Download Electricity Commission SOO Scenario Analysis – Discount Rates

Electricity Commission SOO Scenario Analysis – Discount Rates
1.
Introduction
The Electricity Commission is developing a Statement of Opportunities to meet the
requirements outlined in Part F of the Rules. As part of this process it is proposing
future generation scenarios for the purpose of testing the adequacy of the transmission
system under a range of possible futures. Testing the adequacy of the transmission
system using these scenarios is intended to highlight opportunities for investment in
transmission and alternatives to transmission.
This approach involves the use of discount rates for at least two purposes, including;
discounting cash flows to calculate the “unit cost” of power from particular power
stations, and discounting cash flows to establish “optimised” power station
commissioning schedules.
This note suggests discount rates to use in applying this approach.
2.
Scenario Planning Approach
In order to develop the generation scenarios the Commission is evaluating a range of
generation project options appropriate to each scenario. Each scenario is built up using
an electricity supply/demand energy balance model (GEM) developed specifically for this
task. New power stations are scheduled in the model to meet demand as it increases in
the scenario. The concept involves drawing power stations from a catalogue of options
designed for that scenario, starting with the lowest cost options first. This approach is
intended to mimic the development of new power stations by commercial players in a
market environment.
Given a catalogue of future generation options available to the commercial players in the
sector, the likely future supply pattern can be inferred by finding which generation
options first become profitable as prices rise. This is a relatively straight-forward
modelling exercise although there are some complexities in forecasting how commercial
behaviour in the wholesale market will interact with the profitability of generation options
that have different roles in the merit order.
To establish which generation options would become profitable as prices rise the
approach involves calculating a “unit cost” for each option. This unit cost is calculated
by amortising the capital costs over the life of the power station, and estimating the fuel,
operating and maintenance costs. These costs are spread over the expected output of
the power station, making certain assumptions about the likely station operating
patterns. In this way a unit cost is assessed in cents per unit (kWh) for each power
station option and a “supply curve” of generation options is developed.
3.
Applying Discount Rates
As closely as possible, this forecasting exercise should mimic how the commercial
players will assess their investment opportunities. In particular, it should make realistic
allowances for the costs of capital facing the companies involved and the risks of the
projects. These factors should be taken into account in assessing the unit cost of each
power station option. Section 4 of this note addresses this question.
The approach to developing the scenarios also involves using GEM to simulate supply
and demand over 30 years, calculate capital, fuel, operating and maintenance costs, and
to estimate the cost of any shortages of supply that might eventuate during dry periods.
The aim is to develop a schedule of new power stations that mimics the likely market
outcomes by seeking to minimise the overall NPV cost. A suggested approach for
discounting these cash flows is addressed in section 5.
4.
Cost of Capital for Project Unit Costs
The calculation of unit costs in the SOO scenario project is intended for ranking projects
and reaching conclusions about the level of wholesale electricity price that would justify
a particular investment proceeding. It is therefore important that this forecasting
exercise mimic how potential investors would assess their investment opportunities.
Individual investors will approach the issues of project evaluation and assessing project
risk in many different ways. Some will look for positive net present values when
discounting cash flows using the investor Weighted Average Cost of Capital (WACC).
Some will factor explicit risks into project evaluations and some will assess projects
using a hurdle rate of return that is higher than the firm’s WACC.
The WACC for firms investing in the New Zealand electricity market will vary with the
investor perceived risks associated with those firms. For the analysis of the unit cost of
power from projects for the SOO scenarios it should be assumed that investors in new
power station projects are likely to be a combination of existing generator participants or
new entrants with similar costs of capital.
Asset pricing models like the Capital Asset Pricing Model (CAPM) give an indication of
likely investor WACC. This note assesses the WACC for firms likely to invest in the
electricity sector using the Brennan-Lally1 simplified version of CAPM. The range of
plausible input assumptions that has been derived, and the calculation of WACC is
outlined in Table 1.
1
Reference Lally 1992
2
Table 1: WACC Calculation
CAPM Calculation
Low
Med
High
Risk Free Rate
Debt Margin
Tax Rate
Leverage
Asset beta
Market risk premium
Equity Beta
Cost of debt
Cost of equity
Nominal WACC
Rf
p
Tc
L
Ba
MRP
Be
Kd
Ke
WACCn
5.6%
1.0%
33.0%
35.0%
0.50
7.0%
0.77
6.6%
9.1%
7.5%
6.0%
1.3%
33.0%
40.0%
0.60
7.5%
1.00
7.3%
11.5%
8.9%
6.4%
1.6%
33.0%
45.0%
0.70
8.0%
1.27
8.0%
14.5%
10.4%
Inflation
Real post-tax WACC
WACCr
2.5%
4.9%
2.5%
6.2%
2.5%
7.7%
This suggests a relatively wide plausible range of between 4.9% and 7.7% per annum
(post-tax real) for firms operating in the electricity sector.
It is relatively difficult to benchmark these calculations against investor perceptions about
WACC because most firms regard cost of capital and internal project hurdle rates as
confidential. This is made more difficult because, as a result of barriers to entry into
generation by newcomers, most of the potential investors are SOEs and their investment
thresholds are less observable than private participants. Nevertheless, there are
estimates of WACC for Contact Energy and Trustpower that have been made by
investment advisors and other parties. These are outlined in Table 2.
Table 2: WACC Estimates for Private Generators
Company
WACCn
Estimated by
Date
Contact Energy
8.8%
Cameron Partners
October 2004
Contact Energy
8.5% – 9.0%
Grant Samuel
September 2004
Contact Energy
8.8%
Pricewaterhousecoopers
March 2006
Trustpower
8.9%
Alliant Energy
May 2006
Trustpower
9.3%
Pricewaterhousecoopers
March 2006
These estimates are in good agreement and tend to confirm values for nominal WACC
in the range between the mid-point and the high end of the calculations provided in
Table 1. This is not surprising because the investment advisors tend to use similar
versions of CAPM to derive WACC for individual firms.
Ideally, the evaluations underlying the development of a supply curve of generation
options would allow for option values or the firms’ incomplete diversification of project
risks. These adjustments are not feasible in modelling the whole supply curve, and
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instead it is necessary to apply some sort of mark-up to the estimated WACC. Indeed,
this appears to be what many firms do in practice in investment appraisal.
For the SOO scenario analysis it is therefore proposed to calculate power station unit
costs using a discount rate towards the upper end of the plausible range of WACC for
generation investors. This approach should allow most investors a positive NPV from a
proposed investment. A rate of 7.7% per annum for discounting real post-tax cash flows
is recommended. The model used to calculate the unit cost of different generation
projects using this discount rate should incorporate tax effects including the impact of
depreciation on tax.
5.
Discounting Cash Flows to Determine Generation Scenarios
The approach to developing the generation scenarios involves using GEM to simulate
supply and demand over 30 years, calculate capital, fuel, operating and maintenance
costs, and to estimate the cost of any shortages of supply that might eventuate during
dry periods. The aim is to develop a schedule of new power stations that mimics the
likely market outcomes by seeking to minimise the overall NPV cost over the 30 year
period.
Ideally this would involve assessing tax effects on a project by project basis and using
the same discount rate 7.7% per annum as determined in section 4 to discount real posttax cash flows. This would tend to mimic the outcomes from a series of rational market
investment decisions. However, this approach could be overly complex and impractical
because of the need to allow for the effects of depreciation for tax purposes on different
power station projects.
A simpler alternative that could provide a reasonable approximation is to gross up the
effective WACC to an approximate pre-tax number and apply this rate to the pre-tax
cash flows. Grossing up the discount rate in this way is not completely straight-forward
because tax has a different effect on capital expenditure (which is only deductible over
time) relative to operating expenditure (which is deductible in the year in which it is
incurred). Calculations indicate that discounting post-tax cash flows for typical power
stations at 7.7% is equivalent to using a discount rate of between 9.5% and 11.5% per
annum applied to pre-tax cash flows. The wide range of pre-tax equivalent discount
rates results from the difference in cash flow profiles exhibited by different power station
technologies.
Rather than compromise accuracy by grossing up the discount rate and applying it to
pre-tax cash flows, it is proposed to undertake the NPV calculations using the same
discount rate 7.7% per annum as determined in section 4 to discount real post-tax cash
flows, and to calculate the impact of depreciation for each power station type. This will
involve:
• Deducting tax at 33% from all operating, maintenance and fuel expenditures (opex);
• Calculating annual depreciation of the capital expenditure for each power station
project using the appropriate diminishing values for tax purposes;
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• Deducting 33% of the annual depreciation from the cash flows;
• Applying a 7.7% per annum discount rate to all cash flows.
This means that in each year the cash flow will be:
Cash flow = capex + opex*.67 – dep*.33
Using this approach will best mimic how potential investors would assess their
investment opportunities.
6.
Depreciation Rates for power station Projects
The approach proposed for discounting post-tax cash flows in both the unit cost model
and for determining the “optimised” power station schedule relies on calculating the
depreciation for tax purposes on a project by project basis. The appendix to this note
outlines the current allowable rates of depreciation for tax purposes and how these
should be applied to various generic power station projects..
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Appendix – Calculation of Weighted Average Depreciation for Tax Purposes for Power Station Projects
Depreciation Rates
Dim Val
Loading
Generators & turbines
9.5%
11.4%
Wind generators & turbines
18.0%
21.6%
Hydro structures and land
4.0%
4.8%
Pipes and wells
9.5%
11.4%
Electrical equipment
7.5%
9.0%
Weighted Depreciation
Hydro Stations
Coal Stations
Gas Stations
Wind Stations
%CV
Part%
%CV
Part%
%CV
Part%
15.0%
1.7%
60.0%
6.8%
80.0%
9.1%
0.0%
75.0%
16.2%
2.0%
0.1%
2.0%
0.1%
5.0%
0.0%
80.0%
3.8%
0.0%
0.0%
5.0%
0.5%
6.0%
0.0%
38.0%
3.4%
%CV
0.0%
18.0%
10.4%
1.6%
20.0%
10.8%
Geothermal Stations
Part%
%CV
Part%
0.0%
35.0%
4.0%
0.2%
20.0%
1.0%
0.0%
30.0%
3.4%
1.8%
15.0%
1.4%
0.0%
18.2%
9.7%
Note that:
1. Dim Val is the annual rate of deprecation for tax purposes allowed by Inland Revenue
2. Loading includes the 20% depreciation loading applied to new assets
3. %CV is the estimated proportion of capital value allocated to a particular depreciation category
4. Part% is the calculated contribution to the weighted depreciation for a particular category of equipment
5. Weighted Depreciation is the calculation of the depreciation rate that should be applied to the generic power station type
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