1. Hydro One Networks Stakeholder Session Principles for Defining and Allocating Cost to Density-Based Sub-Classes May 25, John Todd
Pleased to be here
HONI has asked me to prepare a report on the principles for defining and allocating costs to density-based customer classes which is to be included in its evidence to be filed in its upcoming distribution rate application.
I am presenting my initial thinking in order to get your feedback to assist in preparing this evidence.
There is time for comments at the end of this session. Please limit questions to points of clarification during the presentation.
Also, staying for lunch if you want to provide further feedback
Or send comments by

2. Elenchus Research Associates
Outline
Principles and Precedents
Examples of density-based classes
Customer class definition principles
General ratemaking principles
Defining Density-Based Classes
Status Quo
Alternative: “Granular” density-based classes
Implications
Cost Allocation Options
Alternative: “Granular” density-based costs
Conclusions
5/25/2009
Elenchus Research Associates

3. Examples of Density-Based Classes
Canada: CRTC, High Cost of Serving Areas
Low-density, remote communities
Competitive discipline ineffective
Price regulation necessary, subsidization justified
Manitoba: Manitoba Hydro (1980’s)
Various usage and regional rates
California: CPUC, Urban/Rural Zones (1950’s)
“The Staff’s approach gives consideration to the number of customers, the location of the customers, the number of customers per mile of distribution pole line, area growth pattern, and the history of rates.”
(San Diego Gas & Electric, Decision No , Oct 1958)
5/25/2009
Elenchus Research Associates

4. Customer Classification Principles
Standard Ratemaking Texts
Bonbright, Kahn, Phillips are silent on principles and methods for identifying customer classes.
Goodman: “As one commission has noted, ideally each customer class … should be based on “distinct usage or cost patterns, not on type of building or nature of business.” (p. 1017)
Density as a Source of Economies of Scale:
The impact of the “level of traffic, i.e., density” on capacity costs per unit of costs is recognized as a source of economies of scale. (Goodman, p. 417; Kahn, p. 125).
Goodman quote re: Boise Water Corp
Density as a Source of Economies of Scale:
- Who should receive the benefits of the economies of scale
Only customers in dense areas with scale economies, or
All customers (local scale economies are a system benefit)
Context was telecom
5/25/2009
Elenchus Research Associates

5. Relevant Bonbright Principles
Bonbright et al (1988): 10 Attributes of a Sound Rate Structure. Most relevant are:
4. Static efficiency of the rate classes and rate blocks ..
6. Fairness of the specific rates in the apportionment of total costs of service …
7. Avoidance of undue discrimination …
OEB identified three rate design principle in Rate Design Review:
Full Cost Recovery Principle
Fairness Principle
Efficiency Principle
“4. Static efficiency of the rate classes and rate blocks in discouraging wasteful use of service while promoting all justified types and amounts of use.”
6. Fairness of the specific rates in the apportionment of total costs of service among different ratepayers so as to avoid arbitrariness and capriciousness and to attain equity in three dimensions:
(1) horizontal (i.e., equals treated equally)
(2) vertical (i.e., unequals treated unequally);
(3) anonymous (i.e., no ratepayer’s demands can be diverted away uneconomically from an incumbent by a potential entrant.
7. Avoidance of undue discrimination in rate relationships so as to be, if possible, compensatory (i.e., subsidy free with no intercustomer burdens).
OEB: See Staff Discusison Paper (EB ) June 6, 2008 revised version, section 3.
The Board identified three rate design principles for the purposes of this process. These principles encompass all of the “Bonbright attributes of a sound rate structure5” identified in the March 2007 Staff Discussion Paper:
1. full cost recovery;
2. fairness; and
3. efficiency.
5/25/2009
Elenchus Research Associates

6. Conclusions on Principles (1)
The literature and precedents provide no guidance regarding the principles that should be used in addressing the issue of establishing density-based rates.
The central question appears to be: Are urban and rural customers “equals” or “unequals”?
Based on usage, they are equals
Based on cost, they are unequals
Should cost differences due to density of customers (economies of scale/intensity of use) be reflected in rates?
Accepted approach in practice to defining is generally to identify groups of customers with different usage that requires different categories of facilities (e.g., Tx connected, Primary only, Primary and Secondary) or different load profiles (residential vs. commercial/GS).
But reason for differentiating among usage patterns is because costs are different (cost causality)
With the exception of OEB/HONI, regulators generally:
- apply postage stamp rates to all residential customers
- do not differentiate on the basis of location (which is the determinant of density
- e.g., location relative to Tx is not the basis of rate differentials
- Why is there a difference for distance and density-related costs?
5/25/2009
Elenchus Research Associates

7. Conclusions on Principles (2)
The rationales for density based rates include:
Competitive issues:
In telecom competitors can “cherry-pick” service areas
Electricity customers served by LDCs with different mix of urban/rural may have their own competitive concerns
Rate comparison issues:
Benchmarking may need to consider cost drivers such as density where LDCs have significantly different mix of customer densities
Neighbouring customers served by different LDCs compare rates which may reflect different customer mix (and intra-class cross-subsidies)
Fairness Principle:
“Unequals treated unequally”
Are these rationales supported by OEB in the case of density-based rates?
5/25/2009
Elenchus Research Associates

8. Defining Density-based Classes (1)
Option #1: Areas based on average density
Historic HONI approach
Urban Density Zone has 3,000 or more customers
Based on average LDC size at the time (with 312 LDCs)
Should this be updated to new average size? Why?
Line density of 60 residential customers/km or more
There is no apparent cost basis for this threshold
Is there a more meaningful “break point”
“Urban areas” generally extended from a dense core to a “logical” boundary that met minimum threshold
Presumably some UR areas include a mix of urban and rural customers that is consistent with the urban definition
Problem: Does not ensure “equal treatment of equals”
5/25/2009
Elenchus Research Associates

9. Defining Density-based Classes (2)
Option #2: Classify customers based on “granular” density
Principle: Ensure “equals treated equally” where equals are defined as customers requiring similar distribution infrastructure
Use small geographic areas as basis for determining density
Classify areas/customers based on the “granular” density
Result would be a more intuitive and consistent urban:rural split
This approach would focus on small concentration of customers (perhaps at the transformer level)
This approach may ignore the distance to the backbone of grid (which may be important to the cost of serving specific customers)
Conceptually, an alternative “granular” approach would be to define areas based on the network configuration (may be inconsistent with postage stamp principle)
e.g. use postal code as geographic areas as the basis for density determination
5/25/2009
Elenchus Research Associates

10. Google Maps: Blind River
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Elenchus Research Associates

11. Implications of Redefining Classes
Rural or Remote Rate Protection (RRRP)
The customers benefiting and magnitude of subsidy may change
Total value of the RRRP may change
Service Quality indicators (SQI)
Different SQIs apply in urban and rural areas
SQI standards may have to be reviewed if composition of urban and rural regions is changed (e.g., response time; reliability; SAIDI; SAIFI)
Significant effort (costs) will be required
Feasibility Test (DCF Model)
DCF uses estimated construction cost for actual projects but standardized values for future costs (e.g., maintenance, customer service, etc.)
Redefined classes may require changes to DCF model to reflect differences in future costs
4/25/2018
5/25/2009
Elenchus Research Associates
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12. Cost Allocation Options
Option #1: Areas based on average density
Current CA Methodology using weighting factors (presented at the previous stakeholder session)
Option #2: Classify customers based on granular density
Use plant records for distribution plant serving groups of customers (directly allocate to the sub-classes)
Use regression analysis to estimate cost of wires/poles/ transformers to serve different customer classes
Sample actual capital and O&M costs incurred to serve customers in “typical” urban and rural areas
Use engineering analysis to determine cost differentials
Option 2.1: required data are not currently available. May be very costly to develop.
Option 2.3: plant records for O&M, inflation adjusted; track O&M costs for a period of time
Choice of method a matter of cost/feasibility
Implementation method:
Identify costs (USA) allocated to residential only (i.e., not GS or LV) – these are not common costs and need to be allocated to Urban and Rural using appropriate allocators such as customers/km for poles and wire; customers/DS for DS costs; etc.
Allocate losses based on average distance to load on LV facilities
Allocate brushing costs (storm damage) to rural only or as appropriate based on sampling of historical costs incurred
5/25/2009
Elenchus Research Associates

13. The Significance of Cost Factors
There are many factors that affect the cost of serving specific groups of customers:
Density of customers using a feeder
Overhead vs. underground
Rock/soil conditions
Congestion in urban centres
Factors affecting the urban/rural differential:
Rural higher: Storm damage; brushing: travel time; DS under-utilization; etc.
Urban higher: Congestion; undergrounding; SCADA; etc.
Are there best practices studies that might indicate cost of best practices under various conditions?
Key factors based on interviews of Hydro One engineering (?) staff:
Higher costs in rural (and remote) areas
Storm damage is primarily in rural areas – HONI plant is less protected by natural environment
Brushing is done only in rural areas (annual cost about $28 million)
Travel time is 2-3 times higher for each job in rural areas
Distribution Stations (DS) are standardized (more economic than non-standard equipment)
Area a DS can serve efficiently is limited and number of customers is fixed (minimum 10 kVA transformer)
In urban areas, customer density is sufficient to fully utilize DS capacity (allowing for growth)
In rural, density can be too low for optimal utilization; hence, significant excess capacity and cost/customer is higher
In rural areas number of poles/customer and km of line can be 5-10 times greater: hence, higher cost per customer
Higher costs in urban areas
Some urban areas have high costs due to congestion (usually only dense commercial areas – downtown Toronto, etc.)
Underground facilities are more expensive – generally only in urban areas
5/25/2009
Elenchus Research Associates

14. Conclusions
The current HONI approach to defining density-based classes, allocating costs and setting rates is pragmatic rather than principled.
A more granular approach to identifying urban and rural customers would improve fairness, would have little impact on efficiency, and might compromise rate stability & simplicity.
Adopting a more rigorous cost-based approach to allocating density-based cost will be challenging.
Central question is probably: are the fairness benefits worth the costs:
There are bound to be winners and losers
If impact of change is modest, may not be worth the effort
If impact of change is significant, may need mitigation and end up in the same place
if urban and rural customers are not equal (justify different rates) how big a difference is reasonable
i.e., would rates that reflect the full cost difference be fair and equitable (RRRP suggests NO)
A policy decision that rural rates and urban rates should differ so as to reflect the cost differential would imply the need to apply the policy on a provincial basis
Province-wide adoption would result in rates that are more comparable across LDCs.
4/25/2018
5/25/2009
Elenchus Research Associates
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15. Questions
Are there any other principles that should be addressed in the ERA Report?
Are there other issues that are relevant to the OEB’s consideration of the matter:
Are density-based rates equitable?
What is the appropriate way to define density- based rate classes (e.g., UR; R1; R2)?
What is the appropriate way to allocate costs to density-based rate classes?
If the cost (rate) differential increases, should the urban-to-rural cross- subsidy (RRRP) be increased?
Province-wide adoption would result in rates that are more comparable across LDCs.
Also is the basis of cost differences important
Do customers require different distribution facilities that drive cost differences?
Are cost differences the result intensity of use (i.e., density and resulting scale economies)?
4/25/2018
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