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Hydro One Networks Stakeholder Session Principles for Defining and Allocating Cost to Density-Based Sub-Classes May 25, 2009 John Todd

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Presentation on theme: "Hydro One Networks Stakeholder Session Principles for Defining and Allocating Cost to Density-Based Sub-Classes May 25, 2009 John Todd"— Presentation transcript:

1 Hydro One Networks Stakeholder Session Principles for Defining and Allocating Cost to Density-Based Sub-Classes May 25, 2009 John Todd

2 5/25/2009Elenchus Research Associates2 Outline 1.Principles and Precedents Examples of density-based classes Customer class definition principles General ratemaking principles 2.Defining Density-Based Classes Status Quo Alternative: Granular density-based classes Implications 3.Cost Allocation Options Status Quo Alternative: Granular density-based costs Implications 4.Conclusions

3 5/25/2009Elenchus Research Associates3 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 (1980s) Various usage and regional rates California: CPUC, Urban/Rural Zones (1950s) The Staffs 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)

4 5/25/2009Elenchus Research Associates4 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).

5 5/25/2009Elenchus Research Associates5 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

6 5/25/2009Elenchus Research Associates6 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?

7 5/25/2009Elenchus Research Associates7 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

8 5/25/2009Elenchus Research Associates8 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

9 5/25/2009Elenchus Research Associates9 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)

10 Google Maps: Blind River 5/25/2009Elenchus Research Associates10

11 1/2/2014Elenchus Research Associates11 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 5/25/200911Elenchus Research Associates

12 5/25/2009Elenchus Research Associates12 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 1.Use plant records for distribution plant serving groups of customers (directly allocate to the sub-classes) 2.Use regression analysis to estimate cost of wires/poles/ transformers to serve different customer classes 3.Sample actual capital and O&M costs incurred to serve customers in typical urban and rural areas 4.Use engineering analysis to determine cost differentials

13 5/25/2009Elenchus Research Associates13 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.

14 1/2/2014Elenchus Research Associates14 Conclusions 1.The current HONI approach to defining density-based classes, allocating costs and setting rates is pragmatic rather than principled. 2.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. 3.Adopting a more rigorous cost-based approach to allocating density-based cost will be challenging. 5/25/200914Elenchus Research Associates

15 DRAFT 1/2/2014Elenchus Research Associates15 Questions 1.Are there any other principles that should be addressed in the ERA Report? 2.Are there other issues that are relevant to the OEBs 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? 3.If the cost (rate) differential increases, should the urban-to-rural cross- subsidy (RRRP) be increased? 5/25/200915Elenchus Research Associates

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