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Purpose
 overview of the form and use of the AER’s
augex tool
 Not
 Detailed reference material on the underlying spreadsheets
 Defence of the tool’s regulatory role and suitability
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Summary
 Background
 Augex model data requirements
 Overview of workbook – augex modelling tool
 Overview of augmentation algorithm
 Discussion of issues raised
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Background – capex category
Capex driver
Demand driven: customer
connection
Capex activity
Replacement
Additional assets
replacement and development of assets to facilitate the
connection of customers
Augex tool
Demand driven:
augmentation
replacement and development of network assets to
increase the capacity of the network
Repex tool
Non-demand driven
replacement of aged assets
with modern equivalents
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installation of new assets
Background - key aims
 Regulatory tool NOT planning/management tool
 Should account for main driver at aggregate level

but not concerned with excessive detail
 Allow intra- and inter-company comparisons
 Targeting of matters for detailed review
 Development of benchmarks
 But not intended to determine specific network
constraints and solutions
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Overview
 Similar in form
to repex tool
 Similar to tools
used by ESV
and NSPs
Asset state
• network utilisation
and capacity
• growth in peak
demand
Outputs
• forecast capacity
• forecast costs
• forecast
utilisation
Planning
parameters
• utilisation
thresholds
• augmentation costs
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Overview
 Tool is spreadsheet based - uses VBA functions
 Does not rely upon proprietary – or “black box” –
algorithms
 Uses probability model – to apply utilisation threshold
 relatively simple to independently verify
 Asset utilisation = peak loading / normal rating
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Anticipated application
Augex tool assessment
1 - Base-case
2 - Calibration
3 - Comparison
• Prepare individual DNSP
models based upon
DNSP data
• Derive planning
parameters from actual
historical information of
DNSP
• Prepare individual DNSP
calibration models
• Derive benchmarks
parameters based upon
set of DNSPs’ calibrated
planning parameters
• Prepare individual DNSP
benchmark models
inform other elements of the review
for example, targeting matters for more detailed
review, set expenditure allowance
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Network representation - segments
 Multiple network segments used to improve accuracy
 allows for differences between networks
 reduce impact of aggregation e.g. differences in planning
parameters
 Individual segments represent typical planning components
 sub-transmission lines – load type and/or arrangements
 sub-transmission/zone substations – load type and/or transformer number
 distribution feeder – load type
 distribution substations – load type
15 – 30 separate segments
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Network representation - grouping
 Each network segment must be assigned to a group
 allows aggregation for analysis and reporting
Example distribution groups
Sub-transmission lines
CBD distribution feeders
CBD distribution
substations
Sub-transmission
substations
Urban distribution feeders
Urban distribution
substations
Zone substations
Short rural distribution
feeders
Short rural distribution
substations
Long rural distribution
feeders
Long rural distribution
substations
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Segment input data
 For each network segment
1. Asset state data
a.
b.
Utilisation profile – array of the capacity (MVA) of assets at
utilisations (0% to 151% - in 1% increments)
Utilisation annual growth rate – %pa average over study period
2. Planning parameters
a)
b)
c)
Utilisation threshold – mean and standard deviation (assumes
a normal distribution)
Capacity factor – capacity added = capacity factor x capacity
requiring augmentation
Augmentation unit cost - (k$ per MVA of capacity)
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Data – asset status
 Obtain: loading, rating, type and growth data
 Form of data required:
 loadings, ratings, types, should reflect actual data
 individual components: sub-transmission lines and substations, zone
substations, and distribution feeders
 grouping of data for distribution substations (and LV feeders?)
 latest loading and rating data is used to develop utilisation profile input
 other actual data is used to assess changes (calibration)
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Data – asset status
 General comments
 Actual maximum demand should exclude abnormal operating
conditions
 Maximum demand estimate acceptable if not directly measured
 Distribution feeders – trunk model


maximum demand at feeder exit
rating of main trunk section
 Distribution substations
 expect segments to be based upon load type or categories of substation capacity
or substations type
 Demand growth rates – most appropriate that are available for
category
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Data – capex and capacity
 Obtain: historical and future capex and capacity
 Form of data required:
 Capex should be exclusive of corporate overheads
 Unmodelled capex – separately identify augmentation capex that is not
considered to be related to utilisation and peak demand growth
 Assuming there will be an “augmentation” capex category in the
regulatory reporting requirements – overall capex should be
reconcilable to this category
 The type of capacity should reflect rating types defined for asset status
 Capex ideally should be “as commissioned”
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Supporting information
 Explanations of data sources, calculations, assumptions
for tool data inputs
 rationale for segments if defined by NSP
 basis of asset status data - maximum demand, ratings,
growth rates
 derivation of planning parameters
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Possible other supporting information
 Other responses to aid understanding of data
 Inclusions and exclusions in capex

actual development costs, direct project analysis/planning costs,
other costs allocated to the project
 Capex-capacity allocations rules

it is expected that internal systems may not align to AER groups
 Explanation of unmodelled capex

Project/program descriptions, drivers, outcome on capacity
 Comparability with other DNSPs

Differences that may impact augmentation requirements –
utilisation levels, project types and costs
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workbook structure
 Input sheets
 Model initialisation data sheet – “Tables”
 segment data input sheet – “Asset data”
 Output sheets
 Asset category summary sheet – “Utilisation profile summary”
 Augmentation forecast sheet – “aug forecast”
 Chart sheets
 Utilisation profile – “utilisation profile chart”
 Augmentation forecast – “Forecast Ch1” and “Forecast Ch2”
 Internal calculation sheets
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Overview of demo model
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See handbook for more
detailed reference material
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Forecasting – for each segment
Figure 1 augmentation algorithm
utilisation profile and
demand growth
probabilistic model to
account for variations in
the threshold
capacity requiring
augmentation
(probabilistic model)
utilisation
threshold
(similar to asset lives in repex
model)
capacity added
capacity
factor
expenditure
augmentation
unit cost
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VBA function
 Array function
 =aug_calc(utilisation profile index, capacity profile, growth, capacity factor,
utilisation threshold, SD, method, years)
 Inputs
 utilisation profile index – array of utilisation (%) increments
 capacity profile – array of capacity (MVA) matched to utilisation profile index
 growth – average per annum compound growth in peak demand (%)
 capacity factor – as discussed
 utilisation threshold – mean utilisation at augmentation point (%)
 SD – standard deviation of utilisation at augmentation point (%)
 method – augmentation algorithm method (only 1 at this time)
 Years – number of years for forecast
 Outputs
 Array of forecast capacity added by year
 Array of forecast average utilisation by year
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VBA function – worked example
 Assume a network segment is defined in the model
 Where – utilisation threshold
 Mean utilisation threshold = 65%
 SD of threshold = 5%
 Capacity factor – 0.5 (i.e. add 1 MVA for every 2 MVA requiring augmentation)
 Augmentation cost = $1,000 per MVA added
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VBA function – worked example
 VBA function steps through each element of the utilisation profile to
prepare a forecast for the existing capacity at that utilisation level
 That is, the capacity that has survived to that utilisation level
 For each element of capacity in the utilisation profile
 Step 1 – calculate for each forecast year the amount of capacity requiring
augmentation (the probabilistic calculation)
 Step 2 – calculate the amount of capacity to be added (using the capacity
factor)
 Post-function calculation - expenditure forecasts calculated outside of VBA
function as - capacity added x augmentation cost
 For example, assume we still have 100 MVA that is utilised at 60%
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Step 1 – probability calculation
unconditional CRA
CRA, given survived to be utilised at 60%
10.0
CRA (MVA)
8.0
6.0
4.0
2.0
0.0
20
30
40
50
60
70
80
90
100
utilisation (%)
Proportion of capacity requiring augmentation (CRA) at utilisation, u, given the capacity has
survived to be utilised at 60%
=
𝑢𝑛𝑐𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛𝑎𝑙 𝑝𝑟𝑜𝑏𝑎𝑏𝑖𝑙𝑖𝑡𝑦 𝑓𝑜𝑟 𝑎𝑢𝑔𝑚𝑒𝑛𝑡𝑖𝑛𝑔 𝑎𝑡 𝑢𝑡𝑖𝑙𝑖𝑠𝑎𝑡𝑖𝑜𝑛, 𝑢
𝑢𝑛𝑐𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛𝑎𝑙 𝑝𝑟𝑜𝑏𝑎𝑏𝑖𝑙𝑖𝑡𝑦 𝑓𝑜𝑟 𝑎𝑢𝑔𝑚𝑒𝑛𝑡𝑖𝑛𝑔 𝑤ℎ𝑒𝑛 𝑢𝑡𝑖𝑙𝑖𝑠𝑒𝑑 𝑎𝑏𝑜𝑣𝑒 60%
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Step 1 – transform u to year
unaugmented utilisation
75
utilisation (%)
70
65
60
55
50
0
1
2
3 14
CRA (MVA)
12
4
5
7 capacity8 requiring9 augmentation
10
6
forecast year
10
8
6
4
2
0
1
2
3
4
5
6
7
8
9
forecast year
 using peak demand growth for that segment – assume here it is 2% pa.
 transform the x-axis from utilisation to forecast year
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10
Step 2 – capacity added
 For each forecast year
 Using forecast capacity requiring augmentation (CRA)
 Capacity added = CRA x capacity factor
 For example
 in year 1, CAR is 7.7 MVA (utilised at 61.2%)
 Capacity added = 7.7 MVA x 0.5 = 3.9 MVA
 Utilisation of augmented capacity = demand associated with CAR / (CAR + capacity
added) = (7.7 x 61.2%) / (7.7 +3.9) = 41% utilisation
 Return to step 1 to calculate any later augmentation associated with this
augmented capacity.
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Common issues raised
 Anomaly for high growth rates
 More detail in manual
 HV trunk feeder model
 Use of N-1 rating rather than N for utilisation
 Sensitivity to utilisation threshold
 Including LV segments
 Clarifications on modelling certain circumstances
 Cross feeder ties
 Non-trunk HV feeder augmentations
 Projects with long lead times
 Meshed networks
 Preparing $/MVA for different projects
 Weather correcting utilisation
 Augmenting one segment to address constraints on other segments
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Nuttall Consulting