▇▇▇▇▇▇▇▆
## 49 ▇▇▇▇▇▇▇▆
##
## ── Variable type:numeric ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n mean sd p0 p25
## kWh 0 8511095 8511095 8866.53 21484.22 0 68
## month 0 8511095 8511095 6.53 3.45 1 4
## X 205843 8305252 8511095 1680430.91 2e+05 1153139 1504449
## Y 205843 8305252 8511095 5514957.07 327759.44 4830103 5209968
## year 0 8511095 8511095 2013.99 1 2013 2013
## p50 p75 p100 hist
## 2967 10767 292945 ▇▁▁▁▁▁▁▁
## 7 10 12 ▇▅▇▃▅▇▅▇
## 1753729 1831847 2e+06 ▁▂▃▂▂▇▇▃
## 5619536 5779107 6082717 ▂▃▃▃▂▆▇▁
## 2013 2015 2015 ▇▁▁▁▁▁▁▇
##
## ── Variable type:POSIXct ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n min max median
## rDateTime 0 8511095 8511095 2013-01-01 2015-12-31 2013-12-26
## n_unique
## 350329 Runtime
Analysis completed in 193.44 seconds ( 3.22 minutes) using knitr in RStudio with R version 3.4.4 (2018-03-15) running on x86_64-pc-linux-gnu.
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 3.4.4 (2018-03-15)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 16.04.6 LTS
##
## Matrix products: default
## BLAS: /usr/lib/libblas/libblas.so.3.6.0
## LAPACK: /usr/lib/lapack/liblapack.so.3.6.0
##
## locale:
## [1] LC_CTYPE=en_NZ.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_NZ.UTF-8 LC_COLLATE=en_NZ.UTF-8
## [5] LC_MONETARY=en_NZ.UTF-8 LC_MESSAGES=en_NZ.UTF-8
## [7] LC_PAPER=en_NZ.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_NZ.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] kableExtra_1.1.0 ggplot2_3.2.1
## [3] skimr_1.0.7 forcats_0.4.0
## [5] drake_7.6.2 curl_4.1
## [7] GREENGridEECA_0.0.0.9000 GREENGridData_1.0
## [9] lubridate_1.7.4 here_0.1
## [11] data.table_1.12.2
##
## loaded via a namespace (and not attached):
## [1] storr_1.2.1 progress_1.2.2 tidyselect_0.2.5
## [4] xfun_0.9 purrr_0.3.2 reshape2_1.4.3
## [7] colorspace_1.4-1 vctrs_0.2.0 viridisLite_0.3.0
## [10] htmltools_0.3.6 yaml_2.2.0 rlang_0.4.0
## [13] pillar_1.4.2 withr_2.1.2 txtq_0.1.6
## [16] glue_1.3.1 readxl_1.3.1 lifecycle_0.1.0
## [19] plyr_1.8.4 stringr_1.4.0 munsell_0.5.0
## [22] gtable_0.3.0 cellranger_1.1.0 rvest_0.3.4
## [25] evaluate_0.14 labeling_0.3 knitr_1.25
## [28] highr_0.8 Rcpp_1.0.2 readr_1.3.1
## [31] backports_1.1.4 scales_1.0.0 filelock_1.0.2
## [34] webshot_0.5.1 hms_0.5.1 digest_0.6.20
## [37] stringi_1.4.3 bookdown_0.13 dplyr_0.8.3
## [40] rprojroot_1.3-2 grid_3.4.4 cli_1.1.0
## [43] tools_3.4.4 magrittr_1.5 base64url_1.4
## [46] lazyeval_0.2.2 tibble_2.1.3 tidyr_1.0.0
## [49] crayon_1.3.4 pkgconfig_2.0.2 zeallot_0.1.0
## [52] xml2_1.2.2 prettyunits_1.0.2 httr_1.4.1
## [55] assertthat_0.2.1 rmarkdown_1.15 rstudioapi_0.10
## [58] R6_2.4.0 igraph_1.2.4.1 compiler_3.4.4References
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/.
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.