Job Application QJ45141

I. Introduction

This document aims to evaluate the Aurora Energy Network based on the disclosure data available on the Internet. Although, the availability of these general data, they require many manipulations to become workable. Despite the lack of specifics data to drive a deep study, I will gather some information in a simple descriptive analysis in the Chapter 2, and later in Chapter 3 a cross analysis between all company facets. In Chapter 4 I will show a benchmarking and a comparison among Aurora Energy and Similars Companies. Based on the previous chapters the Chapter 5 will bundle the results into a global understanding. Finally, in Chapter 6 the Conclusions.

I encourage the reader to reproduce this document on your computer. I made a great effort to comment every line to let this code understandable and reproducible. Fork me on Github.

II. Sinopsis

Despite the fact, the report is no finished and will be continually updated over the next days, this first release comes to show, very briefly, the outcomes from an initial study.

• The Aurora Energy Dashboard purpose was to provide a data visualisation of the New Zealand Electricity Market (similar to NZCC tableau), furthermore, a complete tool to registry each step of the analysis.

• The Descriptive Analysis in Chapter 2 was essential to a better understanding of the New Zealand Electricity Market, but there are plenty of typos and double entries, sometimes double entries with different values, which demand treatment and cross-validation with the other variables.

III. Document Structure

In this report, you can use the table of content on your left side to navigate, it is easy to use, very straightforward, and show all content until the second sub-level of each chapter.

1. General Information

In a collaborative mindset of the work environment, I need to give the credits to the person who has aided in this research directly and indirectly. For this reason, I put this section, to describe where I acquired the data, which software, and who developed or disclosure this on the web.

1.1. Data Sources

All data for this analysis was available on the internet.

• Electricity Distribution Services Input Methodologies Determination 2012 (NZCC 2018);

• Electricity distributors information disclosures (Commission 2018a)

• Aurora Energy Website

• GeoJSON file

Most of the features of this document are Open Source and free for use.

1.2. Softwares

I performed this studies adopting the R Language (Ihaka and Gentleman 1996), which was created by Ross Ihaka and Robert Gentleman, both researchers of the University of Auckland in 1995. So, I employed as work environment the RStudio IDE with the following versions:

• R Version 3.5.1 (R Core Team 2018) (Website);

• RStudio Version 1.1.456 (Website).

1.3. A briefly introduction about data

Unfortunately, the dataset provided by the New Zealand Commerce Commission (NZCC) is not a tidy dataset according to (Grolemund 2018), and for this reason, I have created a new version of the database so-called neat database.

One reason to make a great effort to registry all data modification is due to this document must be reproducible, reusable for later improvements implementation (with minors adjustments), and the most important is anyone can update it without much effort (time spent).

2. Descriptive Analysis

In this chapter, I will show a straightforward statistical descriptive without the intention of deep understanding and what drive the results. I only want to know the big picture of the company, what is the trend and the overall rates. For this reason, this chapter is very long and exhaustively. You may want to waived this chapter to the Chapter 3, which is richier in analysis.

2.1. Distribution Network in Otago

Aurora Energy is a Line company of New Zealand, located majority in Otago Regional and a minor part in Southland Regional. According to the 2018 Annual Report supplies energy to almost 90,000 homes(Energy 2018), which represents more than 89,000 consumers in 6,683 lines kilometres. Geographically, the company share the Otago Regional electricity distribution with OtagoNet and for this reason has two networks: Central Otago and Dunedin. Figure 1, acqured at (Commission 2018b), shows the concession area of Aurora Energy within Otago Regional and Southland Regional.

Aurora Energy Concession Area

New Zealand Map

For the sake of this report, I will name these two regions as: Dunedin Regional and Central Otago Regional.

Due to the outstanding quantity of information to manage and fit, I have created a mind map to this report. I will share the outcome of this mind map, which helped me so much.

From now, the rest of chapter2 will be exclusively about descriptive statistics to produce an in-depth overview of Aurora Energy network, which will support better conclusions and analysis.

2.2. Network

This short chapter was to count the consumers’ number, distributed energy, and losses.

2.2.1. Consumers

As shown in Table 1, both Regional has increased past these 6 years, but the Central Otago showed a higher growth rate (increase more than 10% in 6 years) as shown in Graphic 1. The majority of consumer was based in Dunedin Regional, which represents about 62% of the total consumer. It is also possible to see a increasing trend.

Based on it, the Table 1 represents the consumers of each Division.

The majority of consumer was located in Dunedin, about 62.58% which represent more than 55.000 consumer, and almost 33.000 consumer was settled in Central Otago. The trend in the last 5 year is the Central Otago increasing its participation on the total share, although Dunedin also increase its connnection number. The growth observed in these last 5 years was 4.04% in Otago Regional, but looking Central Otago separetaly its growth reach 8.95%. For this reason, the Central Otago could sature your power supply.

Table 1

Consumers in Aurora Energy

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total Consumers
2,018	33,959	37.90	55,534	61.97	89,609
2,017	32,943	37.31	55,259	62.58	88,305
2,016	31,876	36.69	54,912	63.21	86,870
2,015	31,119	36.24	54,662	63.66	85,863
2,014	30,795	36.01	54,638	63.89	85,515
2,013	30,237	35.63	54,557	64.28	84,875

Graphic 1

Conclusions:

• The overall is a positive growth rate with Central Otago growing 1.95%/year (annualized rate) and Dunedin Regional 0.30%/year (annualized rate);
• In Graphic 1 is possible to see a slight positive trend line.
• The net change in Central Otago Regional was 3722 and Dunedin Regional was 977, this explains the increasing share in Central Otago Regional.

2.2.2. Total Energy Entering

Total energy entering is calculated based on the Equation (1).

\[\begin{equation} \small E_{entering} = E_{delivered,GXP} + E_{supplied,DR} - E_{exported,GXP} + E_{other,EDB} \end{equation}\]

\(\small \begin{array}{l l} E_{entering}: & \text{Total Energy Entering in Aurora Energy Network [MWh/year]} \\ E_{delivered,GXP}: & \text{Energy Delivered at Grid Exit Points [MWh/year]} \\ E_{supplied,DR}: & \text{Distributed Energy Supplied [MWh/year]} \\ E_{exported,GXP}: & \text{Energy Exported to GPXs [MWh/year]} \\ E_{other,EDB}: & \text{Net electricity supplied to (from) other EDBs [MWh/year]} \\ \end{array}\)

Table 2.1

Total Energy Entering in Aurora Energy Network

Year	Network	Energy Delivered at GXP [MWh/year]	Distributed Energy Supplied [MWh/year]	Energy Exported to GPXs [MWh/year]	Net electricity supplied to (from) other EDBs [MWh/year]	Total Energy Entering [MWh/year]
2,018	All	1,121	316	37	-1	1,400
2,017	All	1,077	332	46	-1	1,364
2,016	All	1,101	323	36	-1	1,388
2,015	All	1,069	324	47	-1	1,347
2,014	All	1,056	300	36	-1	1,321
2,013	All	1,058	315	44	-1	1,330
Central Otago
2,018	CentralOtago	419	166	35	0	550
2,017	CentralOtago	388	172	42	0	518
2,016	CentralOtago	395	158	33	0	520
2,015	CentralOtago	357	172	44	0	485
2,014	CentralOtago	332	156	34	0	454
2,013	CentralOtago	319	167	42	0	443
Dunedin
2,018	Dunedin	702	150	2	0	849
2,017	Dunedin	689	160	4	0	846
2,016	Dunedin	706	165	3	0	867
2,015	Dunedin	713	152	3	0	862
2,014	Dunedin	724	144	2	0	866
2,013	Dunedin	740	148	2	0	886

Table 2.2

Total Energy Entering in Aurora Energy Network

	Central Otago		Dunedin
Year	Central Otago [MWh/Year]	[%]	Dunedin [MWh/Year]	[%]	Total Energy Entering [MWh/Year]
2018	550.13	39.28	849.47	60.66	1400.39
2017	517.84	37.96	845.57	61.99	1364.10
2016	519.91	37.46	867.41	62.49	1388.00
2015	484.83	35.99	861.67	63.96	1347.12
2014	454.08	34.38	866.09	65.58	1320.76
2013	443.12	33.32	886.18	66.63	1329.92

Graphic 2.1

Graphic 2.2

Conclusions:

• Although the global trend is positive the Total Energy Entering in Dunedin Regional is declining over the years. Oppositely, Otago Central has a growth rate of 31.72% from 2013 to 2018, which is 4.7% per year;
• As a result of this high increase in Otago Regional, the share in the Total Energy Entering has increased from 33.32% in 2013 to 39.28% in 2018;
• Table 2.1 shows the components share, it noticeable the Energy Delivered at GXP was the principal component, which represents 80.06% in 2018, the other components keep almost steadily over the years.

2.2.3. Total Energy Delivered to ICPs

Total energy delivered is calculated based on the Equation (2).

\[\begin{equation} \small E_{delivered,ICP} = E_{entering} - LOSS \end{equation}\]

\(\small \begin{array}{l l} E_{delivered,ICP}: & \text{Total energy delivered to ICPs [MWh/year]} \\ E_{entering}: & \text{Total Energy Entering in Aurora Energy Network [MWh/year]} \\ LOSS: & \text{Losses [MWh/year]} \\ \end{array}\)

Table 3.1

Total Energy Delivered to ICPs in Aurora Energy Network

Year	Network	Total Energy Entering [MWh]	Losses [MWh]	Total Energy Delivered [MWh]
2,018	All	1,400	92	1,308
2,017	All	1,364	80	1,284
2,016	All	1,388	85	1,303
2,015	All	1,347	99	1,248
2,014	All	1,321	71	1,250
2,013	All	1,330	81	1,249
Central Otago
2,018	CentralOtago	550	42	508
2,017	CentralOtago	518	31	487
2,016	CentralOtago	520	40	480
2,015	CentralOtago	485	44	441
2,014	CentralOtago	454	21	433
2,013	CentralOtago	443	28	415
Dunedin
2,018	Dunedin	849	50	799
2,017	Dunedin	846	49	796
2,016	Dunedin	867	45	823
2,015	Dunedin	862	62	799
2,014	Dunedin	866	50	816
2,013	Dunedin	886	45	842

##            used (Mb) gc trigger  (Mb) max used (Mb)
## Ncells  1143006 61.1    1894651 101.2  1143006 61.1
## Vcells 10601287 80.9   54320312 414.5 10601287 80.9

Table 3.2

Losses

	Central Otago		Dunedin
Year	[MWh]	[%]	[MWh]	[%]	[MWh]
2018	41.64	45.21	50.38	54.70	92.10
2017	30.56	38.23	49.36	61.75	79.93
2016	39.85	47.13	44.68	52.85	84.55
2015	43.78	44.23	62.36	63.00	98.98
2014	20.73	29.41	49.75	70.57	70.50
2013	28.32	34.98	44.64	55.14	80.96

Table 3.3

Losses Comparison

	Central Otago			Dunedin			Aurora Energy
Year	Energy Entering [MWh]	Losses [MWh]	[%]	Energy Entering [MWh]1	Losses [MWh]1	[%]1	Energy Entering [MWh]2	Losses [MWh]2	[%]2
2018	550.13	41.64	7.57	849.47	50.38	5.93	1400.39	92.10	6.58
2017	517.84	30.56	5.90	845.57	49.36	5.84	1364.10	79.93	5.86
2016	519.91	39.85	7.66	867.41	44.68	5.15	1388.00	84.55	6.09
2015	484.83	43.78	9.03	861.67	62.36	7.24	1347.12	98.98	7.35
2014	454.08	20.73	4.57	866.09	49.75	5.74	1320.76	70.50	5.34
2013	443.12	28.32	6.39	886.18	44.64	5.04	1329.92	80.96	6.09

Graphic 3.1

Graphic 3.2

Graphic 3.3

Conclusions:

• Central Otago has the highest losses, about 8.19% in 2018, supplying only 38.87% of the total energy delivered to ICPs, which is 508 MWh/year. While Dunedin Regional grant energy to more than 61% (799 MWh/year) with losses reaching 6.30%.

Typos

• Some problems was identified in 2014 and 2015.

2.4.1.1. GXP Energy Delivered

The GXP Energy Delivered is a component of Total Energy Entering in Aurora Energy Network.

Table 4

GXP Energy Supplied by Network

	Central Otago		Dunedin
Year	Central Otago [MWh]	[%]	Dunedin [MWh]	[%]	Total [MWh]
2018	419.38	37.40	701.84	62.60	1121.22
2017	388.00	36.02	689.24	63.98	1077.24
2016	394.82	35.87	705.77	64.13	1100.59
2015	356.60	33.35	712.64	66.65	1069.23
2014	332.25	31.46	723.76	68.54	1056.01
2013	318.58	30.10	739.76	69.90	1058.34

Graphic 4

Conclusions:

• It is not visible any trend or disturbs.

• GXP Energy Delivered is the principal component and determines the trend. It is 85.7% of Total energy delivered to ICPs.

2.4.1.2. Distributed Energy Delivered

It is also a component of Total Energy Entering in Aurora Energy Network.

Table 5

Distributed Energy Supplied by Network

	Central Otago		Dunedin
Year	Central Otago [MWh]	[%]	Dunedin [MWh]	[%]	Total [MWh]
2018	165.91	52.57	149.68	47.43	315.60
2017	172.04	51.75	160.41	48.25	332.45
2016	157.79	48.89	164.97	51.11	322.76
2015	172.32	53.17	151.75	46.83	324.06
2014	155.75	51.89	144.42	48.11	300.17
2013	166.85	52.95	148.25	47.05	315.10

Graphic 5

Conclusions:

• It is not visible any trend or disturbs.

2.4.1.3. Exported Energy to GXPs

It is also a component of Total Energy Entering in Aurora Energy Network.

Table 6

Energy Exported to GPXs

	Central Otago		Dunedin
Year	Central Otago [MWh]	[%]	Dunedin [MWh]	[%]	Total [MWh]
2,018	35.14	94.49	2.05	5.51	37.19
2,017	42.19	91.18	4.08	8.82	46.28
2,016	32.70	90.76	3.33	9.24	36.03
2,015	44.08	94.20	2.71	5.80	46.80
2,014	33.92	94.20	2.09	5.80	36.01
2,013	42.31	95.85	1.83	4.15	44.14

Graphic 6

Conclusions:

• It is not visible any trend or disturbs.

2.3. Assets

This subchapter aims to summarize the quantity of all network and non-network assets in both areas of Aurora Energy.

2.2.1. Network Assets

In this subchapter, I will point out the quantity of each component which is related to the Network such as Length of LV Lines, Poles, Capacitor Banks, etc.

2.2.1.1. Lines and Cable

The equation (3) shows the network length composition of Aurora Energy.

\[\begin{equation} \small L_{TOTAL} = L_{CO} + L_{DU} \end{equation}\]

\(\small \begin{array}{l l} L_{TOTAL}: & \text{Total length (includes Overhead lines and Underground cables) in Aurora Energy Network [km]} \\ L_{CO}: & \text{Total length (includes Overhead lines and Underground cables) in Central Otago Regional [km]} \\ L_{DU}: & \text{Total length (includes Overhead lines and Underground cables) in Dunedin Regional [km]} \\ \end{array}\)

Table 7 shows the length by Regional and Graphic 7 shows the trend.

Table 7

Network Length in each Regional

	Central Otago		Dunedin
Year	Central Otago [km]	[%]	Dunedin [km]	[%]	Total [km]
2,018	3,749	56	2,925	44	6,683
2,017	3,624	59	2,511	41	6,135
2,016	3,517	60	2,353	40	5,878
2,015	3,461	60	2,347	40	5,815
2,014	3,436	59	2,516	43	5,796
2,013	3,267	59	2,269	41	5,543

Graphic 7.1

Graphic 7.2

Conclusions:

• By the Table 7 is possible to see Central Otago Regional has a longer network length than Dunedin Regional;
• It is necessary to point out the large investment in Dunedin Regional, which extended more than 400 kilometres in one year (about 16.49%). Excluding this leap in network length in Dunedin, the trend line shows a steady growth rate.

A) Overhead Lines (OH)

The equation (4) shows the network length composition of Aurora Energy in respect of Overhead Lines and Underground Cables.

\[\begin{equation} \small L_{OH,TOTAL} = L_{OH,CO} + L_{OH,DU} \end{equation}\]

\(\small \begin{array}{l l} L_{OH,TOTAL}: & \text{Total length Overhead lines in Aurora Energy [km]} \\ L_{OH,CO}: & \text{Total length Overhead lines in Central Otago Regional [km]} \\ L_{OH,CU}: & \text{Total length Overhead lines in Dunedin Regional [km]} \\ \end{array}\)

Table 8 shows the Overhead Lines length in each Regional.

Table 8

Overhead Lines in Aurora Energy

	Central Otago		Dunedin
Year	Central Otago [km]	[%]	Dunedin [km]	[%]	Total [km]
2,018	2,252	51	2,147	49	4,399
2,017	2,186	56	1,748	44	3,934
2,016	2,183	56	1,707	44	3,890
2,015	2,183	56	1,707	44	3,890
2,014	2,190	56	1,711	44	3,901
2,013	2,190	56	1,708	44	3,898

Graphic 8

Conclusions:

• Until 2017, most of the overhead lines, about 56%, was in Central Otago Regional and the proportion was stable (Table 8). However, in 2018 the Overhead lines in Dunedin leap up around 22.8% comparing with Overhead lines length in 2017.

B) Underground Cables (UG)

The equation (5) shows the Underground cables length composition in Aurora Energy.

\[\begin{equation} \small L_{UG,TOTAL} = L_{UG,CO} + L_{UG,DU} \end{equation}\]

\(\small \begin{array}{l l} L_{UG,TOTAL}: & \text{Total length Underground cables in Aurora Energy [km]} \\ L_{UG,CO}: & \text{Total length Underground cables in Central Otago Regional [km]} \\ L_{UG,CU}: & \text{Total length Underground cables in Dunedin Regional [km]} \\ \end{array}\)

Table 9

Underground Cables in Aurora Energy

	Central Otago		Dunedin
Year	Central Otago [km]	[%]	Dunedin [km]	[%]	Total [km]
2,018	1,497	66	778	34	2,284
2,017	1,438	65	763	35	2,201
2,016	1,334	67	646	33	1,988
2,015	1,278	66	639	33	1,925
2,014	1,246	66	805	42	1,895
2,013	1,077	65	561	34	1,645

Graphic 9

Conclusions:

The Central Otago regional is in charge of 66% of the total length of Underground Cables. Over the last 6 year the growth rate in both Regional was almost the same:

• From 2013 to 2018 Central Otago grew by 39%, and;
• Dunedin in the same period grew by 38.7%) as shown in the Graphic 4.

Typos:

In Table 4, I have found an inconsistency in the data provided in the Commission (2018a), aggregating the columns Central Otago and Dunedin it is different from Total Columns.

C) OH and UG Comparison

The equation (6) shows the network length composition of Aurora Energy in respect of Overhead Lines and Underground Cables.

\[\begin{equation} \small L_{TOTAL} = L_{OH} + L_{UG} \end{equation}\]

\(\small \begin{array}{l l} L_{TOTAL}: & \text{Total length (includes Overhead lines and Underground cables) in Aurora Energy Network [km]} \\ L_{OH}: & \text{Total length Overhead lines in Aurora Energy [km]} \\ L_{UG}: & \text{Total length Underground cables in Aurora Energy [km]} \\ \end{array}\)

Table 10

Overhead Lines and Underground Cables Comparison

	Overhead		Underground
Year	Overhead Lines [km]	[%]	Underground Cables [km]	[%]	Total [km]
2,018	4,399	66	2,284	34	6,683
2,017	3,934	64	2,201	36	6,135
2,016	3,890	66	1,988	34	5,878
2,015	3,890	67	1,925	33	5,815
2,014	3,901	67	1,895	33	5,796
2,013	3,898	70	1,645	30	5,543

Graphic 10

Conclusions:

There is a trend to migrate from Overhead Lines to Underground Cables or to opt to use Underground Cables. The Underground Cables growth rate is 20.57% in 6 years (3.17% per year).

D) Rural, Urban and Remoted OH

The Equation (7) shows the composition of Overhead Lines aggregating Rural, Urban and Remote Overhead Lines.

\[\begin{equation} \small L_{OH,TOTAL} = L_{OH,RURAL} + L_{OH,URBAN} + L_{OH,remote} \end{equation}\]

\(\small \begin{array}{l l} L_{OH,TOTAL}: & \text{Total length Overhead lines in Aurora Energy [km]} \\ L_{OH,RURAL}: & \text{Total length Rural Overhead lines in Aurora Energy [km]} \\ L_{OH,URBAN}: & \text{Total length Urban Overhead lines in Aurora Energy [km]} \\ L_{OH,remote}: & \text{Total length in Remoted or Rugged Areas [km]} \\ \end{array}\)

Table 11.1

Rural Lines in Aurora Energy

	Central Otago		Dunedin
Year	Central Otago [km]	[%]	Dunedin [km]	[%]	Total [km]
2,018	1,917.69	71.48	765.12	28.52	2,682.82
2,017	1,860.00	73.78	662.00	26.26	2,521.00
2,016	1,894.68	72.44	720.76	27.56	2,615.44
2,015	1,894.68	72.44	720.76	27.56	2,615.44
2,014	1,913.00	72.22	736.00	27.78	2,649.00
2,013	1,817.92	77.98	513.40	22.02	2,331.32

Table 11.2

Rural Line Length in comparison with Overhead Lines

	Central Otago			Dunedin			Otago Regional
Year	Rural [km]	Overhead [km]	[%]	Rural [km]	Overhead [km]	[%]	Rural [km]	Total Overhead [km]	[%]
2,018	1,917.69	2,251.52	85.17	765.12	2,147.18	35.63	2,682.82	4,398.70	60.99
2,017	1,860.00	2,186.00	85.09	662.00	1,748.00	37.87	2,521.00	3,934.00	64.08
2,016	1,894.68	2,182.97	86.79	720.76	1,706.98	42.22	2,615.44	3,889.95	67.24
2,015	1,894.68	2,183.00	86.79	720.76	1,707.11	42.22	2,615.44	3,890.11	67.23
2,014	1,913.00	2,190.00	87.35	736.00	1,711.00	43.02	2,649.00	3,901.00	67.91
2,013	1,817.92	2,189.88	83.01	513.40	1,707.72	30.06	2,331.32	3,897.60	59.81

Table 11.3

Urban Lines in Aurora Network

	Central Otago		Dunedin
Year	Central Otago [km]	[%]	Dunedin [km]	[%]	Total [km]
2,018	244.03	15.13	1,368.34	84.87	1,612.36
2,017	238.00	18.15	1,072.00	81.77	1,311.00
2,016	199.02	16.98	972.81	83.02	1,171.83
2,015	199.02	16.98	972.81	83.02	1,171.83
2,014	187.00	16.29	961.00	83.71	1,148.00
2,013	281.86	19.27	1,180.80	80.73	1,462.65

Table 11.4

Urban Line Length comparison with Overhead Lines

	Central Otago			Dunedin			Otago Regional
Year	Urban [km]	Overhead [km]	[%]	Urban [km]	Overhead [km]	[%]	Urban [km]	Total Overhead [km]	[%]
2,018	244.03	2,251.52	10.84	1,368.34	2,147.18	63.73	1,612.36	4,398.70	36.66
2,017	238.00	2,186.00	10.89	1,072.00	1,748.00	61.33	1,311.00	3,934.00	33.32
2,016	199.02	2,182.97	9.12	972.81	1,706.98	56.99	1,171.83	3,889.95	30.12
2,015	199.02	2,183.00	9.12	972.81	1,707.11	56.99	1,171.83	3,890.11	30.12
2,014	187.00	2,190.00	8.54	961.00	1,711.00	56.17	1,148.00	3,901.00	29.43
2,013	281.86	2,189.88	12.87	1,180.80	1,707.72	69.14	1,462.65	3,897.60	37.53

Table 11.5

Remote and/or Rugged Lines in Aurora Network

	Central Otago		Dunedin
Year	Central Otago [km]	[%]	Dunedin [km]	[%]	Total [km]
2,018	89.80	86.74	13.72	13.26	103.52
2,017	88.00	86.27	14.00	13.73	102.00
2,016	89.27	86.94	13.41	13.06	102.68
2,015	89.30	86.83	13.54	13.17	102.84
2,014	90.00	86.54	14.00	13.46	104.00
2,013	90.10	86.95	13.53	13.05	103.63

Table 11.6

Remote and/or Rugged Overhead Lines Comparison

	Central Otago			Dunedin			Otago Regional
Year	Urban [km]	Overhead [km]	[%]	Urban [km]	Overhead [km]	[%]	Urban [km]	Total Overhead [km]	[%]
2,018	89.80	2,251.52	3.99	13.72	2,147.18	0.64	103.52	4,398.70	2.35
2,017	88.00	2,186.00	4.03	14.00	1,748.00	0.80	102.00	3,934.00	2.59
2,016	89.27	2,182.97	4.09	13.41	1,706.98	0.79	102.68	3,889.95	2.64
2,015	89.30	2,183.00	4.09	13.54	1,707.11	0.79	102.84	3,890.11	2.64
2,014	90.00	2,190.00	4.11	14.00	1,711.00	0.82	104.00	3,901.00	2.67
2,013	90.10	2,189.88	4.11	13.53	1,707.72	0.79	103.63	3,897.60	2.66

Conclusions:

• Most of the Overhead Lines in Central Otago Regional is in Rural areas (85% in 2018), whereas the Rural Overhead line in Dunedin Regional represents only 35.6%.

• In an opposed way, the Dunedin Regional has 85% of the Urban network using Overhead lines, whereas in Otago Central Regional only 10.84% of the Urban network is Overhead lines.

2.2.1.2. Tree Management

Table 12 shows the length with Tree Management in each Regional.

Table 12.1

Tree Management Length in Aurora

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2,018	1,879.39	57.27	1,402.47	42.73	3,281.86
2,017	153.00	63.75	87.00	36.25	240.00
2,016	143.00	65.30	76.00	34.70	219.00
2,015	116.28	54.65	96.48	45.35	212.76
2,014	100.00	52.36	91.00	47.64	191.00
2,013	79.22	50.36	78.07	49.64	157.29

Table 12.2

Tree Management and Total Length Network Comparison

	Central Otago			Dunedin			Total
Year	Street [km]	Subtotal [km]	[%]	Street [km]	Subtotal [km]	[%]	Street [km]	Total Network [km]	%
2,018	1,879.39	3,748.87	50.13	1,402.47	2,925.49	47.94	3,281.86	6,682.91	49.11
2,017	153.00	3,624.00	4.22	87.00	2,511.00	3.46	240.00	6,135.00	3.91
2,016	143.00	3,517.07	4.07	76.00	2,353.18	3.23	219.00	5,877.51	3.73
2,015	116.28	3,460.83	3.36	96.48	2,346.59	4.11	212.76	5,814.68	3.66
2,014	100.00	3,436.00	2.91	91.00	2,516.00	3.62	191.00	5,796.00	3.30
2,013	79.22	3,266.64	2.42	78.07	2,268.72	3.44	157.29	5,542.64	2.84

Table 12.3

Tree Management and Overhead Lines Comparison

	Central Otago			Dunedin			Total
Year	Street [km]	Subtotal [km]	[%]	Street [km]	Subtotal [km]	[%]	Street [km]	Total Network [km]	%
2,018	1,879.39	2,251.52	83.47	1,402.47	2,147.18	65.32	3,281.86	4,398.70	74.61
2,017	153.00	2,186.00	7.00	87.00	1,748.00	4.98	240.00	3,934.00	6.10
2,016	143.00	2,182.97	6.55	76.00	1,706.98	4.45	219.00	3,889.95	5.63
2,015	116.28	2,183.00	5.33	96.48	1,707.11	5.65	212.76	3,890.11	5.47
2,014	100.00	2,190.00	4.57	91.00	1,711.00	5.32	191.00	3,901.00	4.90
2,013	79.22	2,189.88	3.62	78.07	1,707.72	4.57	157.29	3,897.60	4.04

Table 12.4

Tree Management and Overhead Lines Comparison

	Central Otago			Dunedin			Total
Year	Street [km]	Subtotal [km]	[%]	Street [km]	Subtotal [km]	[%]	Street [km]	Total Network [km]	%
2,018	1,879.39	1,917.69	98.00	1,402.47	765.12	183.30	3,281.86	2,682.82	122.33
2,017	153.00	1,860.00	8.23	87.00	662.00	13.14	240.00	2,521.00	9.52
2,016	143.00	1,894.68	7.55	76.00	720.76	10.54	219.00	2,615.44	8.37
2,015	116.28	1,894.68	6.14	96.48	720.76	13.39	212.76	2,615.44	8.13
2,014	100.00	1,913.00	5.23	91.00	736.00	12.36	191.00	2,649.00	7.21
2,013	79.22	1,817.92	4.36	78.07	513.40	15.21	157.29	2,331.32	6.75

Graphic 12.1

Graphic 12.2

Conclusions:

• Until 2017, there was a positive trend, which increases the tree management length over the years, but in 2018 the length spike from 240 kilometres to 3281 kilometres. It could be an outcome of a new method to determinate the tree management areas.

Typos:

I have found out this variable divided into two parts, which demanded two filters to compound this table.

• 2013 and 2014: Section -> 9c: Overhead lines and underground cables, Categgory -> Total overhead length, Sub-category -> Circuit length (km), Description -> Overhead circuit requiring vegetation management

• 2015, 2016 and 2017: Section -> Overhead lines and underground cables, Category -> Overhead circuit requiring vegetation management, Subcategoryv -> “Circuit length (km)

2.2.1.3. Coastline and Geothermal

Network length within 10 kilometres from Coastline or Geothermal.

Table 13.1

Coastline and Geothermal Area Length in Aurora

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2,018	0	0	2,286.78	100	2,286.78
2,017	0	0	2,266.00	100	2,266.00
2,016	0	0	2,132.27	100	2,132.27
2,015	0	0	2,125.08	100	2,125.08
2,014	0	0	2,131.00	100	2,131.00
2,013	0	0	1,947.88	100	1,947.88

Table 13.2

Coastline and Geothermal Area Length in Aurora

	Dunedin			Aurora Energy
Year	Coastline and Geothermal [km]	Length[km]	[%]	Coastline and Geothermal [km]	Length[km]	[%]
2,018	2,286.78	2,925.49	78.17	2,286.78	6,682.91	34.22
2,017	2,266.00	2,511.00	90.24	2,266.00	6,135.00	36.94
2,016	2,132.27	2,353.18	90.61	2,132.27	5,877.51	36.28
2,015	2,125.08	2,346.59	90.56	2,125.08	5,814.68	36.55
2,014	2,131.00	2,516.00	84.70	2,131.00	5,796.00	36.77
2,013	1,947.88	2,268.72	85.86	1,947.88	5,542.64	35.14

Graphic 13

Conclusions:

• The Dunedin Regional is a small parcel of the concession area, but concentrates most the load in a small strip of land, more than 78% of the network length was within 10 kilometres from the coastline.

2.2.1.4. Low Voltage (LV)

The Equation (8) shows the LV Network length composition of Aurora Energy.

\[\begin{equation} \small L_{LV,TOTAL} = L_{LV,OH} + L_{LV,UG} \end{equation}\]

\(\small \begin{array}{l l} L_{LV,TOTAL}: & \text{Total LV length in Aurora Energy Network [km]} \\ L_{LV,OH}: & \text{Total length of LV OH in Central Otago Regional [km]} \\ L_{LV,UG}: & \text{Total length of LV UG in Dunedin Regional [km]} \\ \end{array}\)

Table 14.1 is about the LV OH Lines and Table 14.2 about LV UG Cables.

Table 14.1

LV Lines in Aurora Network

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2,018	225.29	21.56	730.04	69.85	1,045.08
2,017	225.00	21.49	822.00	78.51	1,047.00
2,016	225.00	21.45	824.00	78.55	1,049.00
2,015	226.00	21.52	824.00	78.48	1,050.00
2,014	225.00	21.43	825.00	78.57	1,050.00
2,013	225.25	21.49	823.12	78.51	1,048.37

Table 14.2

LV Cables in Aurora Network

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2,018	676.35	70.85	272.65	28.56	954.63
2,017	656.00	70.84	265.00	28.62	926.00
2,016	639.00	70.92	257.00	28.52	901.00
2,015	620.00	70.70	251.00	28.62	877.00
2,014	604.00	70.64	245.00	28.65	855.00
2,013	537.19	70.52	219.27	28.78	761.81

Conclusions:

• LV Cables in Central Otago and Dunedin has been increasing over the years;
• The LV UG has 70.85% of the total length in Central Otago Regional.

2.2.1.5 LV OH/UG Street Lighting

Although Delta managed the street lighting maintenance in Dunedin City, Dunedin Regional has 154 kilometres in Street Lighting lines, and Otago Central Regional has 71 kilometres.

Table 15.1 and 15.2 shows the small participation in total network length.

Table 15.1

Table 1b - Street Lighting Line Length by Network

	Central Otago		Dunedin
Year	Central Otago [km]	[%]	Dunedin [km]	[%]	Total [km]
2,018	151.54	21.34	557.21	78.47	710.06
2,017	71.00	32.13	154.00	69.68	221.00
2,016	71.00	31.98	154.00	69.37	222.00
2,015	69.00	31.36	150.00	68.18	220.00
2,014	66.00	30.14	152.00	69.41	219.00
2,013	66.08	32.09	138.60	67.31	205.90

Table 15.2

Street Lighting Line Length by Network

	Central Otago			Dunedin			Total
Year	Street [km]	Subtotal [km]	[%]	Street [km]	Subtotal [km]	[%]	Street [km]	Total Network [km]	%
2,018	151.54	901.64	16.81	557.21	1,002.69	55.57	710.06	1,999.71	35.51
2,017	71.00	881.00	8.06	154.00	1,087.00	14.17	221.00	1,973.00	11.20
2,016	71.00	864.00	8.22	154.00	1,081.00	14.25	222.00	1,950.00	11.38
2,015	69.00	846.00	8.16	150.00	1,075.00	13.95	220.00	1,927.00	11.42
2,014	66.00	829.00	7.96	152.00	1,070.00	14.21	219.00	1,905.00	11.50
2,013	66.08	762.44	8.67	138.60	1,042.39	13.30	205.90	1,810.18	11.37

Graphic 15

Conclusions:

• Suddenly, LV Street lighting has increased from 221 kilometres in 2017 to 710 kilometres. It is necessary more info to take any conclusion.

2.2.1.6. High Voltage Subtransmission

The Equation (9) shows the HV Subtransmission Length composition of Aurora Energy.

\[\begin{equation} \small L_{SUB,TOTAL} = L_{SUB,Lines} + L_{SUB,cables} \end{equation}\]

\(\small \begin{array}{l l} L_{SUB,TOTAL}: & \text{Total Length of HV Subtransmission [km]} \\ L_{SUB,lines}: & \text{Lines Length of HV Subtransmission [km]} \\ L_{SUB,cables}: & \text{Cable Length of HV Subtransmission [km]} \\ \end{array}\)

Table 16.1

HV Subtransmission in Aurora Network

Year	HV Subtransmission Lines [km]	[%]	HV Subtransmission Cables [km]	[%]	Total HV Subtransmission [km]
2,018	525.80	84.98	92.97	15.02	618.77
2,017	526.00	84.98	93.00	15.02	619.00
2,016	526.00	84.98	93.00	15.02	619.00
2,015	513.00	84.93	91.00	15.07	604.00
2,014	512.00	84.49	94.00	15.51	606.00
2,013	512.66	84.53	93.81	15.47	606.46

Graphic 16.1

Table 16.2

HV Subtransmission Length by Regional

	Central Otago		Dunedin
Year	Central Otago [km]	[%]	Dunedin [km]	[%]	Total [km]
2,018	398.82	64.45	219.97	35.55	618.77
2,017	399.00	64.46	220.00	35.54	619.00
2,016	399.00	64.46	220.00	35.54	619.00
2,015	384.00	63.58	220.00	36.42	604.00
2,014	384.00	63.37	222.00	36.63	606.00
2,013	384.70	63.43	221.76	36.57	606.46

Graphic 16.2

Conclusions:

• High concentration of Subtransmission using Lines, almost 85% of the total;
• There is no evidence of a trend.

A. HV Subtransmission Lines

Table 17.1 shows the share of HV Subtransmission Lines in Otago Central Regional and Dunedin Regional, and Table 17.2 shows the share of HV Subtransmission Lines in Total HV Subtransmission Length for each Regional.

Table 17.1

HV Subtransmission Line in Aurora Energy

	Central Otago		Dunedin
Year	HV Sub. Lines [km]	[%]	HV Sub. Lines [km]	[%]	Total HV Sub. Lines [km]
2,018	382.09	72.67	143.72	27.33	525.80
2,017	382.00	72.62	144.00	27.38	526.00
2,016	382.00	72.62	144.00	27.38	526.00
2,015	369.00	71.93	144.00	28.07	513.00
2,014	368.00	71.88	144.00	28.12	512.00
2,013	369.03	71.98	143.63	28.02	512.66

Graphic 17

Table 17.2

HV Subtransmission Line in Total HV Subtransmission

	Central Otago			Dunedin			Total
Year	HV Sub. Lines [km]	Subtotal [km]	[%]	HV Sub. Lines [km]	Subtotal [km]	[%]	HV Sub [km]	Total Sub. Lines [km]	%
2,018	382.09	398.82	95.81	143.72	219.97	65.34	525.80	618.77	84.98
2,017	382.00	399.00	95.74	144.00	220.00	65.45	526.00	619.00	84.98
2,016	382.00	399.00	95.74	144.00	220.00	65.45	526.00	619.00	84.98
2,015	369.00	384.00	96.09	144.00	220.00	65.45	513.00	604.00	84.93
2,014	368.00	384.00	95.83	144.00	222.00	64.86	512.00	606.00	84.49
2,013	369.03	384.70	95.92	143.63	221.76	64.77	512.66	606.46	84.53

Conclusions:

• Based on Table 17.1 most length of HV Subtransmission Libes was in Central Otago, about 72%.
• 95% of Total HV Subtransmission in Central Otago was made by Lines.

B. HV Subtransmission Cables

Table 18.1 shows the share of HV Subtransmission Cables in Otago Central Regional and Dunedin Regional, and Table 18.2 shows the share of HV Subtransmission Cables in Total HV Subtransmission Length for each Regional.

Table 18.1

HV Subtransmission Cables in Aurora Energy

	Central Otago		Dunedin
Year	Central Otago [km]	[%]	Dunedin [km]	[%]	Total [km]
2,018	16.73	18.00	76.25	82.02	92.97
2,017	17.00	18.28	76.00	81.72	93.00
2,016	17.00	18.28	76.00	81.72	93.00
2,015	15.00	16.48	76.00	83.52	91.00
2,014	16.00	17.02	78.00	82.98	94.00
2,013	15.68	16.71	78.13	83.29	93.81

Graphic 18

Table 18.2

HV Subtransmission Cable Comparison

	Central Otago			Dunedin			Total
Year	HV Sub. Cable [km]	Subtotal [km]	[%]	HV Sub. Cable [km]	Subtotal [km]	[%]	HV Sub. Cable [km]	Total HV Sub. Cable [km]	%
2,018	16.73	398.82	4.19	76.25	219.97	34.66	92.97	618.77	15.02
2,017	17.00	399.00	4.26	76.00	220.00	34.55	93.00	619.00	15.02
2,016	17.00	399.00	4.26	76.00	220.00	34.55	93.00	619.00	15.02
2,015	15.00	384.00	3.91	76.00	220.00	34.55	91.00	604.00	15.07
2,014	16.00	384.00	4.17	78.00	222.00	35.14	94.00	606.00	15.51
2,013	15.68	384.70	4.08	78.13	221.76	35.23	93.81	606.46	15.47

Conclusions:

• It is the inverse of HV Subtransmission Lines. The predominance of HV Subtransmission Cables in Dunedin (almost 82%), which is about 93% of the Total HV Subtransmission Length.

2.2.1.7. High Voltage Lines

Central Otago Regional has 68% of the total length of HV Lines, which is 1,573 kilometres.

Table 19

HV Lines in Aurora Network in Aurora

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2,018	1,573.13	68.05	738.53	31.95	2,311.64
2,017	1,576.00	68.08	740.00	31.97	2,315.00
2,016	1,576.00	68.05	740.00	31.95	2,316.00
2,015	1,588.00	68.21	740.00	31.79	2,328.00
2,014	1,593.00	68.28	740.00	31.72	2,333.00
2,013	1,595.60	68.29	740.97	31.71	2,336.57

Graphic 19

Conclusion:

• The length stayed almost constant during the last 6 years.

2.2.1.8. Poles

\[\begin{equation} \small POLE_{total} = POLE_{wood} + POLE_{concrete} + POLE_{other} \end{equation}\]

\(\small \begin{array}{l l} POLE_{total}: & \text{Total poles quantity} \\ POLE_{wood}: & \text{Quantity of Wood Poles} \\ POLE_{concrete}: & \text{Quantity of Concrete Poles} \\ POLE_{other}: & \text{Other types Quantity of Poles} \\ \end{array}\)

To create the Table 17, I have excluded the Other type of Poles due to the minor relevance to the global results.

Table 20

Poles in Aurora Network

Year	Wood Poles	[%]	Concrete Poles	[%]	Total
2,018	28,841	53.41	25,158	46.59	53,999
2,017	30,820	57.12	23,132	42.88	53,952
2,016	31,757	58.76	22,290	41.24	54,047
2,015	32,376	60.18	21,427	39.82	53,803
2,014	32,942	61.28	20,814	38.72	53,756
2,013	33,325	62.05	20,383	37.95	53,708

Graphic 20

Conclusions:

• There are two trends, decreasing wood pole and increasing the concrete pole, which were complementary because the total quantity of Pole stays constant;
• Although the total network length has increased, the quantity of pole stayed almost constant.

A) Wood Poles, Concrete Poles

Table 21 shows the share of Wood Poles in each Regional.

Table 21

Wood Poles in Aurora Network

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2,018	15,670	54.33	13,171	45.67	28,841
2,017	16,802	54.52	14,018	45.48	30,820
2,016	17,215	54.21	14,542	45.79	31,757
2,015	17,507	54.07	14,869	45.93	32,376
2,014	17,803	54.04	15,139	45.96	32,942
2,013	18,034	54.12	15,291	45.88	33,325

Graphic 21.1

Graphic 21.2

Conclusions:

• Both Regional has the Wood Pole number decreasing with the same pace.

B. Concrete Poles and Steel Structure

Table 22 shows the share of Concrete Poles in each Regional.

Table 22

Concrete Poles in Aurora Network

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2,018	8,905	35.40	16,253	64.60	25,158
2,017	7,805	33.74	15,327	66.26	23,132
2,016	7,409	33.24	14,881	66.76	22,290
2,015	7,141	33.33	14,286	66.67	21,427
2,014	6,799	32.67	14,015	67.33	20,814
2,013	6,511	31.94	13,872	68.06	20,383

Graphic 22.1

Graphic 22.2

Conclusions:

• In opposite of Wood Poles, the Concrete Pole has been increasing over the year. It looks like to be replacing the olds wood pole by new concrete poles.

C. Other Poles

Since 2015 there is nothing registered as other type of poles, for this reason, I will omit this variable in my report.

2.2.1.9. Equipment

In this subchapter, I will investigate the number of equipment on the network such as Capacitor Banks, Voltage Regulators, and Switches.

A. Capacitor Banks and Voltage Regulator

Table 23.1 and 23.2 shows the number of capacitor banks and voltage regulator in Aurora Energy.

Table 23.1

Capacitor Banks in Aurora Network

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2018	0	0	3	100	3
2017	0	0	3	100	3
2016	0	0	3	100	3
2015	0	0	3	100	3
2014	0	0	3	100	3
2013	0	0	3	100	3

Table 23.2

Voltage Regulator in Aurora Network

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2018	29	93.55	2	6.45	31
2017	29	70.73	12	29.27	41
2016	30	73.17	11	26.83	41
2015	29	72.50	11	27.50	40
2014	26	66.67	13	33.33	39
2013	24	64.86	13	35.14	37

Conclusions:

• There are only three Capacitor Banks installed along the Aurora Energy Network. This equipment is suitable to decrease the losses and could help the company to attend the Regulator Standards;
• From 2017 to 2018 there was a decrease of 10 Voltage Regulator in Dunedin Regional. This equipment is adequate to raise the voltage in the final of the feeder but has a drawback increasing the current upstream (it means: increasing losses).

B. Zone substation

Table 24.1 shows the quantity of Zone Substations Switchgear in each Regional, Table 24.2 shows the quantity of Zone Substation Buildings in each Regional, and Table 24.3 shows the quantity of Zone Substation Transformer in each Regional.

Table 24.1

Zone substation switchgear in Aurora Network

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2,018	279	40.85	404	59.15	683
2,017	271	40.63	396	59.37	667
2,016	274	40.90	396	59.10	670
2,015	266	40.18	396	59.82	662
2,014	257	40.54	377	59.46	634
2,013	258	42.23	353	57.77	611

Graphic 24.1

Table 24.2

Zone substation Buildings in Aurora Network

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2,018	12	40.00	18	60.00	30
2,017	12	40.00	18	60.00	30
2,016	12	40.00	18	60.00	30
2,015	11	37.93	18	62.07	29
2,014	10	35.71	18	64.29	28
2,013	9	33.33	18	66.67	27

Graphic 24.2

Table 24.3

Zone Substation Transformer in Aurora Network

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2,018	30	47.62	33	52.38	63
2,017	32	47.76	35	52.24	67
2,016	32	47.76	35	52.24	67
2,015	32	47.76	35	52.24	67
2,014	31	46.97	35	53.03	66
2,013	31	46.97	35	53.03	66

Graphic 24.3

Conclusions:

• Although the quantity of Zone Substation Transformers was similar (52.35% in Dunedin Regional), Zone Substation Switchgear and Zone Substation Building have higher shares in Dunedin Regional (59% and 60%);
• Probably Substations located in Central Otago has more feeders.

C. Load Control

Both types of equipment in this subchapter were used to Load Control.

• Table 25.2 shows Relays used to Load Control.
• Table 25.1 shows the number of Centralised Plant.

Table 25.1

Centralised plant in Aurora Network

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2,018	3	50	3	50	6
2,017	3	50	3	50	6
2,016	3	50	3	50	6
2,015	3	50	3	50	6
2,014	3	50	3	50	6
2,013	3	50	3	50	6

Graphic 25.1

Table 25.2

Load Control - Relays in Aurora Network

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2,018	1,086	49.23	1,115	50.54	2,206
2,017	1,092	49.43	1,112	50.34	2,209
2,016	1,086	49.10	1,121	50.68	2,212
2,015	1,080	48.98	1,120	50.79	2,205
2,014	1,076	48.98	1,116	50.80	2,197
2,013	1,073	48.93	1,115	50.84	2,193

Graphic 25.2

Conclusions:

• Everything stayed unaltered.

D. Protection

Table 26 shows the number of Relays (applied to protection) over the Aurora Energy Network.

Table 26

Protection relays (electromechanical, solid state and numeric) in Aurora Energy

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2,018	230	21.48	840	78.43	1,071
2,017	173	36.34	303	63.66	476
2,016	174	36.63	301	63.37	475
2,015	173	36.19	305	63.81	478
2,014	166	35.10	307	64.90	473
2,013	135	31.47	294	68.53	429

Graphic 26

Conclusions:

• In 2018 the number of Relays leaps up from 476 in 2017 to 1,071 in 2018. Until 2017, the share was 63% in Dunedin Regional and 37% in Central Otago Regional.

E. SCADA and Communications

Table 27 shows the number of SCADA and communications equipment operating as a single system.

Table 27

SCADA and communications equipment operating as a single system in Aurora Energy

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2018	39	58.21	28	41.79	67
2017	64	58.72	45	41.28	109
2016	59	60.20	39	39.80	98
2015	58	59.79	39	40.21	97
2014	57	59.38	39	40.62	96
2013	57	60.00	38	40.00	95

Graphic 27

Conclusions:

• Lack of information to create a satisfactory conclusion. There are many kinds of equipment which could fit as SCADA.

2.2.2. Non-network Assets

This sub-chapter was idealized to registry all non-network assets. Unfortunately, I did not find any number of non-network asset in the document provided by the New Zealand Commerce Commission.

2.4. Realiability

This section was divided into 4 parts:

• Interruptions;
  • Interruptions rate;
  • SAIDI/SAIFI;
  • Cause;
• Interruptions Planned;
  • Interruptions rate;
  • SAIDI/SAIFI;
  • Cause;
• Interruptions Unplanned;
  • Interruptions rate;
  • SAIDI/SAIFI;
  • Cause;
• Consumers’ Restoration;
  • Less tahnthan 3 hours;
  • More than 3 hours.

2.4.1. Interruptions

The Equation (11) shows the Interruptions in Aurora Energy.

\[\begin{equation} \small INT_{TOTAL} = INT_{planned} + INT_{unplanned} \end{equation}\]

\(\small \begin{array}{l l} INT_{TOTAL}: & \text{Number of Interrutions in Aurora Energy Network} \\ INT_{planned}: & \text{Number of Planned Interruptions} \\ INT_{unplanned}: & \text{Number of Unplanned Interruptions} \\ \end{array}\)

The Table 28.1 shows the number of interruptions in each Regional and the total, and the Table 28.2 show the interruptions rate.

Table 28.1

Interruptions in each Regional

	Central Otago		Dunedin
Year	Interruptions	[%]	Interruptions	[%]	Total Interruptions
2,018	802	52.49	726	47.51	1,528
2,017	622	72.49	236	27.51	858
2,016	598	69.78	259	30.22	857
2,015	589	73.17	216	26.83	805
2,014	544	76.62	166	23.38	710
2,013	520	73.97	183	26.03	703

##            used (Mb) gc trigger  (Mb) max used (Mb)
## Ncells  1168854 62.5    1894652 101.2  1168854 62.5
## Vcells 10754482 82.1   34764999 265.3 10754482 82.1

Graphic 28

Table 28.2

Interruptions rate in Aurora Energy

	Central Otago			Dunedin			Aurora Energy
Year	Int.	[km]	[Int./km]	Int.	[km]	[Int./km]	Int.	[km]	[Int./km]
2,018	802	3,748.87	21.39	726	2,925.49	24.82	1,528	6,682.91	22.86
2,017	622	3,624.00	17.16	236	2,511.00	9.40	858	6,135.00	13.99
2,016	598	3,517.07	17.00	259	2,353.18	11.01	857	5,877.51	14.58
2,015	589	3,460.83	17.02	216	2,346.59	9.20	805	5,814.68	13.84
2,014	544	3,436.00	15.83	166	2,516.00	6.60	710	5,796.00	12.25
2,013	520	3,266.64	15.92	183	2,268.72	8.07	703	5,542.64	12.68

Conclusions:

• Although, the number of interruptions has been increasing since 2013, in 2018 the interruptions leap over 117.35%.

2.4.1.1. Global SAIDI and SAIFI

I estimated the percentage using a weighted average based on consumers number of each Regional, as shown in Equation (12). This same equation is used to calculate the Total SAIFI.

\[\begin{equation} \small SAIDI_{TOTAL} = SAIDI_{CO}\cdot\frac{CON_{CO}}{CON_{TOTAL}} + SAIDI_{DU}\cdot\frac{CON_{DU}}{CON_{TOTAL}} \end{equation}\]

\(\small \begin{array}{l l} SAIDI_{TOTAL}: & \text{Number of Interrutions in Aurora Energy Network} \\ SAIDI_{CO}: & \text{Number of Planned Interruptions} \\ SAIDI_{DU}: & \text{Number of Unplanned Interruptions} \\ CON_{TOTAL}: & \text{Total number of Consumer in Aurora Energy} \\ CON_{CO}: & \text{Total number of Consumer in Central Otago Regional} \\ CON_{DU}: & \text{Total number of Consumer in Dunedin Regional} \\ \end{array}\)

Table 29.1 shows the Total SAIDI incurred by the interruptions, and Table 29.2 shows the Total SAIFI incurred by the interruptions.

Table 29.1

SAIDI Total in Aurora Network

	Central Otago		Dunedin
Year	SAIDI [minutes]	[%]	SAIDI [minutes]	[%]	Total SAIDI [minutes]
2018	422.26	36.90	400.16	63.10	407.97
2017	319.43	62.83	106.52	37.17	185.10
2016	377.67	56.32	166.73	43.68	243.54
2015	217.44	60.92	80.99	39.08	130.02
2014	205.40	78.69	33.15	21.31	94.50
2013	153.13	73.65	33.51	26.35	75.61

Graphic 29.1

Table 29.2

SAIFI Total in Aurora Network

	Central Otago		Dunedin
Year	SAIFI [interruptions]	[%]	SAIFI [interruptions]	[%]	Total SAIFI [interruptions]
2018	4.15	42.28	3.14	57.72	3.52
2017	3.13	66.74	0.88	33.26	1.71
2016	3.86	58.97	1.53	41.03	2.38
2015	2.43	64.57	0.77	35.43	1.37
2014	2.66	79.60	0.41	20.40	1.21
2013	1.40	50.18	0.85	49.82	1.05

Graphic 29.2

Conclusions:

• As a consequence of the high number of total interruptions, the SAIDI and SAIFI have also increased.

2.4.2. Interruptions Planned

Table 30 shows the number of Planned Interruptions in each Regional and a percentage of the total.

Table 30

Planned Interruptions in Aurora Network

	Central Otago		Dunedin
Year	Interruptions	[%]	Interruptions	[%]	Total Interruptions
2018	477	51.35	452	48.65	929
2017	283	72.38	108	27.62	391
2016	238	81.23	55	18.77	293
2015	255	80.44	62	19.56	317
2014	224	87.16	33	12.84	257
2013	298	86.13	48	13.87	346

Graphic 30

Conclusions:

• Probably Aurora Energy was doing several works in all Aurora Energy Network.

2.4.2.1. SAIDI of Planned Interruptions

Table 31.1 shows the SAIDI from Planned Interruptions.

Table 31.1

SAIDI of Planned Interruptions in Aurora Network

	Central Otago		Dunedin
Year	[minutes]	[%]	[minutes]	[%]	Total [minutes]
2018	257.49	31.50	310.28	68.50	289.97
2017	79.05	45.76	52.81	54.24	62.48
2016	76.44	76.76	13.17	23.24	36.25
2015	55.30	82.34	6.89	17.66	24.33
2014	60.67	95.23	1.81	4.77	22.78
2013	58.53	95.11	1.84	4.89	21.81

Graphic 31.1

Graphic 31.2

Graphic 31.3

Conclusions:

• Based on the Graphics 31.2 and 31.3, most of the Planned Interruptions is related to Distribution Lines.

2.4.2.2. SAIFI of Planned Interruptions

Table 32.2 shows the SAIFI from SAIFI Interuptions.

Table 32.2

SAIFI of Planned Interruptions in Aurora Network

	Central Otago		Dunedin
Year	[interruptions]	[%]	[interruptions]	[%]	Total [interruptions]
2018	1.10	27.40	1.61	72.60	1.42
2017	0.47	54.87	0.22	45.13	0.31
2016	0.38	60.20	0.14	39.80	0.23
2015	0.27	79.90	0.04	20.10	0.12
2014	0.28	94.19	0.01	5.81	0.10
2013	0.28	85.09	0.03	14.91	0.12

Graphic 32.1

Graphic 32.2

Graphic 32.3

Conclusions:

• Based on the Graphics 32.2 and 32.3, most of the Planned Interruptions is related to Distribution Lines (replacement, renewal, extension, etc.).

2.4.3. Interruptions Unplanned

Table 33 shows the number of Unplanned Interruptions in each Regional and a percentage of the total.

Graphic 33.1

Table 33.1

Unplanned Interruptions in Aurora Network

	Central Otago		Dunedin
Year	Interruptions	[%]	Interruptions	[%]	Total Interruptions
2018	324	54.18	274	45.82	598
2017	338	72.53	128	27.47	466
2016	360	63.94	203	36.06	563
2015	334	68.44	154	31.56	488
2014	320	70.64	133	29.36	453
2013	222	62.18	135	37.82	357

Conclusions:

• Dunedin Regional has an increasing trend, but Central Otago has the majority of the Unplanned Interruptions (54.2%).

2.4.3.1. SAIDI of Unplanned Interruptions

Table 34 shows the SAIDI of Unplanned Interruptions in each Regional.

Table 34

SAIDI by Unplanned Interruptions in Aurora Network

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2018	164.75	50.40	89.87	49.60	117.99
2017	197.71	67.48	53.71	32.52	107.04
2016	301.23	53.90	146.66	46.10	202.91
2015	162.14	55.95	74.10	44.05	105.70
2014	144.73	73.36	31.34	26.64	71.72
2013	94.60	64.62	31.67	35.38	53.80

Graphic 34.1

Graphic 34.2

Graphic 34.3

Conclusions:

• Although the majority of the consumer was in Dunedin, the Graphic 34.2 shows Central Otago Regional has higher SAIDI in comparison with Dunedin Regional. The Graphic 34.1 shows the outcome of this high SAIDI in Central Otago Regional in the Global SAIDI.

2.4.3.2. SAIFI of Unplanned Interruptions

Table 35 shows the SAIFI of Unplanned Interruptions in each Regional.

Table 35

SAIFI by Unplanned Interruptions in Aurora Network

	Central Otago		Dunedin
Year	[interruptions]	[%]	[interruptions]	[%]	Total [interruptions]
2018	3.05	52.54	1.53	47.46	2.10
2017	2.28	66.03	0.66	33.97	1.26
2016	3.48	62.70	1.18	37.30	2.02
2015	2.16	63.06	0.73	36.94	1.25
2014	2.39	78.20	0.40	21.80	1.11
2013	1.12	45.51	0.82	54.49	0.93

Graphic 35.1

Graphic 35.2

Graphic 35.3

Conclusions:

• Similarly, with the SAIDI, the results in SAIFI has the same course.

2.4.4. Restoration

This subchapter details the Unplanned Interruptions in two categories.

• Consumer restored in less than 3 hours;
• Consumer restored in more than 3 hours.

2.4.4.1. Less than 3 hours

Table 36.1 shows the number of Unplanned Interruptions restored in less than 3 hours.

Table 36.1

Interruptions Unplanned restored in less than 3 hours in Aurora Energy

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2018	267	56.81	203	43.19	470
2017	260	76.02	82	23.98	342
2016	257	70.41	108	29.59	365
2015	268	74.44	92	25.56	360
2014	115	62.84	68	37.16	183
2013	173	60.49	113	39.51	286

Graphic 36.1

Graphic 36.2

Conclusions:

• The Graphic 36.2 shows in both Regional a kind of limit of attendance.

2.4.4.2. More than 3 hours

Table 37.1 shows the number of Unplanned Interruptions restored in more than 3 hours.

Table 37.1

Interruptions Unplanned restored in more than 3 hours in Aurora Network

	Central Otago		Dunedin
Year	Central Otago	[%]	Dunedin	[%]	Total
2018	57	44.53	71	55.47	128
2017	78	62.90	46	37.10	124
2016	103	52.02	95	47.98	198
2015	66	51.56	62	48.44	128
2014	205	75.93	65	24.07	270
2013	49	69.01	22	30.99	71

Graphic 37.1

Table 37.2

Unplanned Interruptions

Year	More than 3 hours	[%]	Less than 3 hours	[%]	Unplanned Interruptions
2,018	128	21.40	470	78.60	598
2,017	124	26.61	342	73.39	466
2,016	198	35.17	365	64.83	563
2,015	128	26.23	360	73.77	488
2,014	270	59.60	183	40.40	453
2,013	71	19.89	286	80.11	357

Graphic 37.2

Graphic 37.3

Conclusions:

• The Graphic 37.3 shows in both Regional a kind of limit of attendance.

2.5. Regulatory

2.5.1. Regulatory Profit

The Equation (13) shows the components of Regulatory Profit (including financial incentives and wash-ups).

\[\begin{equation} \small PROFIT_{regulatory} = PROFIT_{regulatory,before,tax} - TAX_{allowance} \end{equation}\]

\(\small \begin{array}{l l} PROFIT_{regulatory}: & \text{Regulatory Profit (including financial incentives and washups [000\$])} \\ TAX_{allowance}: & \text{Regulatory Tax Allowance [000\$]} \\ PROFIT_{regulatory,before,tax}: & \text{Regulatory Profit before tax [000\$]} \\ \end{array}\)

Table 38 shows the value of Regulatory Profit including financial incentives and wash-ups.

Table 38

Regulatory Profit (including financial incentives and wash-ups)

Year	Regulatory Profit Before Tax [000$]	Regulatory Allowance [000$]	Regulatory Profit [000$]
2,018	14,796	3,952	10,844
2,017	25,908	5,990	19,917
2,016	24,776	6,758	18,018
2,015	23,704	5,781	17,923
2,014	26,642	5,574	21,068
2,013	29,341	7,371	21,970

Graphic 38

Conclusions:

• The Company Regulatory Profit fell 49.36% from 2013 to 2018.

2.5.1.1. Regulatory Tax Allowance

The Equation (14) shows the components of the Regulatory Allowance.

\[\begin{equation} \small TAX_{allowance} = TAX_{corporate} + INCOME_{regulatory,taxable} \end{equation}\]

\(\small \begin{array}{l l} TAX_{allowance}: & \text{Regulatory Tax Allowance [000\$]} \\ TAX_{corporate}: & \text{Corporate Rate [%]} \\ INCOME_{regulatory,taxable}: & \text{Regulatory Taxable Income [000\$]} \\ \end{array}\)

Table 39

Regulatory Allowance Tax

Year	Regulatory taxable income [000$]	Corporate tax rate (%)	Regulatory Allowance [000$]
2,018	14,116	28%	3,952
2,017	21,395	28%	5,990
2,016	24,136	28%	6,758
2,015	20,647	28%	5,781
2,014	19,906	28%	5,574
2,013	26,326	28%	7,371

Conclusions:

• It is a percentage of Regulatory Profit before tax.

2.5.1.2. Regulatory Taxable Income

The Equation (15) shows the components of the Regulatory Taxable Income.

\[\begin{equation} \small INCOME_{regulatory,taxable} = PROFIT_{regulatory,before,tax} + (TAX_{add} - TAX_{ded}) \end{equation}\]

\(\small \begin{array}{l l} INCOME_{regulatory,taxable}: & \text{Regulatory Taxable Income [000\$]} \\ PROFIT_{regulatory,before,tax}: & \text{Regulatory Profit before tax [000\$]} \\ TAX_{add}: & \text{Regulatory Tax Addition [000\$]} \\ TAX_{ded}: & \text{Regulatory Deduction [000 \$]} \\ \end{array}\)

Table 40.1 shows the Tax Additions, Table 40.2 shows the Tax Deductions, and Table 40.3 shows the Regulatory Taxable Income.

Table 40.1

Tax Additions

	Regulatory Profit not taxable/deductible		Amortisation
Year	Income not Include [000$]	Expenditure or Loss [000$]	Initial differences [000$]	Revaluations [000$]	Total Addition [000$]
2,018	3,393	188	4,993	1,227	9,801
2,017	2,918	154	4,993	961	9,026
2,016	2,568	-18	4,993	893	8,436
2,015	1,957	-19	3,128	915	5,981
2,014	1,513	19	3,587	746	5,865
2,013	1,105	-16	3,809	875	5,773

Graphic 40.1

Table 40.2

Tax Deduction

	Regulatory Profit not taxable/deductible
Year	Income not Include [000$]	Expenditure or Loss [000$]	Discretionary Discount [000$]	Revaluations [000$]	Notional deductible interest [000$]	Total Deductions [000$]
2,018	0	0	0	3,886	6,595	10,481
2,017	0	0	0	7,381	6,158	13,539
2,016	0	0	0	1,940	7,136	9,076
2,015	0	0	0	273	8,766	9,038
2,014	4,879	0	0	4,879	7,722	12,601
2,013	0	0	0	2,734	8,788	8,788

Graphic 40.2

Table 40.3

Regulatory Profit Before Tax

	Taxes
Year	Addition [000$]	Deduction [000$]	Regulatory Profit before Tax [000$]	Regulatory Income Taxable [000$]
2,018	9,801	10,481	14,796	14,116
2,017	9,026	13,539	25,908	21,395
2,016	8,436	9,076	24,776	24,136
2,015	5,981	9,038	23,704	20,647
2,014	5,865	12,601	26,642	19,906
2,013	5,773	8,788	29,341	26,326

Graphic 40.3

Conclusions:

• Lack of informations about Income not Include;
• Over the years the difference between Addition and Deduction is decreasing.

2.5.1.3. Regulatory profit / (loss) before tax

The Equation (16) shows the components of the Regulatory Profit Before Tax.

\[\begin{equation} \small PROFIT_{regulatory,before,tax} = + PROFIT_{operanting,surplus} + (REVAL_{total} - DEPRE_{total}) \end{equation}\]

\(\small \begin{array}{l l} PROFIT_{regulatory,before,tax}: & \text{Regulatory Profit before tax [000\$]} \\ PROFIT_{operanting,surplus}: & \text{Operating Surplus [000\$]} \\ REVAL_{total}: & \text{Total Revaluation [000\$]} \\ DEPRE_{total}: & \text{Total Depreciation [000\$]} \\ \end{array}\)

Table 41 shows the Operating Suplus.

Table 41

Regulatory profit Before Tax

Year	Operating Surplus [000$]	Total Revaluation [000$]	Total Depreciation [000$]	Regulatory Profit before tax [000$]
2,018	24,444	3,886	13,533	14,796
2,017	31,363	7,381	12,836	25,908
2,016	35,154	1,940	12,318	24,776
2,015	35,372	273	11,941	23,704
2,014	33,236	4,879	11,473	26,642
2,013	37,875	2,734	11,268	29,341

Graphic 41

Conclusions:

• The Regulatory Profit Before Tax was decreasing from more than 29,3 millions in 2013 to 14,8 millions in 2018, almost the half.
• The depraciaton has a sligth trend to increase over the year.

2.5.1.4. Total Depreciation

Table 42 shows the components of Total Depreciation.

Table 42

Depreciation Segmentation

	Distribution and LV				Subtransmission		Network Assets
Year	OH [000$]	UG [000$]	Substation and Transformes [000$]	Switchgear [000$]	Subtransmission Lines [000$]	Subtransmission Cables [000$]	Non Network Assets [000$]	Other Network Assets [000$]	Zone Substation [000$]	Total Depreciation [000]
2,018	2,657	4,126	1,868	1,091	631	391	0	279	2,490	13,533
2,017	2,477	3,980	1,803	1,040	573	383	0	162	2,418	12,836
2,016	2,345	3,869	1,747	999	563	373	0	175	2,247	12,318
2,015	2,233	3,796	1,705	983	549	373	0	201	2,101	11,941
2,014	2,131	3,697	1,654	940	539	318	0	206	1,988	11,473
2,013	2,077	3,650	1,638	931	541	319	0	193	1,919	11,268

Graphic 42.1

Graphic 42.2

Conclusions:

• The depreciation over the years is increasing, the accumulated growth rate from 2013 to 2018 reached 20.1%.

2.5.1.5. Total Revaluation

Table 43 shows the Revaluation components, which was updated based on the CPI4.

Table 43

Revaluation Segmentation

	Distribution and LV				Subtransmission		Network Assets
Year	OH [000$]	UG [000$]	Substation and Transformes [000$]	Switchgear [000$]	Subtransmission Lines [000$]	Subtransmission Cables [000$]	Non Network Assets [000$]	Other Network Assets [000$]	Zone Substation [000$]	Total Revaluation [000]
2,018	614.1	1,396.1	574.1	226.1	166	98	0	110	701.1	3,885.5
2,017	1,135.0	2,722.0	1,122.0	435.0	291	197	0	92	1,387.0	7,381.0
2,016	289.0	733.0	301.0	115.0	80	53	0	23	346.0	1,940.0
2,015	39.0	106.0	43.0	17.0	11	8	0	3	46.0	273.0
2,014	691.0	1,923.0	778.0	302.0	212	115	0	56	802.0	4,879.0
2,013	379.0	1,088.0	442.0	172.0	123	67	0	28	435.0	2,734.0

Graphic 43.1

Graphic 43.2

Conclusions

• The Revaluation is leverage by the CPI4.

2.5.2. Total Regulatory Income

The Equation (17) shows the components of the Total Regulatory Income.

\[\begin{equation} \small INCOME_{total,regulatory} = COSTS_{recoverable,pass-through,wash-ups} + PROFIT_{operanting,surplus} + OPEX \end{equation}\]

\(\small \begin{array}{l l} INCOME_{total,regulatory}: & \text{Total Regulatory Income [000\$]} \\ COSTS_{recoverable,pass-through,wash-ups}: & \text{Pass-through and recoverable costs excluding financial incentives and wash-ups [000\$]} \\ PROFIT_{operanting,surplus}: & \text{Operating Surplus [000\$]} \\ OPEX: & \text{Operational expenditure [000\$]} \\ \end{array}\)

Table 44

Total Regulatory Income

Year	OPEX [000$]	Operanting Surplus [000$]	Pass-through and Recoverable Costs [000$]	Total Regulatory Income [000$]
2,018	35,344	24,444	36,923	96,711
2,017	27,472	31,363	37,270	96,105
2,016	25,173	35,154	34,402	94,729
2,015	23,608	35,372	34,483	93,463
2,014	22,317	33,236	29,712	85,265
2,013	18,641	37,875	31,387	87,903

Graphic 44

Conclusions:

• By the Graphic 44 the Operating Surplus is decreasing, and the OPEX is increasing.

2.5.2.1 Pass-through and recoverable costs

The Equation (18) shows the components of the Pass-through and recoverable costs.

\[\begin{equation} \small COSTS_{recoverable,pass-through,wash-ups} = RCOSTS_{recoverable} + PCOSTS_{pass-through} \end{equation}\]

\(\small \begin{array}{l l} COSTS_{recoverable,pass-through}: & \text{Pass-through and recoverable costs excluding financial incentives and wash-ups [000\$]} \\ RCOSTS_{recoverable}: & \text{Recoverable costs excluding financial incentives and wash-ups [000\$]} \\ PCOSTS_{pass-through}: & \text{Pass-through costs [000\$]} \\ \end{array}\)

Table 45

Pass-through and recoverable costs

Year	Recoverable costs excluding financial incentives and wash-ups [000$]	Pass-through costs [000$]	Pass-through and recoverable costs excluding financial incentives and wash-ups [000$]
2,018	35,773	1,150	36,923
2,017	35,895	1,375	37,270
2,016	33,166	1,236	34,402
2,015	33,014	1,469	34,483
2,014	27,457	2,255	29,712
2,013	28,390	2,997	31,387

Graphic 45.1

Graphic 45.2

Conclusions:

• In accordance with Graphic 45.2, the Pass-through costs have diminished over the year. Inversely, the Recoverable costs have increased.

2.5.2.2 Recoverable costs excluding financial incentives and wash-ups

The Equation (19) shows the components of the Recoverable costs excluding financial incentives and wash-ups.

\[\begin{equation} \small RCOSTS_{recoverable} = RCOSTS_{transpower} + INV_{transpower} + SYSOP_{services} + DG_{allowance} + RES_{allowance} + RCOSTS_{other} \end{equation}\]

\(\small \begin{array}{l l} RCOSTS_{recoverable}: & \text{Recoverable costs excluding financial incentives and wash-ups [000\$]} \\ RCOSTS_{transpower}: & \text{Electricity lines service charge payable to Transpower [000\$]} \\ INV_{transpower}: & \text{Transpower new investment contract charges [000\$]} \\ SYSOP_{services}: & \text{System operator services [000\$]} \\ DG_{allowance}: & \text{Distributed generation allowance [000\$]} \\ RES_{allowance}: & \text{Extended reserves allowance [000\$]} \\ RCOSTS_{other}: & \text{Other recoverable costs excluding financial incentives and wash-ups [000\$]} \\ \end{array}\)

Table 46

Recoverable costs excluding financial incentives and wash-ups

Year	Electricity lines service charge payable to Transpower [000$]	Transpower new investment contract charges [000$]	Distributed Generation Allowance or Avoided Transmission Charge [000$]	System operator services [000$]	Extended reserves allowance [000$]	Other recoverable costs excluding financial incentives and wash-ups [000$]	Recoverable costs excluding financial incentives and wash-ups [000$]
2,018	27,225	691	7,857	0	0	0	35,773
2,017	26,584	0	7,987	0	0	1,324	35,895
2,016	24,555	0	7,256	0	0	1,355	33,166
2,015	25,562	0	6,656	0	0	796	33,014
2,014	20,756	0	6,701	0	0	1,256	27,457
2,013	20,772	0	7,618	0	0	2,033	28,390

Graphic 46.1

Graphic 46.2

Conclusions:

• The recoverable costs were increasing due to the charge payable to Transpower.

2.5.2.3 Pass-through costs

The Equation (20) shows the components of the Pass-through costs.

\[\begin{equation} \small PCOSTS_{pass-through} = PCOSTS_{Rates} + LEVIES_{commerce} + LEVIES_{industry} + PCOSTS_{CPP} \end{equation}\]

\(\small \begin{array}{l l} PCOSTS_{pass-through}: & \text{Pass-through costs [000\$]} \\ PCOSTS_{Rates}: & \text{Rates [000\$]} \\ LEVIES_{commerce}: & \text{Commerce Act levies [000\$]} \\ LEVIES_{industry}: & \text{Industry levies [000\$]} \\ PCOSTS_{CPP}: & \text{CPP specified pass through costs [000\$]} \\ \end{array}\)

Table 47

Pass-through costs

	Levies or Rates [000$]
Year	Rates [000$]	Electricity Authority levies [000$]	Commerce Act levies [000$]	Other specified pass-through costs [000$]	Pass-through costs [000$]
2,018	716	301	133	0	1,150
2,017	926	309	140	0	1,375
2,016	893	243	100	0	1,236
2,015	979	324	166	0	1,469
2,014	673	164	162	1,256	2,255
2,013	655	200	109	2,033	2,997

Graphic 47

Conclusions:

• The Pass-through was decreasing over the years.

2.5.3. Line Charge Revenue

The Equation (21) shows the components of the Lines Charge.

\[\begin{equation} \small REVENUE_{line,charge} = INCOME_{total,regulatory} - OTHER_{regulated,income} - GAIN_{asset,disposal} \end{equation}\]

\(\small \begin{array}{l l} REVENUE_{line,charge}: & \text{Line charge revenue [000\$]} \\ INCOME_{total,regulatory}: & \text{Total Regulatory Income [000\$]} \\ OTHER_{regulated,income}: & \text{Other regulated income [000\$])} \\ GAIN_{asset,disposal}: & \text{Gains/Losses on asset disposals [000\$]} \\ \end{array}\)

Table 48

Line Charge Revenue

Year	Total Regulatory Income [000$]	Other regulated income [000$]	Gains/Losses on Asset Disposals [000$]	Line Charge Revenue [000$]
2,018	96,711	1,001	-562	96,272
2,017	96,105	3,468	0	92,637
2,016	94,729	3,462	0	91,267
2,015	93,463	2,633	0	90,830
2,014	85,265	3,225	-363	82,403
2,013	87,903	2,989	-81	84,995

Graphic 48

Conclusions:

• Both, Regulatory Income and Line Charge Revenue, are increasing at the same rate, from 2013 to 2018 the Regulatory Income has increased by 10.02%%.

2.5.4. Regulatory Asset Base (RAB)

The Equation (22) shows the components of Regulatory Asset Base.

\[\begin{equation} \small RAB_{closing} = RAB_{opening} + ASSETS_{commissioned} + ASSETS_{disposal} + REVAL_{total} - DEPRE_{total} + ADJ \end{equation}\]

\(\small \begin{array}{l l} RAB_{closing}: & \text{RAB in the end of the year [000\$]} \\ RAB_{opening}: & \text{RAB in the start of the year [000\$]} \\ ASSETS_{commissioned}: & \text{Assets Commissioned [000\$]} \\ ASSETS_{disposal}: & \text{Assets Disposasl [000\$]} \\ REVAL_{total}: & \text{Total Revaluation [000\$]} \\ DEPRE_{total}: & \text{Total Depreciation [000\$]} \\ ADJ: & \text{Adjustments [000\$]} \\ \end{array}\)

In the next subchapters, I will discuss each of these components, except Depreciation and Revaluation because both I have already detailed in chapter 2.5.1.4. and chapter 2.5.1.5..

2.5.1.1. RAB Opening Year

Table 49 shows the composition of the RAB at the beginning of the year. In Graphic 49.1 and 49.2 there are two visuals representations.

Table 49

Opening RAB Segmentation

	Distribution and LV				Subtransmission		Network Assets
Year	OH [000$]	UG [000$]	Substation and Transformes [000$]	Switchgear [000$]	Lines [000$]	Cables [000$]	Non Network [000$]	Other [000$]	Zone Substation [000$]	RAB Total [000$]
2,018	56,453.4	126,887	52,189	20,512	15,138	8,898	0	9,986	63,741	353,804
2,017	52,400.0	125,626	51,795	20,091	13,414	9,082	0	4,236	64,021	340,665
2,016	49,274.0	124,892	51,201	19,589	13,657	9,095	0	3,881	59,008	330,597
2,015	46,641.0	125,524	51,047	19,999	13,569	9,460	0	4,033	54,694	324,967
2,014	45,067.0	125,437	50,729	19,702	13,835	7,464	0	3,636	52,446	318,316
2,013	44,193.0	126,619	51,426	20,006	14,354	7,782	0	3,206	50,677	318,263

Graphic 49.1

Graphic 49.2

Conclusions:

• The most of the RAB has been allocated in Distribution (57.62% in 2018) and in Substation (32.77% in 2018)). The trend in both segments is positive, which means they are increasing, whereas Other Network Assets and Sub transmission stayed constant.

2.5.1.2. Assets Commissioned

The Equation (23) shows the components of the Total Assets Commissioned.

\[\begin{equation} \small ASSETS_{commissioned} = ASSETS_{acquired,related} + ASSETS_{acquired,regulated} + ASSETS_{commissioned,other} \end{equation}\]

\(\small \begin{array}{l l} ASSETS_{commissioned}: & \text{Assets Commissioned [000\$]} \\ ASSETS_{acquired,related}: & \text{Assets acquired from a related party [000\$]} \\ ASSETS_{acquired,regulated}: & \text{Assets acquired from a regulated supplier [000\$]} \\ ASSETS_{commissioned,other}: & \text{Other Assets Commissioned [000\$]} \\ \end{array}\)

Table 50 shows the total assets Commissioned in each year divided into segments.

Table 50.1

Asset Commissioned Segmentation

	Distribution and LV				Subtransmission		Network Assets
Year	Overhead	Underground	Substation and Transformes	Switchgear	Lines	Cables	Non Network	Other	Zone Substation	Total
2,018	38,234.4	3,048	3,014	2,442	1,142	206	758	1,009	482	50,335
2,017	5,395.0	2,519	1,075	1,026	2,006	2	0	5,820	751	18,594
2,016	5,182.0	3,870	2,040	1,386	240	307	0	507	6,914	20,446
2,015	4,827.0	3,058	1,816	556	626	0	0	46	6,369	17,298
2,014	3,014.0	1,861	1,194	935	61	2,199	0	547	3,563	13,374
2,013	3,372.0	3,244	1,449	691	105	87	0	640	3,107	12,695

Table 50.2

Assets Commissioned

Year	Other [000$]	Regulated Supplier [000$]	Related Party [000$]	Total Assets Commissioned [000$]
2,018	35,443	0	14,892	50,335
2,017	7,085	0	11,509	18,594
2,016	5,143	0	15,303	20,446
2,015	4,103	0	13,195	17,298
2,014	2,446	0	10,928	13,374
2,013	1,068	0	11,627	12,695

Graphic 50.1

Graphic 50.2

Conclusions:

• In 2018 Aurora Energy leaps up the amount of asset commissioned (reaching more than 50 million), most in Distribution segment, with a high focus in Overhead Lines. In the past years, Distribution and Substations share almost the totality of assets commissioned.

2.5.1.3. Assets Disposal

The Equation (24) shows the components of the Total Assets Disposals.

\[\begin{equation} \small ASSETS_{disposals} = ASSETS_{disposals,other} + ASSETS_{disposals,regulated} + ASSETS_{disposals,related} \end{equation}\]

\(\small \begin{array}{l l} ASSETS_{commissioned}: & \text{Assets Commissioned [000\$]} \\ ASSETS_{acquired,related}: & \text{Assets acquired from a related party [000\$]} \\ ASSETS_{acquired,regulated}: & \text{Assets acquired from a regulated supplier [000\$]} \\ ASSETS_{commissioned,other}: & \text{Other Assets Commissioned [000\$]} \\ \end{array}\)

Table 51 shows a resume of the Assets Disposals by Aurora Energy.

Table 51

Assets Disposal

	Assets Disposal
Year	Regulated Suppliers [000$]	Related Parties [000$]	Other [000$]	Total Disposals [000$]
2,018	0	0	570	570
2,017	0	0	0	0
2,016	0	0	0	0
2,015	0	0	0	0
2,014	0	0	129	129
2,013	0	0	0	0

Conclusions:

• Aurora Energy does not have much in Assets Disposals.

2.5.1.4. Adjustments

The Equation (25) shows the components of Adjustments.

\[\begin{equation} \small ADJS = ASSETS_{lost,found} + ASSETS_{asset,allocation} \end{equation}\]

\(\small \begin{array}{l l} ADJS: & \text{Assets Commissioned [000\$]} \\ ASSETS_{lost,found}: & \text{Assets acquired from a related party [000\$]} \\ ASSETS_{asset,allocation}: & \text{Assets acquired from a regulated supplier [000\$]} \\ \end{array}\)

Table 52 shows the Adjustments in RAB of Aurora Energy.

Table 52

RAB Adjustment

	Adjustment
Year	Lost and found assets adjustment [000$]	Adjustment resulting from asset allocation [000$]	Total Adjustment [000$]
2,018	0	0.43	0.43
2,017	0	-0.08	-0.08
2,016	0	0.20	0.20
2,015	0	0.38	0.38
2,014	0	0.49	0.49
2,013	0	-0.22	-0.22

Conclusions:

• Aurora Energy does not have problems with Lost and Found Assets and has insignificant expenditure with asset allocation.

2.5.1.5. Regulatory Asset Base Closing Year

Based on Equation 22, Table 53.1 aggregate the Assets Commissioned, Depreciation, Revaluation, etc. to compound the RAB Closing Year.

Table 53.1

Regulatory Asset Base (in the end of Year)

Year	(+) RAB in January [000$]	(+) Asset Commissioned [000$]	(+) Revaluation [000$]	(-) Depreciation [000$]	(-) Asset Disposal [000$]	(+) Adjustments [000$]	(=) RAB in December [000$]
2,018	353,804	50,335	3,885.5	13,533	570	0.43	394,085.6
2,017	340,665	18,594	7,381.0	12,836	0	-0.08	353,804.1
2,016	330,597	20,446	1,940.0	12,318	0	0.20	340,664.8
2,015	324,967	17,298	273.0	11,941	0	0.38	330,596.6
2,014	318,316	13,374	4,879.0	11,473	129	0.49	324,966.5
2,013	318,263	12,695	2,734.0	11,268	0	-0.22	322,424.2

Table 53.2

Closing Year RAB Segmentation

	Distribution and LV				Subtransmission		Network Assets
Year	Distribution OH [000$]	Distribution UG [000$]	Substation and Transformes [000$]	Switchgear [000$]	Subtransmission Lines [000$]	Subtransmission Cables [000$]	Non Network Assets [000$]	Other Network Assets [000$]	Zone Substation [000$]	RAB Closing Year [000$]
2,018	92,074.9	127,205.1	53,909.1	22,089.1	15,815	8,811	758	10,826	62,434.1	394,085.6
2,017	56,453.0	126,887.0	52,189.0	20,512.0	15,138	8,898	0	9,986	63,741.0	353,804.1
2,016	52,400.0	125,626.0	51,795.0	20,091.0	13,414	9,082	0	4,236	64,021.0	340,664.8
2,015	49,274.0	124,892.0	51,201.0	19,589.0	13,657	9,095	0	3,881	59,008.0	330,596.6
2,014	46,641.0	125,524.0	51,047.0	19,999.0	13,569	9,460	0	4,033	54,694.0	324,966.5
2,013	45,867.0	127,301.0	51,679.0	19,938.0	14,041	7,617	0	3,681	52,300.0	322,424.2

Graphic 53.1

Graphic 53.2

Conclusions:

• In a nutshell, in this last year, the atypical amount in Assets Commissioned was about 170.71% greater than in 2017. Generally, RAB has been increasing over the years from 2013 to 2018 the growth accumulated was about 22.23%.

2.6. OPEX

The Equation (26) shows the components of the Operational Expenditure (OPEX).

\[\begin{equation} \small OPEX = OPEX_{network} + OPEX_{non-network} \end{equation}\]

\(\small \begin{array}{l l} OPEX: & \text{Operational expenditure (OPEX) [000\$]} \\ OPEX_{network}: & \text{Network OPEX [000\$]} \\ OPEX_{non-setwork}: & \text{Non-network OPEX [000\$]} \\ \end{array}\)

Table 54 shows the OPEX divided into Network OPEX and Non-network OPEX.

Table 54.1

Operational Expenditure

Year	Network opex [000$]	Non-network opex [000$]	Operational expenditure [000$]
2,018	16,187	19,157	35,344
2,017	16,041	11,431	27,472
2,016	15,400	9,773	25,173
2,015	12,355	11,253	23,608
2,014	11,174	11,143	22,317
2,013	9,029	9,612	18,641

Table 54.2

Operating Cost Allocations

Year	Replacement and Renewal [000$]	System Operation and Network Support [000$]	Business Support [000$]	Service interruptions and emergencies [000$]	Vegetation management [000$]	Routine and corrective maintenance and inspection [000$]	Total Operating Cost [000$]
2,018	636	9,985	9,172	4,251	5,517	5,783	35,344
2,017	279	3,867	7,564	5,633	3,699	6,430	27,472
2,016	894	3,743	6,030	4,155	5,247	5,104	25,173
2,015	582	3,857	7,396	4,115	3,619	4,039	23,608
2,014	1,464	4,694	6,449	4,923	2,312	2,475	22,317
2,013	1,331	5,400	4,212	4,259	1,253	2,186	18,641

Graphic 54.1

Graphic 54.2

Graphic 54.3

Conclusions:

• Both expenditures were increasing, with similar growth rates, Network OPEX has increased 79.28% from 2013 to 2018, and Non-network OPEX in this same period has increased by 99.3%;
• There is a high trend of OPEX increasing.

---

2.6.1. Network OPEX

The Equation (27) shows the subcomponents of OPEX, which compound the Network OPEX.

\[\begin{equation} \small OPEX_{network} = SERV_{interruptions,emergencies} + VEG_{management} + RCMI + ASSET_{replacement,renewal} \end{equation}\]

\(\small \begin{array}{l l} OPEX_{network}: & \text{Network OPEX [000\$]} \\ SERV_{interruptions,emergencies}: & \text{Service interruptions and emergencies [000\$]} \\ VEG_{management}: & \text{Vegetation management [000\$]} \\ RCMI: & \text{Routine and corrective maintenance and inspection [000\$]} \\ ASSET_{replacement,renewal} & \text{Asset replacement and renewal [000\$]} \\ \end{array}\)

Table 55 shows the Network OPEX divided into its subcomponents.

Table 55

Network OPEX

Year	Service interruptions and emergencies [000$]	Vegetation management [000$]	Routine and corrective maintenance and inspection [000$]	Asset replacement and renewal [000$]	Network OPEX [000$]
2,018	4,251	5,517	5,783	636	16,187
2,017	5,633	3,699	6,430	279	16,041
2,016	4,155	5,247	5,104	894	15,400
2,015	4,115	3,619	4,039	582	12,355
2,014	4,923	2,312	2,475	1,464	11,174
2,013	4,259	1,253	2,186	1,331	9,029

##            used (Mb) gc trigger  (Mb) max used (Mb)
## Ncells  1176179 62.9    2357904 126.0  1176179 62.9
## Vcells 10776707 82.3   34764999 265.3 10776707 82.3

Graphic 55

Conclusions:

• In these 6 years of data, Vegetation Management has increased by 340.3%, which is aligned with routine and corrective maintenance and inspection. It also shows a constant expenditure amount to service interruptions and emergencies.

---

2.6.2. Non-network OPEX

The Equation (28) shows the subcomponents of OPEX, which compound the Non-network OPEX.

\[\begin{equation} \small OPEX_{non-network} = BUS_{support} + SYS_{support,operations} \end{equation}\]

\(\small \begin{array}{l l} OPEX_{non-setwork}: & \text{Non-network OPEX [000\$]} \\ BUS_{support}: & \text{Business support [000\$]} \\ SYS_{support,operations}: & \text{System operations and network support [000\$]} \\ \end{array}\)

Table 56 shows the Non-network OPEX divided into Business support and System operations.

Table 56

Non-network OPEX

Year	System operations and network support [000$]	Business support [000$]	Non-network OPEX [000$]
2,018	9,985	9,172	19,157
2,017	3,867	7,564	11,431
2,016	3,743	6,030	9,773
2,015	3,857	7,396	11,253
2,014	4,694	6,449	11,143
2,013	5,400	4,212	9,612

Graphic 56

Conclusions:

• Although, both subcomponents have increased over the years, in 2018 the growth was higher. System Operation and Network Support has increased 30% from 2017 to 2018.

---

2.6.3. OPEX Subcomponents

The Equation (29) shows other subcomponents of OPEX.

\[\begin{equation} \small OPEX_{subcomponents} = Efficiency + BILL_{direct} + R\&D + Insurance \end{equation}\]

\(\small \begin{array}{l l} OPEX_{subcomponents}: & \text{Subcomponents of Operational Expenditure [000\$]} \\ Efficiency: & \text{Energy efficiency and demand side management, reduction of energy losses [000\$]} \\ BILL_{direct}: & \text{Direct billing [000\$]} \\ ReD: & \text{Research and development [000\$]} \\ Insurance: & \text{Insurance [000\$]} \\ \end{array}\)

Table 57 shows the investments in Research and Development, Energy Efficient Programs, Insurances, etc.

Table 57

Subcomponents of Operational Expenditure

Year	Energy efficiency and demand side management, reduction of energy losses [000$]	Direct billing* [000$]	Research and development [000$]	Insurance [000$]	Total Subcomponets [000$]
2018	0	0	0	219	219
2017	0	0	0	195	195
2016	0	0	0	223	223
2015	0	0	0	258	258
2014	0	0	0	192	192
2013	0	0	0	192	192

Conclusions:

• Unfortunately, Aurora Energy invests neither in R&D and Energy Efficient. There is only expenditure on Insurance.

---

2.7. CAPEX

The Equation (30) shows the components of Capital Expenditure (CAPEX).

\[\begin{equation} \small CAPEX = ASSETS_{expenditure} + COSTS_{financing} + ASSETS_{vested} - FUN_{total} \end{equation}\]

\(\small \begin{array}{l l} CAPEX: & \text{Capital expenditure [000\$]} \\ ASSETS_{expenditure}: & \text{Expenditure on Assets [000\$]} \\ COSTS_{financing}: & \text{Cost of financing [000\$]} \\ ASSETS_{vested}: & \text{Value of vested assets [000\$]} \\ FUN_{total}: & \text{Value of capital contributions [000\$]} \\ \end{array}\)

Table 58 shows the CAPEX total amount from 2013 until 2018.

Table 58

CAPEX in Aurora Energy

Year	Cost of financing [000$]	Value of capital contributions [000$]	Value of vested assets [000$]	Expenditure on assets [000$]	CAPEX [000$]
2,018	0	4,751	0	69,297	64,546
2,017	0	3,499	0	30,138	26,639
2,016	0	6,114	0	29,040	22,926
2,015	0	4,434	0	29,162	24,728
2,014	0	4,087	0	15,919	11,832
2,013	0	3,043	0	17,642	14,599

Graphic 58.1

Graphic 58.2

Graphic 58.3

Conclusions:

• Although the CAPEX has increased about 342.13%, the total amount contributed by the consumers did not increase as the CAPEX grew (almost 56.13%).

---

2.7.1. Expenditure on Asset

The Equation (31) shows the components of Expenditure on Assets.

\[\begin{equation} \small ASSETS_{expenditure} = ASSETS_{network} + ASSETS_{non-network} \end{equation}\]

\(\small \begin{array}{l l} ASSETS_{expenditure}: & \text{Expenditure on Assets [000\$]} \\ ASSETS_{network}: & \text{Expenditure on Network Assets [000\$]} \\ ASSETS_{non-network}: & \text{Expenditure on Non-network Assets [000\$]} \\ \end{array}\)

Table 59 shows the amount allocated to Expenditure on Network Assets and Non-network Assets.

Table 59

CAPEX - Expenditure on Assets

Year	Network assets [000$]	Non-network assets [000$]	Expenditure on assets [000$]
2,018	68,341	956	69,297
2,017	30,138	0	30,138
2,016	29,040	0	29,040
2,015	29,162	0	29,162
2,014	15,919	0	15,919
2,013	17,642	0	17,642

Graphic 59

Conclusions:

• By the database, until 2017, Aurora Energy did not invest in Non-network.

---

2.7.2 Network Asset

The Equation (32) shows the components of Network Assets.

\[\begin{equation} \small ASSETS_{network} = EXP_{rse} + Connections + SYS_{growth} + ASSETS_{replacement,renewal} + ASSETS_{relocation} \end{equation}\]

\(\small \begin{array}{l l} ASSETS_{network}: & \text{Expenditure on Network Assets [000\$]} \\ EXP_{rse}: & \text{Total Reliability, Safety and Environment [000\$]} \\ Connections: & \text{Expenditure on Consumer Connections [000\$]} \\ SYS_{growth}: & \text{System Growth [000\$]} \\ ASSETS_{replacement,renewal}: & \text{Asset Replacement and Renewal [000\$]} \\ ASSETS_{relocation}: & \text{Asset Relocations [000\$]} \\ \end{array}\)

Table 60 shows the expenditures in each component of Network Asset.

Table 60

Network Asset

Year	Total reliability, safety and environment [000$]	Consumer connection [000$]	System growth [000$]	Asset replacement and renewal [000$]	Asset relocations [000$]	Network Asset [000$]
2,018	1,700	8,494	6,343	50,767	1,037	68,341
2,017	2,133	7,526	270	18,128	2,081	30,138
2,016	1,929	10,553	8,980	5,511	2,067	29,040
2,015	1,943	10,250	6,898	7,501	2,570	29,162
2,014	2,550	4,723	350	7,761	535	15,919
2,013	1,986	6,671	2,152	6,374	459	17,642

Graphic 60.1

Graphic 60.2

Graphic 60.3

Graphic 60.4

Conclusions:

• In 2017 and 2018, most of the Expenditure on Assets were in Relocations, Replacement and Renewal. The share of Asset Replacement and renewal reached 74.28% of the total in 2018 and 60.15% in 2017;
• The expenditure on new connections stayed steadily over the years.

---

2.7.2.1. Total Reliability, safety and environment

The Equation (33) shows the subcomponents of Total Reliability, safety and environment.

\[\begin{equation} \small EXP_{rse} = QUA_{supply} + LEGREG + SYS_{growth} + OTHER_{rse} \end{equation}\]

\(\small \begin{array}{l l} EXP_{rse}: & \text{Total Reliability, Safety and Environment [000\$]} \\ QUA_{supply}: & \text{Quality of Supply [000\$]} \\ LEGREG: & \text{Legislative and Regulatory [000\$]} \\ OTHER_{rse}: & \text{Other Reliability, Safety and Environment [000\$]} \\ \end{array}\)

Table 61

The Reliability, Safety and Environment

Year	Quality of supply [000$]	Legislative and regulatory [000$]	Other reliability, safety and environment [000$]	Total reliability, safety and environment [000$]
2,018	0	0	1,700	1,700
2,017	1,310	0	823	2,133
2,016	1,678	0	251	1,929
2,015	1,541	0	402	1,943
2,014	2,337	0	213	2,550
2,013	725	0	1,261	1,986

Graphic 61

Conclusions

• Seems the total available to Reliability, safety and environment is about 2 million NZD.

---

A) Quality of Supply

Table 62 divide the Total Reliability, Safety and Environment into 2 components.

{.tabset}

Table 62

Quality of Supply

Year	Quality of supply less capital contributions [000$]	Capital contributions funding asset relocations [000$]	Quality of supply expenditure [000$]
2,018	0	0	0
2,017	1,278	32	1,310
2,016	1,678	0	1,678
2,015	1,541	0	1,541
2,014	2,328	9	2,337
2,013	725	0	725

Graphic 62

Conclusions

• From 2014 to 2017 the efforts on The Reliability, Safe and Environment was in Quality of Supply, but suddenly in 2018, they change the focus to Other Reliability, Safety and Environment (which is unknown due to lack of information). For this reason, in 2018 there is no expenditure in Quality supply.
• I think Aurora Energy does not have a large provision to this item and need to choose which one to “attack”.

---

B) Legislative and Regulatory

Conclusions:

• I did not find any data on this item, the fields are in blank or have zeros.

---

C) Other reliability, safety and environment

Table 63 divide the Other Reliability, Safety and Environment into two components.

Table 63

Other reliability, safety and environment

Year	Other reliability, safety and environment less capital contributions [000$]	Capital contributions funding other reliability, safety and environment [000$]	Other reliability, safety and environment expenditure [000$]
2,018	1,700	0	1,700
2,017	806	17	823
2,016	246	5	251
2,015	402	0	402
2,014	213	0	213
2,013	1,261	0	1,261

Graphic 63

Conclusions

• Although this item aims to detail, there is only one new information about the Capital Contribution of the Consumers.

---

2.7.2.2. Consumer Connections

Consumer Connections is a subitem of Network Asset.

Table 64 shows the expenditure to connect the new consumer to the grid and the capital contributions funding.

Table 64

Consumer connection expenditure

Year	Capital contributions funding consumer connection expenditure [000$]	Consumer connection less capital contributions [000$]	Consumer connection expenditure [000$]
2,018	4,483	4,011	8,494
2,017	2,904	4,622	7,526
2,016	5,059	5,494	10,553
2,015	3,584	6,666	10,250
2,014	2,948	1,775	4,723
2,013	2,765	3,906	6,671

Graphic 64.1

Graphic 64.2

Graphic 64.3

Conclusions

• Aurora Energy has been decreasing the expenditure on the new connection. From 2015 to 2018, the expenditure has diminished by 39.83%.

---

2.7.2.3. System Growth

System Growth is a subitem of Network Asset.

Table 65 shows the expenditure involved in Sub transmission, Zone Substation, Distributions lines, etc.

Table 65

System Growth

	Distribution
Year	OH [000$]	UG [000$]	Substations and Transformers [000$]	Switchgear [000$]	Subtransmission [000$]	Other Network Assets [000$]	Zone substations [000$]	Capital contributions funding system growth [000$]	System Growth Expenditure [000$]
2,018	41	391	150	352	224	5,180	5	0	6,343
2,017	82	106	0	3	4	52	23	27	270
2,016	406	910	168	232	495	174	6,595	22	8,980
2,015	125	43	34	39	0	3	6,654	17	6,898
2,014	91	104	71	34	0	26	24	64	350
2,013	152	457	204	163	54	23	1,099	19	2,152

Graphic 65.1

Graphic 65.2

Graphic 65.3

Conclusions

• In 2015 and 2016 have atypical expenditures amounts in Zone Substations, whereas in 2018 Other Network Assets has reached 81.66% of the System Growth Expenditure.

---

2.7.2.4. Asset Replacement and Renewal

Asset Replacement and Renewal is also a subitem of Network Asset.

Table 66 shows the expenditure involved in Capital Contribution, Zone Substation, Distributions lines, etc.

Table 66

Asset Replacement and Renewal

	Distribution
Year	OH [000$]	UG [000$]	Substations and Transformers [000$]	Switchgear [000$]	Subtransmission [000$]	Other network assets [000$]	Zone substations [000$]	Capital contributions funding asset replacement and renewal [000$]	Asset replacement and renewal expenditure [000$]
2,018	32,020	1,204	2,896	2,896	3,872	1,550	7,470	0	50,767
2,017	5,109	883	398	398	2,622	7,405	855	26	18,128
2,016	3,806	341	557	557	114	163	383	26	5,511
2,015	4,222	311	616	616	628	45	1,486	0	7,501
2,014	1,583	468	299	299	2,069	125	2,865	615	7,761
2,013	2,391	958	281	281	542	108	1,830	0	6,374

Graphic 66.1

Graphic 66.2

Conclusions

• In 2018 the focus of Asset Replacement and Renewal was in Distribution and LV lines, the total expenditure was about 32 million NZD.

---

2.7.2.5. Asset Relocations

Consumer Connections is a subitem of Network Asset.

The Equation (34) shows the subcomponents of Asset Relocation Expenditure.

\[\begin{equation} \small ASSETS_{relocation,expenditure} = RELOC_{capital contribution} + ASSETS_{relocation,expenditure,less,cc} \end{equation}\]

\(\small \begin{array}{l l} ASSETS_{relocation,expenditure}: & \text{Asset relocations expenditure [000\$]} \\ RELOC_{capital contribution}: & \text{Capital contributions funding asset relocations [000\$]} \\ ASSETS_{relocation,expenditure,less,cc}: & \text{Asset relocations less capital contributions [000\$]} \\ \end{array}\)

Table 67.1 shows 2 components of Asset Relocations:

• Asset relocations less capital contributions;
• Capital contributions funding asset relocations.

Table 67.1

Asset relocations expenditure

Year	Asset relocations less capital contributions [000$]	Capital contributions funding asset relocations [000$]	Asset relocations expenditure [000$]
2,018	769	268	1,037
2,017	1,588	493	2,081
2,016	1,065	1,002	2,067
2,015	1,737	833	2,570
2,014	84	451	535
2,013	200	259	459

Graphic 67.1

Graphic 67.2

Graphic 67.3

Conclusions

• The Asset Relocations Expenditure has a decreasing trend.

---

2.7.3. Non-network Asset

The Equation (35) shows the subcomponents of Non-network Asset.

\[\begin{equation} \small ASSETS_{non-network} = ATYPICAL_{expenditure} + ROUTINE_{expenditure} \end{equation}\]

\(\small \begin{array}{l l} ASSETS_{non-network}: & \text{Expenditure on Non-network Asset [000\$]} \\ ATYPICAL_{expenditure}: & \text{Atypical Expenditure [000\$]} \\ ROUTINE_{expenditure}: & \text{Routine Expenditure [000\$]} \\ \end{array}\)

Table 68 shows the Non-network Asset Expenditure divided into two components:

• Atypical Expenditure;
• Routine Expenditure.

Table 68.1

Non-network Assets

Year	Atypical expenditure [000$]	Routine expenditure [000$]	Non-network assets expenditure [000$]
2,018	956	0	956
2,017	0	0	0
2,016	0	0	0
2,015	0	0	0
2,014	0	0	0
2,013	0	0	0

Table 68.2

Atypical expenditure in Non-Network Assets

Description	Expenditure [000$]
Office Furniture - Desks, Screens, Chairs, Cabinets	301
Sundry Computer Equipment - Laptops and Associated Equipment	138
Halsey St, Upgrade Power and Generator	70
Power Factory Upgrade - IT Asset Management Software	155
All other projects or programmes - atypical expenditure	292
Atypical expenditure	956

Conclusions

• First year identified with this kind of expenditure. The Atypical Expenditure was Equipment to Office, Computers, IT Software, etc.

---

2.7.4. Capital Contribution

Table 69 sum up the Capital Contribution from all items of CAPEX. In the list below, you can see the chapter where you can find it.

• Consumer Connection
• Asset Replacement and Renewal
• System Growth
• Asset relocations
• Quality of supply
• Legislative and Regulatory
• Other Reliability, Safety and Environment

Table 69

Capital Contribution

Year	Consumer connection [000$]	Asset Replacement and Renewal [000$]	System Growth [000$]	Asset relocations [000$]	Quality of supply [000$]	Legislative and Regulatory [000$]	Other Reliability, Safety and Environment [000$]	Capital Contribution [000$]
2,018	4,483	0	0	268	0	0	0	4,751
2,017	2,904	26	27	493	32	0	17	3,499
2,016	5,059	26	22	1,002	0	0	5	6,114
2,015	3,584	0	17	833	0	0	0	4,434
2,014	2,948	615	64	451	9	0	0	4,087
2,013	2,765	0	19	259	0	0	0	3,043

Graphic 69.1

Graphic 69.2

Conclusions

Most of the Capital Contribution was in Consumer Connection, it means, to connect a new consumer or to upgrade an existing installation. In 2018 the share of new connection reached 94.36% over the Capital Contribution.

---

2.8. Revenue

This subchapter divides the Lines Charges into load-group, and whether standard or non-standard (as a classification by NZCC).

2.8.1. Lines Charges

Table 70 shows the Target and the Actual amount of Energy delivered to the ICPs.

Table 70

Comparison - Actual vs Target

	Revenues
Year	Target [000$]	Actual [000$]	Rate [%]
2,018	93,778	95,653	102
2,017	91,020	92,640	102
2,016	87,711	91,267	104
2,015	89,870	90,830	101
2,014	84,580	82,403	97
2,013	83,982	84,229	100

Graphic 70

Conclusions

• Along 6 years, only one time Aurora did not reach the target.

---

2.8.1.1. Standard and Non-standard Consumers

The Equation (36) shows the components of Total Energy Delivered.

\[\begin{equation} \small E_{delivered,ICP} = E_{standard} + E_{non-standard} \end{equation}\]

\(\small \begin{array}{l l} E_{delivered,ICP}: & \text{Total energy delivered to ICPs [MWh/year]} \\ E_{standard}: & \text{Energy delivered to Standard Consumer [MWh/year]} \\ E_{non-standard}: & \text{Energy delivered to Non-standard Consumer [MWh/year]} \\ \end{array}\)

Table 71 shows the Total Energy Delivered share between Standard and Non-standard Consumers.

Table 71

Energy delivered to ICPs by Demand Group

Year	Network	Standard [MWh/year]	Non-standard [MWh/year]	Total Energy Delivered [MWh/year]
2,018	All	1,297,730	10,563	1,308,293
2,017	All	1,272,557	11,613	1,284,170
2,016	All	1,291,261	12,188	1,303,450
2,015	All	1,242,064	6,070	1,248,134
2,014	All	1,250,257	0	1,250,257
2,013	All	1,248,959	0	1,248,959
Central Otago
2,018	CentralOtago	497,928	10,563	508,491
2,017	CentralOtago	475,671	11,613	487,284
2,016	CentralOtago	467,872	12,188	480,060
2,015	CentralOtago	434,981	6,070	441,050
2,014	CentralOtago	433,346	0	433,346
2,013	CentralOtago	414,803	0	414,803
Dunedin
2,018	Dunedin	799,089	0	799,089
2,017	Dunedin	796,206	0	796,206
2,016	Dunedin	822,726	0	822,726
2,015	Dunedin	799,308	0	799,308
2,014	Dunedin	816,336	0	816,336
2,013	Dunedin	841,545	0	841,545

Graphic 71

Conclusions

• Aurora Energy does not have various non-standard consumers as shown in Table 70.1. In 2018 the share in Total Energy Delivered to this load-group was only 0.81%.

---

2.8.1.2. Average Number of ICPs

Table 72 shows each Load Group and the number of consumer from 2013 to 2018.

Table 72

Graphic 72.1

Graphic 72.2

Conclusions:

• Aside from the typos observed in Graphic 72.1, it is possible to see a positive trend in Central Otago and a slight positive trend in Dunedin. Aggregating these trends result in a global growth of 6.32% accumulated in 6 years.

---

2.8.2. Comparison Regionals

Based on the informations gathered in chapters 2.8.1. Table 73 compile a sum up.

Table 73

Consumer, ICP number, and Ratio

	Central Otago			Dunedin			Total
Year	[MWh]	[ICP]	[MWh/ICP]	[MWh]	[ICP]	[MWh/ICP]	[MWh]	[ICP]	[MWh/ICP]
2,018	508,490.5	33,417.15	15.22	799,089.5	55,036.49	14.52	1,308,293	88,569.10	14.77
2,017	487,284.3	32,291.21	15.09	796,206.1	54,686.93	14.56	1,284,170	87,083.04	14.75
2,016	480,060.2	31,352.00	15.31	822,726.1	54,495.00	15.10	1,303,450	85,947.00	15.17
2,015	441,050.2	30,647.00	14.39	799,308.4	54,277.00	14.73	1,248,134	84,998.00	14.68
2,014	433,345.5	29,907.00	14.49	816,336.4	53,947.00	15.13	1,250,257	83,945.00	14.89
2,013	414,803.0	29,354.00	14.13	841,544.9	53,831.00	15.63	1,248,959	83,305.00	14.99

Conclusions:

• Although, the global average of consumptions by ICP is increasing over the years, in Dunedin Regional this ratio was slightly decreasing, and in an inverse way, the Central Otago Regional was increasing.

---

3. Aurora Energy Analysis

Due to the type of analysis involving many Graphics, I will use the tool called Flex Dash Board in a separated platform, which can be accessed by the link below.

Aurora Energy Dashboard

This tool has several features that allow the data interpretation easier to understand and also allow the analyst to record each step of the data transformation.

4. Benchmarking

On the Aurora Energy Dashboard (same of the Chapter 3), there is a complete and commented section to the Clusterization.

4.1. Clusterization

The aim of the clusterization is to find groups in a population with same similarity, but underlying this main objective resides many details, which will be discussed in the next subchapters. The methodology applied in this chapter is based on the book Kassambara (2017).

4.2. Data Preparation

In this step I will choose the variables, scale method and the standardization method.

4.2.1. Variables and Observations

The observations of this clusterization is the EDB companies, and the variables selected are:

1. Number of ICPs
2. Energy Delivered
3. Lines Charge
4. Network Length
5. Losses
6. SAIDI
7. SAIFI
8. Interrupptions
9. Closing RAB
10. OPEX
11. CAPEX

All the calculation will be based on the 2018 values.

4.2.2. Data Standardization

This step is necessary to make features comparable because many of the variable are in different scales. The Equation (37) shows the method adopetd to perform the standardization.

\[\begin{equation} \small obs_{standard} = \frac{(x_{i} - centre_{i})}{scale(x)} \end{equation}\]

\(\small \begin{array}{l l} obs_{standard}: & \text{standardizated observation} \\ x_{i}: & \text{observation i} \\ y_{i}: & \text{mean of all x observations}\\ scale(x): & \text{standard deviation of the x observation}\\ \end{array}\)

The output of this equation is a variable with mean zero and standard deviation one.

## **Results for the Principal Component Analysis (PCA)**
## The analysis was performed on 29 individuals, described by 11 variables
## *The results are available in the following objects:
## 
##    name               description                          
## 1  "$eig"             "eigenvalues"                        
## 2  "$var"             "results for the variables"          
## 3  "$var$coord"       "coord. for the variables"           
## 4  "$var$cor"         "correlations variables - dimensions"
## 5  "$var$cos2"        "cos2 for the variables"             
## 6  "$var$contrib"     "contributions of the variables"     
## 7  "$ind"             "results for the individuals"        
## 8  "$ind$coord"       "coord. for the individuals"         
## 9  "$ind$cos2"        "cos2 for the individuals"           
## 10 "$ind$contrib"     "contributions of the individuals"   
## 11 "$call"            "summary statistics"                 
## 12 "$call$centre"     "mean of the variables"              
## 13 "$call$ecart.type" "standard error of the variables"    
## 14 "$call$row.w"      "weights for the individuals"        
## 15 "$call$col.w"      "weights for the variables"

4.2.3. Observation Distances

I choose the Manhattan method to calculate the distance between observation because this method is less sensitive of unusual values and should give more robust results. The Equation (38) shows the Manhattan method.

\[\begin{equation} \small d_{man}(x,y) = \sum_{i=1}^n|(x_{i} - y_{i})| \end{equation}\]

\(\small \begin{array}{l l} d_{man}: & \text{Distance between x and y} \\ x_{i}: & \text{} \\ y_{i}: & \text{} \\ \end{array}\)

The Graphic X shows the output of the VAT (Visual Assessment of Cluster Tendency) method developed by Bezdek and Hathaway (2012).

Graphic X

The interpretation of the Graphic is:

• Red: high similarity
• Blue: Low similarity

EDB belonging to the same cluster (group) are shown in consecutive order.

Other approach to assess the Clustering Tendency is using the Hopkins statistic. The Equation () shows the Hopkins Statisc.

\[\begin{equation} \small H = \frac{\sum_{i=1}^n{y_{i}}}{\sum_{i=1}^n{x_{i}}+\sum_{i=1}^n{y_{i}}} \end{equation}\]

\(\small \begin{array}{l l} d_{man}: & \text{Distance between x and y} \\ x_{i}: & \text{a} \\ y_{i}: & \text{a} \\ \end{array}\)

The null and the alternative hypotheses are defined below:

• Null hypothesis: the dataset is uniformily distributed;
• Alternative hypothesis: the dataset is not uniformily distributed,

If H is close 0.5 means that there are not clusters.

The results of this statistic in the NZ Electricity Market is 0.25, which means there are clusters in this dataset.

4.3. Clustering Algorithm

The are several Cluster algorithms in the academic literature, however as an example of cluster application I will adopt the K-medoids method and I will use the PAM (Kaufamn & Rouseeeuw, 1990) algorithm to solve it.

4.3.1. PAM Algorithm

This method is more stable than the K-means because the centroid of each clusters is an observation instead of a mean of the cluster. Due to this modification the K-medoids is less sensitive to outliers than K-means.

4.3.2. Opitimized Number of Cluster

Unfortunalety, the K-menoids needs as input the number of clusters, however there is a solution calculating the silhouette, as shown in the Graphic X.

Graphic X

The Silhouette is an iteractivy application of PAM algorithm varying the number of cluster from 1 to 10 and then plotting. The objective is to find the curve knee, where the optimized solution will be find. So, from the Graphic X, the optimized number of cluster is 2.

Besides this straighforward solution, I will apply a statistical method to ensure the number of cluster called Gap Statistic (R. Tibshirani, G. Walther, and T. Hastie).

## Warning in pf(beale, pp, df2): NaNs produzidos

## *** : The Hubert index is a graphical method of determining the number of clusters.
##                 In the plot of Hubert index, we seek a significant knee that corresponds to a 
##                 significant increase of the value of the measure i.e the significant peak in Hubert
##                 index second differences plot. 
## 

## *** : The D index is a graphical method of determining the number of clusters. 
##                 In the plot of D index, we seek a significant knee (the significant peak in Dindex
##                 second differences plot) that corresponds to a significant increase of the value of
##                 the measure. 
##  
## ******************************************************************* 
## * Among all indices:                                                
## * 1 proposed 2 as the best number of clusters 
## * 11 proposed 3 as the best number of clusters 
## * 3 proposed 5 as the best number of clusters 
## * 1 proposed 7 as the best number of clusters 
## * 4 proposed 9 as the best number of clusters 
## * 3 proposed 10 as the best number of clusters 
## 
##                    ***** Conclusion *****                            
##  
## * According to the majority rule, the best number of clusters is  3 
##  
##  
## *******************************************************************

## Among all indices: 
## ===================
## * 2 proposed  0 as the best number of clusters
## * 1 proposed  1 as the best number of clusters
## * 1 proposed  2 as the best number of clusters
## * 11 proposed  3 as the best number of clusters
## * 3 proposed  5 as the best number of clusters
## * 1 proposed  7 as the best number of clusters
## * 4 proposed  9 as the best number of clusters
## * 3 proposed  10 as the best number of clusters
## 
## Conclusion
## =========================
## * According to the majority rule, the best number of clusters is  3 .

4.3.3. PAM Clustering Application

4.3.4. Agglomerative

4.3.4. Dendrogram

4.3.4. Evaluating the Tree

## [1] 0.674461

## [1] 0.8979558

4.3.5. Comparison

## 
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## The following object is masked from 'package:stats':
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4.6.

## Joining, by = c("EDB", "Network")

5. Results

1. Table 1 - Consumers: em 6 anos Central Otago cresceu cerca de 3.000 consumidores (o que representa 10%) e Dunedin 1.000, acumulando mais de 4.000 em toda área de concessão.

2. Table 2 - Comprimento de rede: A maior parte da rende está na regional de Central Otago, embora Dunedin tenha crescido muito no ano de 2018.

3. Table 3 - Rede aérea: Havia uma predominancia de Central Otago até 2017, mas com o crescimento da rede em Dunedin esse percentual agora é praticamente igual.

4. Table 4 - Cabos subterrâneos: 2/3 estão em Central Otago, cujo crescimento é igual em ambas regionais (Central Otago é de 39% e Dunedin é de 38.7%).

5. Em 2016 aconteceu alguma coisa na estrutura tarifária. Analisando os Annual Comliance de (conferir os mais antigos) 2014 até 2015 os valores de receita (Notional revenues) estava bem parecido, em 2016 houve uma diminuição muito grande. Comparando com os dados da Planilha Database é possível notar um aumento dos non-standard prices. Houve aí uma ruptura do processo daquela época.

6. Conclusions

(Chang et al. 2015)

7. References

7.1. Session Info

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## [34] highr_0.7            htmlwidgets_1.3      rlang_0.3.0         
## [37] rstudioapi_0.8       shiny_1.1.0          bindr_0.1.1         
## [40] jsonlite_1.5         crosstalk_1.0.0      mclust_5.4.1        
## [43] magrittr_1.5         modeltools_0.2-22    leaps_3.0           
## [46] Rcpp_0.12.19         munsell_0.5.0        viridis_0.5.1       
## [49] scatterplot3d_0.3-41 stringi_1.2.4        whisker_0.3-2       
## [52] yaml_2.2.0           MASS_7.3-51          flexmix_2.3-14      
## [55] plyr_1.8.4           promises_1.0.1       crayon_1.3.4        
## [58] miniUI_0.1.1.1       lattice_0.20-35      hms_0.4.2           
## [61] knitr_1.20           pillar_1.3.0         ggpubr_0.1.8        
## [64] fpc_2.1-11.1         reshape2_1.4.3       stats4_3.5.1        
## [67] glue_1.3.0           evaluate_0.12        httpuv_1.4.5        
## [70] cellranger_1.1.0     gtable_0.2.0         purrr_0.2.5         
## [73] kernlab_0.9-27       reshape_0.8.8        assertthat_0.2.0    
## [76] xfun_0.4             mime_0.6             xtable_1.8-3        
## [79] later_0.7.5          class_7.3-14         viridisLite_0.3.0   
## [82] tibble_1.4.2

Chang, W., J. Cheng, JJ. Allaire, Y. Xie, and J. McPherson. 2015. “Shiny: Web Application Framework for R. R Package Version 0.12.1.” Computer Program. http://CRAN.R-project.org/package=shiny.

Commission, New Zealand Commerce. 2018a. “Electricity Distributors Information Disclosures.” Excel. New Zealand Commerce Commission. https://comcom.govt.nz/regulated-industries/electricity-lines/electricity-distributor-performance-and-data/information-disclosed-by-electricity-distributors.

———. 2018b. “Electricity Distributors Information Disclosures.” Dashboard. New Zealand Commerce Commission. public.tableau.com/profile/commerce.commission.regulation#!/vizhome/Performanceaccessibilitytool-NewZealandelectricitydistributors/Highlevelratios.

Energy, Aurora. 2018. “2018 Aurora Energy Annual Report.” Report. Aurora Energy. www.auroraenergy.co.nz/disclosures/annual-reports/.

Grolemund, G. 2018. Data Science with R. O’Reilly Media. http://garrettgman.github.io/tidying.

Ihaka, R., and R. Gentleman. 1996. “R: A Language for Data Analysis and Graphics.” Journal of Computational and Graphical Statistics. American Statistical Association. https://www.stat.auckland.ac.nz/~ihaka/downloads/R-paper.pdf.

Kassambara, A. 2017. Practical Guide to Cluster Analysis in R. sthda.com. http://www.sthda.com.

NZCC. 2018. “Electricity Distribution Services Input Methodologies Determination 2012.” Report. New Zealand Commerce Commission. https://comcom.govt.nz/regulated-industries/input-methodologies/electricity-distribution-ims.

R Core Team. 2018. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

 

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A work by AH Uyekita

anderson.uyekita[at]gmail.com