Home / Renewable Grid Power – Index / Renewable Grid Power – Application

Renewable Grid Power – Application

Case Study on Renewable Grid-Power
Electricity

Previous – Content – Next

5. Economic and Policy
Analysis – Application to Canada

5.1
Introduction

This
section presents the results of the economic modelling
of each of the fiscal instruments. The discussion is
organized and presented as follows:

• Overview
  of the fiscal instruments that are assessed
• Overview
  of the RFF model used to assess the instruments
• Summary
  of results (including a road map for understanding
  the results)
• Detailed
  discussion of the base case and each fiscal instrument
  
• Sensitivity
  analysis results
• Conclusion.
  

5.2
Overview of Fiscal Instruments Assessed

In
collaboration with the NRTEE, a base case and five fiscal
instruments were selected and modelled. They were:

• An
  emissions price, which is analogous to an emissions
  trading permit system or a carbon tax. Under this
  scenario, a shadow price is placed on carbon equivalent
  to $10/tonne of CO2. This shadow price is equivalent
  to the cost of an emission trading permit or the tax
  rate on carbon. The emissions price is applied uniformly
  across all fossil fuel generation in Canada in 2010. 
• A
  renewable portfolio standard (RPS), which requires
  that green certificates, or the equivalent, be purchased
  by utilities so that renewables generation increases
  relative to fossil fuel generation. Thus, the model
  compares the uptake of renewables attributable to
  an RPS relative to generation from fossil fuels, not
  from the entire electrical generation. Constraints
  are not placed on technologies or regional shares
  of the total RPS. Instead, prices are used as the
  determinant for the type of technology that is supplied
  at the prevailing electricity price under the RPS. 
• A
  renewable generation subsidy, which is modelled
  as a direct subsidy from government to grid-power
  RET producers on a per-kWh basis. In practice, a subsidy
  could include any fiscal instrument that lowers the
  cost of production for producers such as a direct
  production subsidy or a capital cost allowance. 
• A
  combination of RPS and generation subsidy, applied
  in tandem in both the first and second stages. We
  let the RPS be the dominant policy, since the standard
  is meaningless if the subsidy encourages more renewable
  generation than required. A notable feature of this
  combination is that relative to the case when the
  instruments are implemented in isolation, the price
  of the green certificates is offset in part by the
  subsidy. This outcome will therefore trigger distributional
  shifts in terms of cost imposition. 
• An
  R&D subsidy, which is a program targeted
  at reducing the future cost of renewables generation.
  As such, the instrument can be anticipated to have
  a greater impact in future periods. In the model,
  the increase above current renewables R&D required
  to achieve the emission reduction target is identified.

An
important point to keep in mind is that the levels of
the instruments, such as an RPS target (e.g., 10% of
generation from renewables) or a subsidy level (e.g.,
$0.01 per kWh), are solved endogenously in the model.
Each instrument is required to achieve a common emission
reduction (or policy target) and then the model solves
for the policy level that would achieve the carbon target.
Included in the predicted outcomes are the instrument
levels such as the RPS target, the subsidy level or
the investment in R&D.

5.3
Overview of RFF Renewables Uptake Model

The
RFF unified analytical model was employed to assess
the impacts of the fiscal instruments on the reduction
of greenhouse gas emissions as well as the development
and diffusion of renewable energy. This model was developed
and tested for the U.S. Environmental Protection Agency
to assess the preferred fiscal instruments for promoting
renewable energy technologies. The analytical model
is deliberately kept simple to highlight key features.
It includes two sectors, one emitting and one non-emitting,
and both are assumed to be perfectly competitive and
supplying an identical product, electricity. Fossil
fuel production is assumed to be the marginal technology,
setting the overall market price; thus, to the extent
that renewable energy is competitive, it displaces fossil
fuel generation in future policy periods.

The
model has two stages (i.e., the short-term covering
2010 to 2015 and the longer-term covering 2015 to 2030).
Electricity generation, consumption and emissions occur
in both, while investment in knowledge takes place in
the first stage and through technological change and
innovation lowers the cost of renewable generation in
the second. Thus, the model incorporates technological
change and innovation when assessing the relative merits
of the fiscal instruments. An important assumption is
that firms take not only current prices as given, but
they also take prices in the second stage as given,
having rational expectations about those prices. This
is a plausible assumption given that utilities routinely
forecast prices in future periods, especially when contemplating
large capital investments. As well, long-term power
contracts are prevalent, thus adding certainty to the
price in future periods. Appendix B provides further
details on the analytical model.

The
carbon-emitting sector of the electrical generation
industry relies on fossil fuels. As it is the mature
technology, the productivity improvements available
through new R&D are assumed to be negligible.33
Its marginal production costs are assumed to be constant
with respect to output and increasing with reductions
in emissions intensity. The representative firm chooses
emissions intensity to equate the additional costs of
abatement to the price of emissions. The full marginal
costs of generation then include both the marginal production
costs, given the emissions intensity choice, and any
effective tax, such as the price of the emissions embodied
in an extra unit of output, or the cost of green certificates
under an RPS. As long as fossil fuel generation occurs,
the competitive market price must equal the sum of these
marginal costs.

Another
sector of the industry generates without emissions by
using renewable resources. Unlike the fossil supply
curve, which is flat and set at the long-term marginal
cost of electricity, the renewable supply curve slopes
upward, reflecting marginal production costs that increase
with output (see Section 3). As the young technology,
the costs of renewable power shift down over time as
the knowledge stock increases. There are two ways to
increase the knowledge stock: investments in R&D
and “learning by doing,” which is a function
of total output during the first stage in the model.
The representative renewable energy firm chooses output
in each stage and R&D investment to maximize profits.
In the first stage, it produces until the marginal cost
of production equals the value it receives from additional
output, including the competitive market price, any
production subsidy, and the contribution of such output
to future cost reduction through learning by doing.
The firm also invests in research until the discounted
returns from R&D equal investment costs on the margin.
In the second stage, output does not generate a learning
benefit, so it depends only on the effective price for
renewables.

Grid-RET
electricity generation and fossil fuel electricity generation
are assumed to be perfect substitutes from the consumer’s
point of view. Consumer demand for electricity is a
declining function of the price, and in equilibrium,
total consumption must equal total supply, where total
supply is the sum of fossil fuel and grid-RET electricity
generation.

In
this model, fossil fuels are the marginal technology
(by the assumption of flat marginal costs), and their
generation costs determine the price of electricity.
Fossil fuel output satisfies remaining demand after
profitable renewable energy is produced, so any increase
in renewable energy production “crowds out”
fossil fuel production. Since all of the fossil sector
costs are passed on to consumers, their producer surplus
is by definition always zero (i.e., the fossil sector
is not impacted directly by the fiscal instruments in
terms of price changes, but does experience changes
in the demand for fossils, which could lead to indirect
costs associated with fixed variable costs for reduced
fossil capacity).

The
renewable sector has positive producer surplus: the
area between the price received and the marginal cost
curve. That is, some firms in the sector can produce
power below the subsidized market price and therefore
may reap some profit under the fiscal instrument. This
indicator is assessed in the model.

Consumer
surplus is the area under the demand curve above the
price of electricity. The change in consumer surplus
due to the renewable energy policy in this partial equilibrium
model is roughly the retail price change attributable
to the fiscal instrument multiplied by the average of
the quantities demanded. The change in the consumer
surplus provides a proxy for the cost impact on consumers
of each fiscal instrument – that is, faced with
higher prices, what is the cost increase to the consumer
sector?

Policies
also have implications for government revenues, which
we denote as transfers, assuming that these revenues
are raised or returned in a lump-sum fashion. For example,
a tax will raise government revenue, whereas an R&D
program is a disbursement. The change in these transfers
equals the tax revenues net of the cost of the subsidies
or programs.

The
change in societal welfare due to a policy is the sum
of the changes in consumer and producer surplus, net
of the change in revenue transfers from the subsidy
or tax. Since we target equivalent emissions reductions
for each of the fiscal instruments, we hold the environmental
effects constant across the policy scenarios. That said,
the distribution of emission reductions in the two stages
is altered by each of the instruments.

Of
course, welfare is unlikely to be the only metric for
evaluating policy. Other indicators may be total emissions,
consumer surplus, renewable energy market share, and
so on. “General equilibrium” factors –
like interactions with tax distortions, leakage or other
market failures – can also be important for determining
welfare impacts. Political economy constraints may also
be important for determining policy goals. To the extent
that these unmodelled issues are present, this partial
equilibrium presentation of welfare within the sector
will not reflect the full social impacts; still, it
represents a useful baseline metric.

While we calculate the costs of achieving emissions
targets in this case study, the benefits of the fiscal
instruments are not estimated. The fiscal instruments
through their displacement of fossil fuel can be expected
to trigger a number of environmental and economic benefits,
including:

• Improved
  ambient air quality and reduced carbon in the atmosphere
  
• Avoided
  ambient air quality impacts on sensitive ecosystem
  and health receptors and the associated economic value
  of the avoided damages
• Climate
  change mitigation benefits such as avoided ecosystem,
  health and economic damages stemming from extreme
  weather events, temperature changes and sea-level
  rise and the associated economic value of the avoided
  damages.

While
important to assessing the desirability of the fiscal
instruments from a social perspective, the benefits
are in a sense fixed in the case study by stipulating
a common emission target that all instruments achieve.
Thus, benefits are assumed to be constant across the
fiscal instruments and each instrument is then assessed
on a welfare cost basis.

The
following section presents and discusses the modelling
results with respect to changes from the baseline as
well as absolute indicators.

5.4
Summary of Results

When
reviewing the summary results it is important to remember
that the outcomes are a function of how the energy market
is influenced by each instrument. In the model, this
means that outcomes differ due to changes in three “decarbonization
drivers”:

• Renewables
  penetration
• The
  carbon intensity of fossil fuel generation
• Total
  electricity demand.

Outcomes
listed in Exhibits 5.1 and 5.2 can therefore be traced
back to an instrument’s ability to impact one
or all of these three decarbonization drivers. Exhibit
5.1 provides the estimated values for each scenario;
Exhibit 5.2 presents the percentage change in the outcomes
relative to a base. Each numbered item in the first
column, which is a modelling output, is defined as follows:

1. No
   policy base case: Our model predicts that
   with no policy, renewable energy generation will increase
   from 13% to 17% of included generation in the second
   stage, which corresponds to a 5% emissions reduction.
   Subsequent policy scenarios will target a 12% reduction
   overall from the combined emissions in the two stages
   of the no policy case. 
2. Policy
   level for 12% emissions reduction: This row
   provides an estimate of the size of the fiscal instrument
   that is required to achieve the carbon reduction target:
   
   • For
     the emissions price, a tax of $10/tonne CO2 would
     achieve the 12% reduction in carbon emissions
     from the base case carbon emissions of 106 megatonnes
     (MT).
   • For
     the RPS, a portfolio standard of 24% would achieve
     the 12% carbon reduction. This 24% is the final
     share of renewables generation in generation covered
     under this study, which consists of both renewables
     and fossil fuel generation but excludes major
     hydro and nuclear.
   • For
     the renewable generation subsidy, a value of about
     0.6 cents per kWh achieves the policy objective
     of a 12% carbon reduction.
   • When
     combined with a subsidy of 0.2 cents, the RPS
     needs to be set at a slightly higher target of
     24.2%.
   • For
     the R&D subsidy, a program that increases
     R&D spending by 61% above the base case R&D
     levels would achieve the target.
3. Electricity
   price ($/kWh): This row indicates the impact
   of the fiscal measure on the annual price of electricity
   in the first and second stages (2015 and 2030, respectively).
   In Exhibit 5.1, a price above the base case indicates
   an electricity price change attributable to the instrument.
   Exhibit 5.2 provides an indication of the percentage
   change in price relative to the base case. 
4. Carbon
   emissions (MT): Carbon emissions are presented
   as annual estimates in megatonnes of CO2 for the last
   years in the first and second stages. Carbon reductions
   are influenced by the three drivers in the following
   ways:
   • Renewable
     penetration displaces fossil generation when an
     instrument reduces renewable production costs
     relative to fossil generation costs.
   • The
     carbon intensity of fossil fuel generation is
     reduced when carbon is priced in the fossil sector
     (i.e., abatement from natural gas generation that
     displaces coal).
   • An
     increase in electricity prices reduces total electricity
     demand, which displaces output from fossil fuels.For each scenario, carbon emissions are estimated
     by multiplying the “on margin” emissions
     intensity of fossil fuel by the quantity of fossil
     fuel supplied. There are no emissions associated
     with renewable output.
5. Renewable
   output (MWh 10^11): This row indicates the
   output of renewable generation in the two stages.
   Renewable output is a function of production cost
   differentials between renewables and fossil fuels.
   Instruments impact the cost differential through subsidizing
   renewable generation, inducing renewable production
   cost decreases through innovation, and/or taxing fossil
   fuel production. There is also a temporal aspect here,
   where instruments that promote innovation reduce renewables
   costs in the second stage. 
6. Fossil
   output (MWh 10^11): As with renewable output,
   fossil fuel output is altered by the instruments through
   price changes in production costs. Fossil output is
   also altered by total demand reductions, which occur
   when an instrument increases the price of electricity. 
7. Total
   electricity output (MWh 10^11): Total generation
   includes fossil and renewable output; changes indicate
   that the instrument influences final demand through
   electricity price increases. 
8. Renewable
   R&D ($M): Expenditures are expressed
   in millions of dollars annually in total R&D spending
   by the public and private sectors. 
9. Additional
   renewables cost reduction: This row indicates
   the percent reduction in the cost of renewables electricity
   below the base case. 
10. Consumer
    surplus ($M): This is the net consumer cost
    of the instrument measured as the change in the present
    value of the total cost to consumers for both stages.
    The consumer surplus is negative and is present when
    the instrument increases the price of electricity. 
11. Producer
    surplus ($M): This is the change in the measure
    of total profit in the renewable sector for both stages.
    Renewable sector profits increase when the instrument
    raises the price received by renewable generation,
    by either a subsidy or a tax on fossil generation.
    When this occurs, profits can be made if some renewable
    production costs are below the instrument electricity
    price in the scenario. 
12. Transfers
    ($M): This is the change in government revenues,
    where a positive number is revenue and a negative
    is a disbursement. Again, the estimate is a total
    cost for both stages. 
13. Welfare
    (excluding environmental benefits) ($M):
    This is the change in social welfare, and is a proxy
    for the societal cost of the instrument. It is the
    sum of consumer and producer surpluses and transfers.
    It is an important metric, since all scenarios achieve
    the same carbon reduction target, yet have differing
    social costs. 
14. Welfare
    relative to emissions price: This is simply
    a ratio that indicates the welfare costs of each scenario
    compared with the emissions price scenario. The emissions
    price is selected as the basis for comparison since
    it has the lowest welfare cost.

Exhibit
5.1

Summary of Modelling Results for Fiscal Instruments

*
Figures may not add due to rounding.

Source: Marbek and RFF.

Exhibit
5.2

Summary of Modelling Results

Comparison of Scenarios from Base Case or Emissions
Price

*Figures may not add due to rounding.

Source: Marbek and RFF.

5.5
Discussion of the Base Case and Fiscal Instruments

A
discussion of the base case and each of the five fiscal
instruments (emissions price, RPS, generation subsidy,
combination and the R&D subsidy) is presented below.

5.5.1
Base Case

The
base case provides the reference from which the percentage
changes are estimated in Exhibit 5.2. Renewables
penetration is forecast based on the relative costs
of fossil fuel and renewables production. The baseline
penetration of renewables increases over time, reflecting
decreasing renewables production costs due to innovation.

Total
electricity output remains fixed in both periods in
the base case, and thus increased renewables penetration
decreases the carbon intensity of overall generation.
This is captured as a decrease in carbon emissions over
time, from an annual level of 106 MT in the first stage
to 101 MT in the second stage. It is recognized that
electrical production is increasing over time, but total
electricity output in the model is fixed in both stages
so that the demand and supply responses of the policies
can be better understood.

5.5.2
Emissions Price

An
emissions price works to reduce emissions by reflecting
their cost, either in terms of environmental damages
(as with an environmental levy) or in terms of opportunity
cost elsewhere in the economy (as with an emissions
cap-and-trade system). This price sends a signal to
everyone in the energy market to conserve carbon. Fossil
energy producers can reduce costs by boosting efficiency
or switching to lower-carbon fuels and processes. Since
the price of fossil energy will then incorporate the
cost of the carbon associated with that form of generation,
the price of electricity will also rise, creating two
effects. First, it signals consumers to conserve
and take advantage of opportunities to reduce their
demand, like adopting more energy-efficient appliances.
Second, it increases the price received by renewable
energy producers, encouraging production and investment
in non-emitting generation technologies.

In
the absence of major market failures, this three-pronged
decarbonizing effect is the most cost-effective way
to reduce emissions. In other words, with fossil generators,
renewables producers and consumers all responding, fewer
resources are expended to meet emissions reduction targets
compared with policies that focus only on one or two
of the “decarbonizing drivers.”

In
the results, a modest emissions price of $10/tCO2 causes
emissions to fall by 10% from the base case. Compared
with the other policies that meet that target, the emissions
price induces the greatest rise in electricity prices
(5%) and the least amount of renewables. Those results
go hand in hand, since the reduction in demand due to
the price increase and the efforts by fossil producers
to reduce their emissions intensity in response to the
carbon price reduces the need to rely on more costly
renewables to reduce carbon. This three-pronged approach
is reflected in the change in welfare ($579 million),
where the emissions price has the lowest welfare impact
of the instruments under consideration (see Exhibit
5.1).

From
a distributional perspective:

• Consumers
  incur the highest electricity price increase and consumer
  surplus loss under the emissions price. Since consumers
  are also taxpayers, the use of the revenues (i.e.,
  transfers) is important in assessing the net effect
  on households. 
• From
  a renewables producer perspective, the emissions price
  has a modest but significant impact on renewables
  output, production cost decreases and producer surplus.
  The impact is also relatively consistent across stages,
  not targeting one more heavily than the other. 
• For
  fossil fuel electricity generators, the emissions
  price is the only policy with an incentive to reduce
  emissions intensity. Although profits for the fossil
  sector are not modelled – rather, they are assumed
  to be driven to zero in the long run by the market
  – the potential costs to the fossil sector under
  an emissions price would depend on their ability to
  pass along the production costs increases due to carbon
  abatement (i.e., coal to gas) to consumers, as well
  as any windfall gains from permit allocation. 
• For
  government, significant transfers or revenue could
  be raised under the emissions price either through
  a tax-based system that collects revenue or through
  the allocation or auctioning of carbon permits under
  an emissions trading system. This is the only modelled
  scenario where significant government revenue potential
  exists. It also represents the value of the emissions
  rents, which are available to be allocated to consumers,
  generators and their shareholders, funds for transition
  assistance, or taxpayers more generally. 
• From
  society’s perspective, the welfare costs are
  lowest with the emissions price, making it the preferred
  option. One negative consequence of this scenario,
  not incorporated into this single-sector analysis,
  is that the increase in electricity prices could lead
  to economy-wide competitiveness impacts such as reduced
  exports, to the extent that industrial users of electricity
  are affected. Reserving some permits for allocation
  to trade-exposed sectors that are electricity intensive
  could mitigate these impacts. 
• An
  advantage of a cap-and-trade system is certainty in
  reaching the carbon target; however, uncertainty will
  then manifest itself in the price. All the other policies
  face challenges in setting a policy level that would
  achieve the emissions target with certainty.

5.5.3
Renewable Portfolio Standard

The
renewable portfolio standard (RPS) requires total electricity
generation to comprise a minimum share of renewable
sources. Although such a market share requirement can
be implemented in several ways – quota obligations
for retailers, green certificates for fossil generators
– the general effect is the same. As long as the
market would not meet the requirement on its own, renewables
producers receive a price premium (the value of the
green certificates they generate), while fossil energy
producers receive a negative one (the cost of the green
certificates they must buy in proportion to their generation).
Moreover, the total subsidy to renewables producers
is equal to the total effective tax paid by fossil generators,
so no net revenues are raised or lost by the government
(i.e., no transfers to or from government).

Since
the RPS does not distinguish among fossil generation
technologies, there is no incentive to reduce emissions
intensity in that sector. Consumer prices rise due to
the effective tax on fossil energy to fund the renewables
subsidy (i.e., buy green certificates), but not as much
as with the emissions price instrument. Although under
the RPS more renewable energy is generated than under
the emissions price, the timing of that generation is
changed. Normally, when prices are fixed, as costs fall
over time, renewable generation expands. However, the
RPS fixes the renewables share in both periods, and
over time this becomes easier to meet; hence, the effective
tax and subsidy fall (i.e., the price of green certificates
falls), while total electricity generation increases
with the reduced price (recall that the market price
is equal to the price of electricity plus the price
of green certificates, which fall due to innovation
over time, and therefore electricity prices fall and
final demand increases). Renewables then get a bigger
boost in the first period and less in the second. The
larger current subsidy may enable more learning by doing,
but recognizing that the support will fall in the future,
investment in cost-reducing R&D may be smaller (this
result is borne out in our scenarios).

Compared
with the emissions price, the welfare costs of the RPS
are higher by about 1.8 times. That said, the cost imposition
on consumers is lower and the profits to the renewables
sector is higher. Transfers to or from government do
not occur. As there is less of a price impact on electricity,
competitiveness and trade issues are less of a factor
under an RPS than with an emissions price. Therefore,
although the RPS may be less desirable from an economic
efficiency perspective (i.e., higher welfare costs),
the stakeholder acceptability of an RPS may in fact
be greater.

An
exception may be the fossil generators, who must pay
for the RPS, lose market share, and do not have the
option to seek more cost-effective ways to reduce their
carbon emissions. Furthermore, fixing an RPS has an
important effect on the time path of renewable generation
and thereby on the present value of the costs. The level
of the RPS that achieves the carbon reduction target
is 24.1% of total generation, which requires much greater
renewables penetration in the early stage and less in
the second stage, relative to the emissions price. Since
more renewable production occurs when it is more costly,
and less expansion occurs after knowledge accumulation
brings costs down, this front-loading of effort under
a fixed RPS raises overall welfare costs.

From
a distributional perspective:

• Consumers
  experience some electricity price increase and consumer
  surplus loss under the RPS. This effect is about 80%
  as large as with the emissions price in the first
  stage, and nearly negligible in the second. The electricity
  price rise is due to the purchase of renewable power
  in the form of green certificates (or the equivalent)
  by the fossil sector. Since renewables become cheaper
  with technical innovation, the cost of green certificates
  (and thereby consumer prices) is higher in the first
  stage but lower in the second as the cost of renewables
  supply decreases. 
• For
  renewables producers, the RPS induces a high uniform
  penetration through both periods, which is not surprising
  since the RPS fixes the share of renewables in both
  periods. Producer profits are also high, indicating
  the potential for the sector to benefit under an RPS.
  While there is certainty in terms of market share
  for the renewables sector, there is less stability
  in terms of prices, and less flexibility in terms
  of the timing of renewable generation. Furthermore,
  the fact that the implicit subsidy falls over time
  with cost decreases means that incentives for innovation
  may be muted – indeed, our model predicts less
  R&D spending than under the emissions price. Although
  more renewable generation is needed overall, so much
  is done in the first stage that the return to lowering
  costs in the second stage is lower, both because of
  the lower second-stage output (relative to the other
  policy scenarios) and also possibly because of greater
  learning by doing in the first stage, which can substitute
  for R&D. 
• For
  fossil fuel generators, output shares remain steady
  in the two periods, with the lower output in the first
  stage and higher in the second, compared with other
  scenarios. In other words, cost reductions in renewables
  allow for fossil sector expansion. Still, short-term
  transitional costs could be expected to be greater
  under the RPS than in other scenarios. Actual potential
  costs to the fossil sector under an RPS will be higher
  if they are not fully able to pass along the costs
  of green certificate costs to consumers. 
• For
  government, the RPS has a neutral impact, with no
  revenue and no program disbursements. The implicit
  subsidy to renewables producers is fully funded by
  the implicit tax on fossil producers (and consumers)
  in the form of the green certificates. 
• From
  society’s perspective, the welfare costs in
  our estimates are greater than the emissions price
  and generation subsidy, but lower than the combination
  and R&D subsidy. This ranking does not necessarily
  hold under all circumstances, but rather depends on
  the particular trade-off between the extra costs of
  encouraging more effort up front and the inefficiencies
  of not giving consumers incentives to conserve. Indeed,
  if one coped with the former problem by optimally
  designing the RPS requirement to increase over time,
  the RPS could be made to dominate the subsidy always,
  due to the presence of the modest conservation incentive. 
• Looking
  beyond the electricity sector, the increase in electricity
  prices risks causing some economy-wide competitiveness
  impacts such as decreased productivity or reduced
  exports, but these effects will be less severe than
  with the emissions price, particularly in the second
  stage. The RPS strikes a certain balance in coping
  with cost uncertainties over time, with less emission
  reduction uncertainty than a fixed emissions price,
  and less price uncertainty than a fixed cap.

5.5.4
Renewable Generation Subsidy

This
fiscal instrument includes a range of possible policies
that subsidize renewable generation (e.g., tax credits,
direct subsidies) to encourage the expansion of carbon-free
generation; however, they do nothing to encourage conservation
or reduce the emissions intensity of fossil generators.
As well, there is no impact on the price of electricity
and thus consumers are not encouraged to reduce demand
and therefore carbon emissions. Hence, much more effort
must be expended on higher-priced renewables to displace
fossil generation and meet the carbon reduction target.

The
simulations show that consumer prices remain stable,
while renewable generation expands more than with the
emissions price, particularly in the second stage, bringing
with it greater investment in R&D to reduce costs.
This extra expansion is necessary to make up for the
lack of incentives to abate directly or to conserve.
The effective subsidy that achieves the emission reduction
target is $0.006 per kWh.

In
this scenario, we estimate the generation subsidy to
cost 23% more in terms of welfare than the emissions
price. This welfare cost seems quite modest, and we
note some important caveats. First, the target is relatively
modest, given the near competitiveness of renewable
supply; the need for more substantial reductions could
magnify the limitations of the single-lever approach.
Second, consumer demand is assumed to be quite inelastic;
if demand were more sensitive to price changes, conservation
incentives would be much more important. Third, it indicates
that abatement opportunities are not as cost effective
at low prices. Finally, we do not account for any inefficiencies
in raising the substantial public revenues needed to
fund subsidies to the renewables sector. The first and
third issues are explored to some extent in Section
5.6.

Surprisingly,
the subsidy also costs less from a welfare perspective
than the RPS. This result was somewhat unexpected, since
the RPS does include some incentives for demand reduction.
However, as we noted, the magnitude of this inefficiency
loss is dwarfed by the costs of changing the timing
of the renewables expansion under a fixed RPS. Both
policies require greater expansion than the emissions
price, but the path of the renewables subsidy more closely
follows that of the optimal one.

From
a distributional perspective:

• Consumer
  prices are not impacted in the subsidy scenario, since
  all of the reductions are supplied through lower renewables
  costs, which do not affect the fossil fuel sector
  directly. Consumers would be indirectly impacted since
  it is their tax revenue that funds some portion of
  the subsidy transferred to the renewables sector. 
• For
  renewables producers, generation subsidies have the
  largest impact on profits, since they must be encouraged
  to displace more fossil output than the preceding
  scenarios. Ongoing innovation is stimulated by the
  greater scope to reduce production costs at the higher
  output levels induced by the price premium. 
• For
  fossil fuel generators, the generation subsidy has
  a similar impact on fossil output as the emissions
  price, since the additional renewable generation is
  partly offset by additional demand. The decline is
  slightly larger in the second stage, due to the more
  dramatic increase in the competitiveness of renewables
  from innovation. That fossil output may be lower with
  the subsidy than with the emissions price may seem
  surprising, since the electricity price increase is
  absent, but since the fossil sector lacks an opportunity
  to adjust its own emissions, the full burden of reductions
  falls on renewables to displace fossil output. 
• For
  government, the subsidy required to achieve the emission
  reduction target is a significant disbursement. 
• From
  society’s perspective, the welfare costs are
  greater than the emissions price. With respect to
  reaching the emissions target, the renewables subsidy
  is likely to suffer from greater uncertainty than
  the preceding policies. Although this is not modelled,
  the reasoning is twofold:
  • First,
    the uncertainty over the scope and speed for cost
    reductions in renewables is likely to be greater
    than the uncertainty surrounding the costs of
    abatement in the fossil sector or conservation
    by consumers.
  • Second,
    even if all cost uncertainties were similar, the
    reliance on only one method of emissions reductions
    raises overall uncertainty. Otherwise, if innovation
    does not lower renewable production costs significantly,
    one could engage in relatively more emissions
    abatement or conservation, whichever turns out
    to have the lower costs.

Consequently,
the renewables subsidy alone has more uncertainty regarding
the emissions that will be reduced. It also has more
uncertainty about the revenue requirement. If costs
fall more than expected, a high subsidy would induce
an oversupply relative to the carbon target, reflecting
additional efficiency loss, as well as lost public funds.
If costs do not fall as expected, either emissions targets
will not be met, and some public funds will be saved,
or the subsidy must be increased even more to meet them,
requiring greater than expected outlays.

5.5.5 A Combination of RPS and Generation Subsidy

Particularly
in renewable energy, a combination of policies is often
implemented, partly out of overlapping jurisdictions
of the federal, provincial and local governments, and
perhaps out of a diversification motive. In response
to a request by the Scoping Group, we have estimated
the effects of placing a portfolio standard and a renewable
production subsidy in place simultaneously. The key
result is that the subsidy weakens the effect of the
portfolio standard and raises costs slightly.

With
both policies, the fossil fuel producer must still purchase
“green certificates” for every unit of electricity
generated. For the renewables producer, there are now
two subsidies – the value of a green certificate,
and the direct subsidy. Since the direct subsidy boosts
renewable supply, the equilibrium price of a green certificate
does not need to be as high to reach the portfolio standard
(as compared to the RPS implemented in isolation). Consequently,
when the policy target is a portfolio share, a direct
subsidy to renewables primarily offsets the burden to
fossil producers and consumers instead.

Another
way to think of this problem is to recall that the value
of the green certificate represents the price differential
between the market price of electricity and the price
received by renewables; since the direct subsidy raises
the price received, that differential is lowered accordingly.
However, the effective RPS subsidy is not completely
crowded out by the direct subsidy. The lower certificate
price means lower electricity prices and less conservation,
requiring a bit more renewable production to meet its
share of the extra electricity demand; in our case,
with a $0.002 subsidy, we estimate the RPS must rise
slightly to 24.2%.

In
other combinations, it is also possible – particularly
in the second stage after costs fall – for the
subsidy to be strong enough to ensure that the portfolio
standard is more than met, recognizing that the quantity
of renewables supplied is a function of prices received
and knowledge in current and future periods (which lowers
renewables cost and increases uptake). For example,
if the RPS were set at 18% instead and combined with
the $0.006 subsidy, the subsidy would be the driving
policy, and green certificates would have no value.

Since
we assume the RPS is the driving policy instrument in
our combination scenario, the distributional effects
are quite similar to the RPS alone. The slight differences
are as follows:

• Consumer
  prices are slightly lower. Despite the additional
  electricity demand, emissions are also lower in the
  first stage. This results from the fact that the standard
  must be raised to offset the loss of conservation
  incentive, leading to even more reductions in the
  first stage and less in the second.
• Renewable
  production is 0.5% higher and R&D spending is
  1.5% higher.
• For
  fossil fuel generators, between the lower certificates
  cost and the additional renewable generation, output
  is nearly unchanged relative to the portfolio standard
  alone.
• Perhaps
  the most telling effect is that the government in
  this combination scenario spends just over $1 billion
  on a subsidy that has little or no effect on behaviour,
  given the presence of the RPS.
• From
  society’s perspective, to the extent the subsidy
  does affect behaviour, it tends to lower prices and
  raise overall welfare costs. The weaker conservation
  incentive and the additional front-loading of emissions
  reduction efforts by increasing the RPS are the cause
  of the increase in welfare costs, from 1.8 to 1.83
  times that of the emissions price.

5.5.6
Renewable Research Subsidy

The
renewable research subsidy uses current investments
in reducing costs to increase future renewable production.
Since it does not change any price incentives for demand
or production, nor change current costs, all the burden
of emissions reduction is placed on future displacement
of fossil by renewable generation. Furthermore, given
the lack of future production incentives, the required
cost reductions are large, and the required investments
even larger. The ability for an R&D subsidy alone
to deliver all of this is clearly an area of uncertainty.

In
the simulations, to achieve the same emissions reductions
as the $10/tC emissions price, a 61% subsidy per year
above forecast 2010 levels of $129 million to R&D
must be offered. A small increase in first-stage renewable
generation may reflect some complementarity between
learning by doing and R&D. However, nearly the entire
increase is in the second period. The cost of this delay
and lack of incentives for other actors in the electricity
market is a fourfold increase in the welfare costs above
the emissions price instrument. That said, the uptake
and cost decreases of renewable are ultimately maximized
under the R&D subsidy – because it is targeted
to meet emissions goals. This instrument clearly supports
innovation in the sector, but that is because it relies
on no other method for reducing emissions. The price
of this uptake is borne entirely by the government sector
through large transfers to the renewables sector. Electricity
prices remain unaffected, thus reducing any direct impacts
on consumers. Of course, the tax revenue is an indirect
cost borne in part by the consumers.

From
a distributional perspective:

• Consumers
  do not experience electricity price increases and
  consumer surplus losses under the R&D subsidy.
  As with the generation subsidy, they indirectly contribute
  to the renewables sector through tax contribution
  to fund the R&D subsidy. 
• For
  renewables producers, the R&D subsidy induces
  the highest penetration in the second stage. This
  penetration is driven exclusively by innovation and
  cost decreases from renewable production. An important
  caveat is the degree to which Canadian learning by
  doing and R&D can drive cost decreases in renewables.
  While such production cost decreases are observed
  in Canada and internationally, it is not certain that
  price decreases can occur through Canadian R&D
  alone that are sufficient to achieve the high levels
  of renewables penetration predicted in this scenario.
  This is particularly questionable since, as a general
  observation, innovation in renewable production occurs
  internationally and is imported into Canada. This
  uncertainty in the ability of domestic R&D subsidies
  to achieve the penetration predicted in the model
  only reinforces the result that this policy is a much
  more costly method for achieving emissions reductions. 
• For
  fossil fuel generators, the R&D subsidy does not
  impact electricity price, but does significantly reduce
  fossil output in the second stage. Although not modelled,
  costs associated with stranded assets or variable
  costs due to lower capacity utilization could occur.
  But transaction costs associated with decreased fossil
  demand are likely lower in this scenario, since a
  majority of reductions occur in the second stage.
  Thus, the transition period for the fossil sector
  to adjust to decreased demand is long and has the
  potential for costs to be minimized. 
• For
  government, the R&D subsidy requires the largest
  disbursement of the instruments. That said, promoting
  innovation is a government policy and therefore R&D
  programs are generally part of a desirable
  policy approach to decarbonization. However, given
  the longer-term nature of the reductions associated
  with R&D, a government faced with a carbon reduction
  target would likely not achieve significant reductions
  in the short term under an R&D program. 
• From
  society’s perspective, the welfare costs are
  greatest under the R&D subsidy. Another negative
  consequence of this scenario is uncertainty. For similar
  reasons to the renewable generation subsidy, the uncertainty
  of renewable cost reductions makes this a relatively
  risky policy for promoting carbon reductions –
  all the more so, since in the absence of cost reductions,
  there is no incentive for additional renewables uptake,
  in either stage. Given the uncertainty about innovation
  success more generally, and the impact of domestic
  efforts more specifically, it is highly uncertain
  that a domestic R&D program alone could achieve
  a significant carbon reduction target through renewables
  uptake. Instead, an R&D subsidy could be viewed
  as a complementary instrument that can be used to
  achieve longer-term societal goals such as promoting
  innovation.

5.6
Sensitivity Analysis

To
further test the robustness of the results presented
in the preceding discussion, it was agreed that a sensitivity
analysis would be conducted with respect to the following:

• An
  increase in the baseline electricity price
• An
  increase in the baseline price of natural gas.

For
each of these sensitivity cases, we re-estimate the
baseline scenario and the policy scenarios that achieve
reductions equivalent to a $10/tonne CO2 emissions price.
We do not report on the sensitivity of the R&D subsidy
instrument, as it was concluded by the Scoping Group
that the scenario is not plausible.

5.6.1
Increase in Baseline Forecast Electricity Price

Uncertainty
exists over the future price of electricity. The assumed
price of electricity impacts the supply of renewables
in the baseline as well as the size of the incentives
and costs required to comply with the fiscal instrument.
Uncertainty in the electricity pricing assumption is
introduced into the model in three ways:

• First,
  the price assumed in the modelling is adopted from
  the CEOU99. This estimate is somewhat dated and, indeed,
  recent forecasts predict higher oil and natural gas
  prices in the future, which translate into higher
  electricity prices.
• Second
  is the impact of reduced coal in the baseline, where
  a partial or full coal phase-out in Ontario will increase
  electricity prices as generation shifts to more expensive
  natural gas or nuclear power.
• Third,
  air emission control polices for carbon, criteria
  air contaminants and toxics will increase electricity
  costs in the future.

To
test for the impact of an increase in electricity prices,
a separate electricity price sensitivity run was conducted,
in which the base electricity price was increased by
50%. A 50% increase in electricity price is a reasonable
assumption given that a tripling of the assumed natural
gas prices in the CEOU99, which is consistent with current
natural gas prices in 2004, would impact electricity
prices in the order of 50%.

The
impacts resulting from changing the electricity price
assumption are summarized below and presented in Exhibit
5.3.

• Carbon
  emissions can be expected to be lower in the base
  case due to the higher penetration of renewables.
  This occurs since the higher electricity price makes
  renewables more cost competitive with fossil fuel
  generation, therefore reducing fossil output and carbon
  emissions. Not all of this percentage reduction translates
  into reductions under the policy scenarios; since
  additional increases in renewable production are more
  costly, the emissions price does not induce as much
  additional emissions reductions. Furthermore, the
  fossil generation that remains is more carbon intensive. 
• Renewable
  output expands due to the increased competitiveness
  of renewables when electricity prices are high. However,
  while renewable output is higher, the policy-induced
  increases are smaller in all scenarios. The reason
  is that higher prices drive renewable supply further
  up the marginal cost curve, so additional increases
  in price induce less expansion. Another effect is
  to flatten the path of emissions reductions, since
  the electricity price increase is far larger than
  any of the differentials created by the policies,
  and since this big boost is felt in both periods. 
• The
  main impact is that welfare costs drop significantly
  with a higher electricity price assumption. This result
  holds despite the fact that the electricity price,
  and thereby lost consumer surplus, is higher. Generally,
  the smaller the price differential between renewables
  and fossil fuel generation the lower the welfare implications
  of the instruments. A shift in renewables costs relative
  to fossil fuel generation costs can also be expected
  to trigger similar results. 
• The
  change in total electricity output is small, since
  initial output is assumed to be fixed. That said,
  the consumer surplus under the RPS changes dramatically
  due to the larger increase in electricity prices,
  relative to the reference scenarios. 
• These
  impacts are magnified under the other policies. The
  electricity price increase due to green certificates
  is higher by $0.001 in both stages, and the subsidy
  to achieve the same reductions as the emissions price
  is also higher. In welfare terms, the marginal cost
  of expanding renewables is so much higher that the
  welfare loss from the improper timing of reductions
  under the RPS now almost balances the inefficiency
  of not inducing additional conservation under the
  renewable generation subsidy. 
• Policy
  impacts on producer surplus are higher in all cases,
  since the higher baseline renewables output gains
  revenue from the increases in the price differential,
  while those price increases induce less expansion. 
• The
  change in R&D spending falls in all scenarios,
  due both to the greater learning by doing and to the
  smaller increase in renewable output induced by the
  policies. 

The sensitivity testing shows that when electricity prices
are high and the price differential is small, a renewable
generation subsidy is more desirable than an RPS (as in
the reference case in Exhibit 5.1). Conversely, when electricity
prices are low, an RPS is more desirable than a generation
subsidy from a welfare perspective. To understand this,
recall that welfare is measured through changes in three
outcomes:

1. Consumer
   surplus is increased when the instrument raises
   electricity prices. Under an RPS, the price of the
   green certificates is passed on to consumers, thus
   triggering consumer surplus losses, or costs. This
   effect does not occur in the generation subsidy scenario,
   since fossil producers are not impacted by the subsidy.
   Under a high price differential between renewables
   and fossil fuel generation, the size of the consumer
   surplus increases significantly under an RPS but not
   under the generation subsidy. This effect on consumer
   surplus primarily explains why an RPS is less desirable
   than a generation subsidy when electricity prices
   are high. 
2. Producer
   surplus increases with the price differential,
   since higher electricity prices allow more renewable
   producers to supply output at a profit. Under both
   an RPS and generation subsidy, the producer surplus
   increases and thus does not significantly impact the
   relative desirability of either instrument. 
3. Transfers
   only occur under the generation subsidy and they increase
   as the differential increases between renewables and
   fossil generation (as measured by the electricity
   price). Thus, the size of the transfer grows when
   the price differential increases, making the generation
   subsidy less attractive than an RPS under a low electricity
   price scenario.

The
sensitivity analysis shows that the price differential
between renewables and the electricity price is an important
determinant of the size of the welfare cost. As well,
the desirability of an RPS versus a renewable generation
subsidy is affected. These results can also be expected
when the price of renewables changes, where a decrease
in the price of renewables would produce results that
are directionally similar to an increase in the electricity
price.

Exhibit
5.3

Sensitivity Case No. 1 Results – 50% Increase
in Electricity Price

% Change (%D) from Exhibit 5.1 (Reference Case) to Sensitivity
Case

5.6.2
Increase in the Price of Natural Gas

It
can be expected that higher long-term natural gas prices
will increase the cost of carbon abatement from combined-cycle
plants. The result of higher natural gas prices is a
decrease in the competitiveness of combined cycle as
a carbon mitigating technology relative to RETs. We
can therefore expect to have less abatement and more
penetration of RETs in the emissions price scenario.
As with electricity, we increase the price of gas by
50% in the estimate of variable costs for combined-cycle
natural gas plants. The impacts associated with the
natural gas price increase are summarized below:

The
increase in natural gas price has no impact on the baseline,
since without a binding policy instrument in place no
abatement occurs.

• In
  the emissions price scenario, fossil emitters can
  either abate internally or use RETs to achieve their
  emission reduction constraint. With higher natural
  gas prices increasing the cost of internal carbon
  abatement, as expected, more RETs are deployed. This
  deployment does not, however, have a large relative
  impact on emissions. 
• For
  the RPS and generation subsidy, there is no incentive
  for the fossil sector to abate internally, and thus
  the rising natural gas price has virtually no impact
  on the predicted outcomes.

In
conclusion, the sensitivity results indicate that increasing
natural gas prices has a minimal impact on the outcomes
with respect to the reference case. As discussed in
the previous scenario, however, increasing gas prices
could increase the price of electricity, and this effect
would have a real impact on the scenario outcomes.

5.7
Conclusion

We
conclude that the results are robust to changing key
variable assumptions. Indeed, our core observation holds:
the economic efficiency and environmental effectiveness
of the EFR instruments are linked to their ability to
influence the entire electricity market, and three decarbonizing
drivers in particular. As a general rule, an EFR instrument
will be more efficient and effective if it signals to
multiple agents in the electricity market that carbon
is more expensive: fossil producers will reduce their
emissions intensity; renewables producers will supply
more output when the price differential between renewables
and fossil generation decreases; and consumers will
take measures to conserve electricity, reduce demand
and displace fossil output. This finding holds under
multiple input variables and explains why an emissions
price is preferable to an RPS or renewable generation
subsidy. A good example of the increased risk in using
a single instrument is highlighted by the R&D instrument
scenario, where the emission reduction is entirely reliant
on the ability of R&D investments to reduce renewables
costs through innovation. While cost reductions can
be expected to occur from R&D spending, the scope
and scale of the cost reductions is questionable, thus
increasing the overall uncertainty in the instrument.