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Regulatory Incentives for Investments in Electric Networks

A presentation to European Copper Institute

Dr. Konstantin Petrov / Rosaria Nunes

May 2009

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Table of Contents

5. Analysis of Regulatory Incentives on Losses - Spain

3. Regulatory Practice - Examples

1. Rationale for Regulation

4. Case Study on Distribution Losses

6. Conclusions

2. Regulatory Models

3

Rationale for Economic Regulation

Scale economies

Scope economies

High initial (sunk) cost

Market failure in relation to externalities (not typical for networks)

One of the regulator’s tasks is to ensure that the transmission and distribution companies do not exploit their market power by operating inefficiently and charging high prices and/or providing inadequate quality of supply.

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Regulatory Model (1)

Rate of return (also known as cost of service regulation or “cost plus”)

Transparent and easy to apply

Risk of over-capitalisation /over-investment

Rate of Return vs. Incentive Regulation

Rt = TCt-1 + ROR * RABt-1

Total cost in the previous year (inflated)

(Allowed) rate of return

Regulatory asset base

5

Regulatory Model (2)

Price / Revenue Cap

Rate of Return vs. Incentive Regulation

Price

time

Benefit to customers(lower prices)

Benefit to firm (higher profit)

Expected improvement(RPI-X)

Actual improvement

Regulatory period

Price

time

Benefit to customers(lower prices)

Benefit to firm (higher profit)

Expected improvement(RPI-X)

Actual improvement

Regulatory period

Pt = Pt-1 *(1 + CPI - X)

Inflation (consumer price index)

Productivity growth rate

Price in the previous year

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Regulatory Model (3)

Building blocks

– Implemented as linked (coupled) cap regulation

– Formalised efficiency analysis of controllable OPEX

– Explicit projection of CAPEX for the upcoming regulatory period

TOTEX approach

– Implemented as unlinked (decoupled) cap or yardstick regulation

– Total expenditure level is regulated irrespective of its composition into CAPEX and

OPEX

– Inclusion of capital cost of historic investments into efficiency assessment modelling

– Usually CAPEX standardisation for benchmarking purposes

Building blocks vs. TOTEX approach

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Regulatory Model (4)

Yardstick Regulation

– Base prices/revenues on an external benchmark, e.g. average cost in

industry

– Transparent, non-intrusive, cost and prices de-linked to a large extent

– Problems with the practical implementation

Quality of Supply

– Cost reduction incentives may lead to quality deterioration

– Quality regulation is necessary (public exposure, minimum quality

standards, incentive schemes)

Other Regulatory Models and Quality of Supply

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Regulatory Model (5)

Trade-offs between OPEX and CAPEX

Regulation should encourage an efficient mix of OPEX and CAPEX

Inadequate regulation may encourage sub-optimal choices in terms of:

– Spending CAPEX when OPEX is the more efficient option

– Reclassify expenditures

– Delaying investments and causing risks on quality of supply

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Regulatory Model (6)

Trade-offs between CAPEX and Quality of Supply

Providing higher quality will generally require higher costs – conflicting

incentives

Regulatory system does not provide guidance on what level of quality to

choose => establishment of explicit quality regulation

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Regulatory Model (7)

Types of losses

– Technical (variable, fixed)

– Commercial

Valuing Losses

– Value of the electricity lost (the cost of generating it)

– Cost of providing the additional transportation capacity

– Cost of the environmental impacts

Regulatory incentive schemes for loss reduction

– Input-based scheme

– Output-based scheme

– Minimum technical standards

Regulation and Network Losses

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Regulatory Practice – Selected Examples

Country Type of

Regulation

Regulatory

Period

Procurement

Network

Losses

Treatment of Network Losses

Germany Revenue cap 5 yearsNetwork

Operators

Included in the allowed revenue

(but not in the current

benchmarking exercise)

UK Revenue cap 5 years SuppliersExplicit loss adjustment term with

an allowed target level

Spain Revenue cap 4 years SuppliersExplicit loss adjustment term with

an allowed target level

NorwayYardstick

regulation

Allowed

revenue reset

annually

Network

Operators

Included in the allowed revenue

(incentives on physical volumes

via the benchmarking)

The

Netherlands

Yardstick

regulation

4 years

/transm.

5 years /distr.

Network

OperatorsIncluded in the allowed revenue

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Case Study on Distribution Losses (1)

Indicative assessment of an investment in energy-efficient distribution

transformers

Economic incremental analysis: compares dynamically incremental

investments costs and incremental benefits defined by monetised loss

savings

Case study aims to broadly approximate the Spanish conditions

– Average load factor of 63% (based on previous studies)

– Loss savings monetised at the simulated wholesale market price

– Discount rate set equal to 5% and 6%

Simplified Cost-Benefit Analysis

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Case Study on Distribution Losses (2)

The Present Value of the additional investment cost equals the Present Value of the reduced losses in 9 to

10 years.

Results 400 kVA transformers (i=5%; i=6%)

-2500

-2000

-1500

-1000

-500

0

500

1000

1 2 3 4 5 6 7 8 9 10 11 12 13Additional investment

Loss savings (i=5%)

Loss savings (i=6%)

NPV (i=5%)

NPV (i=6%)

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Case Study on Distribution Losses (3)

When the difference in transformer prices decreases by 20%, the pay-back period of the

investment decreases to 7 years (instead of 9 to 10 years).

Results 400 kVA transformers (i=6%; ΔI= +/-20%)

-3000

-2500

-2000

-1500

-1000

-500

0

500

1000

1 2 3 4 5 6 7 8 9 10 11 12 13 Additional investment- A

Additional investment- B

Additional investment- C

Loss savings (i=6%)

NPV- A (i=6%)

NPV- B (i=6%)

NPV- C (i=6%)

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Case Study on Distribution Losses (4)

When the electricity prices are 10% higher than the simulated future level in the model

(Scenario C), the pay-back period is 9 years for both the 400 kVA and the 630 kVA

transformer.

Results 400 kVA transformers (i=6%; ΔP= +/-10%)

-2500

-2000

-1500

-1000

-500

0

500

1000

1 2 3 4 5 6 7 8 9 10 11 12 13 Additional investment

Loss savings- A (i=6%)

Loss savings- B (i=6%)

Loss savings- C (i=6%)

NPV- A (i=6%)

NPV- B (i=6%)

NPV- C (i=6%)

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Analysis of Regulatory Incentives on Losses - Spain (1)

Revenue cap with 4 years regulatory period

Formalised in a comprehensive regulatory formula

Include opex, depreciation and return on distribution assets

Does not account explicitly for capex in the regulatory period

Include a quantity term coupled to energy distributed

Include loss adjustment term aiming to encourage loss reduction

Include an incentive scheme for quality of supply

Include efficiency increase factors

Include inflation term

Distribution Price Control

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Where:

Eperdin-1 : actual losses (%) incurred by distribution company i in year n-1 and calculated as

follows:

Eipf : energy measured at the distribution boundary in year n-1 (MWh);

Eig: energy produced by generators connected to the distribution network (MWh) in year n-1;

Eif: energy invoiced to customers connected to the distribution network (MWh) in year n-1;

Eperdiobj,n-1 : loss target for distribution company i in year n-1 defined as % of the energy

entering the distribution system;

PrEperd: price of energy losses (€/MWh).

Loss incentive scheme in Spain

Pin-1 = 0.8*PrEperd *(Eperdi

obj,n-1– Eperdin-1)*(Ei

pf + Eig)

Eperdin-1= [(Ei

pf + Eig) – Ei

f] /(Eipf + Ei

g)

Pin-1 is capped at +/-1% of the allowed revenue

Analysis of Regulatory Incentives on Losses - Spain (2)

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Analysis of Regulatory Incentives on Losses - Spain (3)

Economically feasible investments in loss reduction equipment

Sufficiently long period for benefit retention

Trade-off between incremental CAPEX and loss savings

– Output-based regime should include an appropriate cost

allowance on losses to encourage efficient investments

– Input-based regime should incorporate the expected loss

reduction in the allowed cost

Factors that determine the properties of the loss incentive scheme

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Analysis of Regulatory Incentives on Losses - Spain (4)

Option 1: Implementation of input-based scheme

– It requires specific project-based assessment

– Rolling forward the included assets and keeping the loss targets

reflecting the expected higher performance of the efficient transformers

– Any ex-post adjustment of the RAB should be aligned with proper re-

setting of loss targets

– Not considering the interdependences between the RAB and losses

may cause financial losses for the network operators

Improvement of the Spanish Loss Incentive Scheme

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Analysis of Regulatory Incentives on Losses - Spain (5)

Option 2: Adjusting the current incentive scheme

– Setting Loss Targets

Use of a long term average of the actual loss values

Use a benchmark as an estimate of the efficient level of losses

– Loss Evaluation

Projected energy wholesale prices of electricity produced

Cost of providing additional transportation network capacity

– Caps on Incentive Payments

upper boundary on the level of risk to the company

reduces incentives to improve performance beyond optimal levels

Improvement of the Spanish Loss Incentive Scheme

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Conclusions (1)

Incentive regulation encourages efficiency increase and cost reduction

The power of incentives depends on benefits sharing arrangements and

length of regulatory period

System for quality of supply regulation is imperative under incentive

regulation

Economically feasible investments (positive net benefits) in loss reduction

equipment (e.g. efficient transformers) should be encouraged via the

regulatory process

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Conclusions (2)

Benefit retention period should be sufficiently long to encourage

companies to undertake investments in loss reduction equipment

– Implied in a loss target which is set annually on the basis of moving

average using historic data (e.g. last 15 years)

– Set explicitly for a period of time (e.g. two regulatory periods) by

imposing fix loss target during this time period

Setting network loss targets

– Based on the actual losses during a sufficiently long historic period

– Using some form of benchmarking (relative to the performance of other

companies) or using a reference network model

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Dr. Konstantin PetrovKEMA Consulting GmbH

Kurt-Schumacher-Str. 8

53113 Bonn / Germany

Phone: +49 228 4469058 Fax: +49 228 4469099 Mobile: +49 173 5151946 e-Mail: konstantin.petrov@kema.com