| |
|
Case Study on Renewable
Grid-Power Electricity
Executive Summary
Submitted
by Marbek Resource Consultants in association with Resources
for the Future
June
2004
|
|
1.
INTRODUCTION
The National Round Table on the Environment and
the Economy (NRTEE) has initiated a program to examine the role
of ecological fiscal reform (EFR) in meeting the challenges of
implementing sustainable development in Canada. The first phase
of the EFR program, which focussed on the agricultural, transportation
and chemical sectors, demonstrated that fiscal policy is one of
the most powerful means at the government’s disposal to
influence outcomes in the economy; if used in a consistent and
strategic manner, EFR can promote objectives that have simultaneous
economic and environmental benefits.
In the spring of 2003, the NRTEE launched the
second phase of its EFR program, which focuses on the potential
contribution of EFR to reducing carbon dioxide (CO2)
emissions from energy. The goal of this second phase is to
“examine how to reduce energy-based carbon emissions,
both in absolute terms and as a ratio of GDP, using fiscal
policy without increasing other pollutants.” As in the
previous phase, this phase of the EFR program includes the
development of case studies on three sectors that can contribute
significantly to the “decarbonization” of Canada’s
energy sector: renewable energy, hydrogen and energy efficiency.
This case study provides an analysis of the
role that fiscal policy can play in promoting the long-term
development of Canada’s renewable energy (RE) sector.
EFR is recognized as a lever to promote and, where appropriate,
accelerate the use of renewable energy technologies (RETs)
in order to make long-term reductions in energy-based carbon
emissions. This case study explores the ability or “traction”
of five fiscal instruments to improve the uptake or deployment
of RETs connected to the electricity grid (“grid-power
RETs”) in Canada.
2.
THE RENEWABLE ENERGY CONTEXT
The term “renewable energy technologies”
is commonly used interchangeably with such terms as “clean
energy,” “green power,” “alternative
energy” and “low-impact energy.” While there
is considerable overlap in the technologies included in each
group, the terms are not identical. In practice, these definitional
differences can become quite important when dealing with the
RET policy and technology eligibility issues.
This case study adopts the definition of RETs
used by the Environmental Choice Program (ECP)—Environment
Canada’s ecolabelling program—for two reasons:
-
the goal of the EFR program specifies that
the “decarbonization” of the energy sector not
increase other pollutants; and
-
an implied goal of this initiative is the
promotion of innovation.[For readers not familiar
with the ECP, the links between these two points and the
use the ECP definition of RETs may not be obvious. Suggest
adding a short explanation.]
The NRTEE also directed that the case study
examine only those RETs that generate electrical power (as
opposed to thermal technologies such as solar water heaters)
and that are—or will be—tied into the national
electricity grid (as opposed to stand-alone systems).
Consequently, this case study examines the following
technologies:
-
-
-
grid-connected photovoltaics (PV);
-
landfill gas (for electricity generation);
-
biomass (for electricity generation);
-
ocean energy, including wave and tidal
power conversion technologies; and
-
3.
GRID-POWER RETS IN CANADA
The study addresses three key areas with respect
to grid-power RETs:
-
CURRENT STATUS. What is
the current status of each technology in terms of installed
electricity generating capacity (connected to the Canadian
grid), technical maturity and costs?
-
POTENTIAL IN CANADA. What
is the long-term maximum generating capacity for each technology
and how much of this capacity is achievable by 2010 and
2020?
-
FUTURE COSTS AND LEARNING TRENDS.
What is the projected cost of each technology and what are
the learning trends that affect this cost ?
CURRENT STATUS
Table 1 shows Canada’s current (2003)
installed generating capacity by source, as well as the total
share of electricity generated by each source. As illustrated,
Canada’s installed renewable generating capacity—with
large hydro and all biomass installations included—is
over 70,000 megawatts (MW), or about 60% of the total; virtually
all of this capacity is large hydro.
Table
1
Installed Generating Capacity and Annual Electricity Generation
Canada (2003)
Source
|
Installed
Capacity
|
Generation
|
megawatts
|
%
|
gigawatt
hours
|
%
|
Hydro |
68,100
|
58
|
346,000
|
59
|
Nuclear |
12,600
|
11
|
81,700
|
14
|
Coal |
16,600
|
14
|
109,400
|
19
|
Oil |
7,500
|
6
|
14,200
|
2
|
Natural
gas |
11,000
|
9
|
29,100
|
5
|
Wind
and biomass |
2,200
|
2
|
9,100
|
2
|
Totals |
118,000
|
100
|
589,500
|
100
|
Source: National Energy Board, http://www.neb.gc.ca/energy/SupplyDemand/2003/index_e.htm.
If the ECP’s more stringent criteria are
used, large hydro and some biomass facilities are excluded
and the figure drops significantly. A breakdown of the estimated
current (2003) installed generating capacity of ECP-certifiable
grid-power RETs is shown in Table 2. In 2003, these RETs generated
an estimated 12,100 gigawatt hours (GWh) of electricity, or
about 2% of all electricity generated in Canada.
Table
2
(Discussion of the source/background for these numbers found
in the full report)
Installed Generating Capacity of ECP-Certifiable Grid-Power
RETs
Canada (2003)
RET
|
Capacity
Factor
(%)
|
Installed
Capacity (megawatts)
|
Generation
(gigawatt hours/year)
|
%
of Total Grid-Power RET Generation
|
Wind
(On-shore) |
35
|
316
|
970
|
8
|
Hydro* |
60
|
1,800
|
9,460
|
78
|
Solar
PV |
14
|
0.092
|
0.1
|
0
|
Landfill Gas |
90
|
85
|
670
|
6
|
Biomass |
80
|
128
|
900
|
7
|
Wave |
35
|
0
|
0
|
0
|
Tidal |
35
|
0
|
0
|
0
|
Geothermal
(Large) |
95
|
0
|
0
|
0
|
TOTAL
|
2,300
|
12,100
|
100
|
* Includes many small hydro sites that
may NOT be ECP-certifiable
POTENTIAL IN CANADA
An RET’s technical potential
is its maximum generating capacity over the long term. For
example, if wind power has a technical potential of 100,000
MW, this means that wind turbines could supply 100,000 MW
of electricity if they were installed in every technically
feasible location across the country.
Table 3 provides the estimated technical potential
of each grid-power RET. The ranges reflect a high level of
uncertainty.
Table
3 [Sourcing discussed in full report (as with Table 2)]
Technical Potential of ECP-Certifiable Grid-Power RETs
Canada
RET
|
Capacity
Factor
(%)
|
Technical
Potential (total, not additional)
|
Installed
Capacity (megawatts)
|
Generation
(gigawatt hours/year)
|
|
|
Low
|
High
|
Low
|
High
|
Wind
(On-shore) * |
35
|
28,000
|
100,000
|
85,800
|
306,600
|
Low-Impact Hydro |
60
|
11,000
|
14,000
|
57,800
|
73,600
|
Solar
PV |
14
|
9,800
|
100,000
|
12,000
|
122,600
|
Landfill Gas |
90
|
350
|
700
|
2,700
|
5,500
|
Biomass |
80
|
6,800
|
79,300
|
47,700
|
555,600
|
Wave |
35
|
10,100
|
16,100
|
31,000
|
49,400
|
Tidal |
35
|
2,500
|
23,500
|
7,700
|
72,100
|
Geothermal
(Large) |
95
|
no
data
|
3,000
|
no
data
|
25,000
|
* Off-shore wind is not included because of
the lack of independent estimates. See Appendix B.3 of the
main report for details.
Practical potential recognizes
that an RETs technical potential is hampered by such factors
as grid access and capacity; zoning and permitting; technological
advances; financing; market demand and acceptance; and design,
manufacturing and installation capacity.1
Table 4 provides the estimated practical potential
of each grid-power RET. The estimates are based on consideration
of several factors and consultations with industry and government.
Again, a range is provided.
Table 4
Practical Potential of ECP-Certifiable Grid-Power RETs in
Canada
RET
|
Cap
Factor
(%)
|
Practical
Potential (total, not additional)
|
Annual
Growth in Installed Capacity to Reach Practical Potential
(%)*
|
Installed
Capacity (megawatts)
|
Generation
(gigawatt hours/year)
|
2010
|
2020
|
2010
|
2020
|
Min
|
Max
|
Low
|
High
|
Low
|
High
|
Low
|
High
|
Low
|
High
|
Wind
(On-shore) |
35
|
25
|
64
|
5,000
|
10,000
|
15,000
|
40,000
|
15,300
|
30,700
|
46,000
|
122,600
|
Low-Impact
Hydro |
60
|
18
|
27
|
5,600
|
9,000
|
9,800
|
no
data
|
29,400
|
47,300
|
51,500
|
no
data
|
Solar
PV |
14
|
152
|
347
|
60
|
265
|
225
|
3,295
|
100
|
300
|
300
|
4,000
|
Landfill
Gas |
90
|
10
|
17
|
170
|
no
data
|
250
|
no
data
|
1,300
|
no
data
|
2,000
|
no
data
|
Biomass |
80
|
42
|
73
|
1,500
|
2,000
|
no
data
|
6,000
|
10,500
|
14,000
|
no
data
|
42,000
|
Wave |
35
|
0
|
infinite
|
0
|
20
|
4
|
no
data
|
0
|
60
|
12
|
no
data
|
Tidal |
35
|
infinite
|
infinite
|
4
|
300
|
50
|
2,000
|
12
|
900
|
200
|
6,100
|
Geothermal
(Large) |
95
|
infinite
|
infinite
|
100
|
600
|
1,500
|
no
data
|
800
|
5,000
|
12,500
|
no
data
|
* Assuming logarithmic growth and based on practical potential
in 2010 and 2020. The growth rates are not forecasts of installed
capacity, but rather the annual growth required to reach the
practical potential. See Appendix C of the main report for
details.
FUTURE COSTS AND
LEARNING TRENDS
Table 5 presents the estimated levelized costs
for each grid-power RET. To ensure consistency among the technologies,
all cost data are derived from recent estimates provided by
the International Energy Agency (IEA). Again, a range is provided.
Table 5 also provides IEA estimates of cost
reductions for each technology over the study period. The
forecast levels of cost reduction are based on learning theory.
This theory, which is well supported by empirical data, defines
the link between the increase in installed capacity and the
rate of cost decrease.
The practical potential and levelized costs
are used in modelling the fiscal instruments. The results
of the modelling are discussed in Section 4.
Table
5
IEA Cost Reductions and Estimates for ECP-Certifiable Grid-Power
RETs*
RET |
Cap
Factor
(%) |
Cost
Reduction
|
Cost
Estimates
|
Cost
Reduction Every 10 Years (%)
|
Annual
Cost Reduction (%)**
|
Levelized
Cost Estimates (¢CAN (2000)/kilowatt hour)
|
2003
|
2010
|
2020
|
Min
|
Max
|
Min
|
Max
|
Low
|
High
|
Low
|
High
|
Low
|
High
|
Wind
(On-shore) |
35
|
25%
|
25%
|
3%
|
3%
|
3.8
|
15.1
|
3.0
|
11.3
|
1.9
|
8.5
|
Low-Impact
Hydro |
60
|
0%
|
13%
|
0%
|
1%
|
2.5
|
18.8
|
2.5
|
16.3
|
2.3
|
15.2
|
Solar
PV |
14
|
30%
|
50%
|
4%
|
7%
|
22.6
|
100.3
|
12.5
|
50.2
|
7.5
|
30.1
|
Landfill
Gas |
90
|
0%
|
20%
|
0%
|
2%
|
2.5
|
18.8
|
2.5
|
15.1
|
2.3
|
13.5
|
Biomass |
80
|
0%
|
20%
|
0%
|
2%
|
2.5
|
18.8
|
2.5
|
15.1
|
2.3
|
13.5
|
Wave |
35
|
no
data
|
no
data
|
no
data
|
no
data
|
4.4
|
7.6
|
no
data
|
no
data
|
no
data
|
no
data
|
Tidal |
35
|
no
data
|
no
data
|
no
data
|
no
data
|
4.7
|
9.6
|
no
data
|
no
data
|
no
data
|
no
data
|
Geothermal
(Large) |
95
|
10%
|
25%
|
1%
|
3%
|
2.5
|
15.1
|
2.5
|
12.5
|
2.1
|
10.3
|
Source: IEA figures as cited in Background
Document for the Green Power Workshop Series, Workshop #4,
Pollution Probe, February 2004, pp. 30–32, http://www.pollutionprobe.org/whatwedo/GPW/calgary/gpwbackgroundercalgary.pdf.
* Cost estimates are for all countries that are members of
the Organisation for Economic Cooperation and Development;
the wide range of values shown reflects both the diversity
of conditions experienced and the high levels of uncertainty.
** Assuming logarithmic cost reductions.
Table 6 presents the share of total electricity
generation in Canada in 2010 covered under this case study.
Table 6
Projected Share of Generation by Source
Canada (2010)
Source |
Projected
Generation in 2010 (gigawatt hours)
|
Share
of Total Generation
(%)
|
Grid-Power
RETs
(as included in this study)
|
31,000*
|
5
|
Fossil
Fuels (coal, gas and oil as included
in this study) |
198,000**
|
32
|
Other
(nuclear and renewables excluded from this study) |
394,000
|
63
|
Total
|
623,000**
|
100
|
* Canada’s Energy Future: Scenarios
for Supply and Demand to 2025 (Techno-Vert Scenario),
National Energy Board, 2003, http://www.neb-one.gc.ca/energy/SupplyDemand/2003/index_e.htm.
** Canada’s Emissions Outlook: An Update, Natural
Resources Canada, 1999, http://www.nrcan.gc.ca/es/ceo/update.htm.
4. MODELLING RESULTS
This section presents the results of the modelling
of the fiscal instruments. The discussion is organized as
follows:
-
overview of the fiscal instruments assessed;
-
overview of the model used to assess the
instruments;
-
-
detailed discussion of the base case and
each fiscal instrument; and
-
sensitivity analysis results.
4.1 FISCAL INSTRUMENTS
ASSESSED
In collaboration with the NRTEE, a base case
and five fiscal instruments were selected and modelled. They
are:
-
An emissions price, which
is analogous to an emissions trading permit system or a
carbon tax. Under this scenario, a shadow price of $10/tonne
is placed on CO2 emissions; this is the cost
of an emissions 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 utilities purchase green certificates,
or the equivalent, so that renewables generation increases
relative to fossil fuel generation. The model compares the
uptake of renewables attributable to an RPS relative to
generation from fossil fuels (i.e., not relative to all
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.
-
A renewable generation subsidy,
which is modeled as a direct subsidy for grid-power RET
producers on a per kilowatt hour (kWh) basis. In practice,
this 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, modelled in tandem. We let the RPS be
the dominant policy, since the RPS is meaningless if the
subsidy encourages more renewable generation than required.
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.
-
A subsidy for research and development
(R&D), which is a program to reduce the future
cost of renewable generation. The model identifies the annual
increase in renewables R&D required to achieve the emissions
reduction target.
In the model the levels of the instruments,
such as an RPS target (i.e., 10% of generation from renewables)
or a subsidy level (i.e., $0.01 per kWh), are solved endogenously.
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.
4.2 OVERVIEW OF THE MODEL
The case study uses Resources for the Future’s unified
analytical model to assess the impact of the fiscal instruments
on greenhouse gas emissions and the development and diffusion
of grid-power RETs. This model was developed and tested for
the United States’ Environmental Protection Agency to
assess the preferred fiscal instruments for promoting RETs.
The model includes two sectors of the electricity generation
industry: one that emits CO2 and one that does
not. Both are assumed to be perfectly competitive and supplying
an identical product, electricity. As the marginal technology,
fossil fuel generation sets the overall market price of electricity.
Thus, to the extent that renewable energy is competitive,
it displaces fossil fuel generation in future policy periods.
The model has two stages: a short-term stage covering 2010
to 2015 and a longer term stage covering 2015 to 2030. Electricity
generation, consumption and emissions occur in both stages.
Investment in knowledge takes place in the first stage, producing
technological change and innovation that lowers the cost of
renewable generation in the second.
The CO2-emitting sector relies on fossil fuels.
As the mature technology, fossil fuel generation is assumed
to realize only negligible productivity improvements from
new R&D.2 Its marginal
production costs are assumed to be constant with respect to
output, and to increase 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
or carbon 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.
The non-emitting sector uses RETs. 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.
As the young technologies, RETs become less expensive over
time as the knowledge stock increases. There are two ways
to increase the knowledge stock: investments in R&D and
“learning by doing” (LBD), 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
investments 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.
Since all fiscal instruments have the same emissions reduction
target in this case study, we hold the environmental effects
constant across the policy scenarios. By displacing fossil
fuels, the fiscal instruments are expected to have several
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; and
-
the benefits of mitigating climate change,
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.
4.3 SUMMARY OF RESULTS
The results are a function of how the energy market is influenced
by each instrument. In the model, results differ according
to changes in three decarbonization drivers:
renewables penetration, the carbon intensity of fossil fuel
generation and total electricity demand.
The results in Table 7 can be traced back to an instrument’s
ability to affect one or all of the decarbonization drivers.
Generally, an instrument will be more economically efficient
if it affects all three drivers.
Each numbered item in the first column of Table 7 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
required to achieve the emissions reduction target.
3. Electricity price ($/kWh). This row indicates
the impact of the fiscal measure on the annual price of electricity
in the first (2010 to 2015) and second (2015 to 2030) stages.
4. Carbon emissions (megatonnes). Annual
estimates of CO2 emissions for the last years of
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 generate 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);
and
-
an increase in the electricity price reduces
total electricity demand, which displaces fossil fuel generation.
For each scenario, carbon emissions are estimated by multiplying
the “on-margin” emissions intensity of fossil
fuel with the quantity of fossil fuel supplied.
5. Renewable generation (megawatt hours 10^11).
This row indicates electricity generation from grid-power
RETs during each stage. Renewable generation is a function
of production cost differentials between renewables and fossil
fuels. Instruments affect the cost differential by subsidizing
renewable generation, promoting innovations that reduce the
cost of renewable generation, and/or taxing fossil fuel production.
Instruments that promote innovation reduce renewable costs
and carbon emissions in the second stage.
6. Fossil fuel generation (megawatt hours 10^11).
As with renewable generation, fossil fuel generation is altered
when the fiscal instruments change the cost of production.
Fossil fuel generation is also altered by reductions in total
demand, which occur when an instrument increases the price
of electricity.
7. Total electricity generation (megawatt hours 10^11).
Total generation includes fossil fuel and renewable generation;
changes indicate that the instrument influences total demand
through electricity price increases.
8. Renewable R&D ($million/year). Total
R&D spending by the public and private sectors.
9. Additional renewables cost reduction.
This row indicates the percent reduction in the cost of renewable
generation.
10. Consumer
surplus ($million/year). This is the net cost to
the consumer, 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 ($million/year). This is the change in total
profits in the renewable sector for both stages. Renewable
sector profits increase when the instrument raises the price
received by renewable generation, either by a subsidy or a
tax on fossil generation. When this occurs, profits can be
made if some renewable production costs are below the electricity
price.
12. Transfers
($million/year). This is the change in government
revenues for both stages. A positive number is revenue and
a negative number is a disbursement.
13. Welfare
(excluding environmental benefits) ($million/year).
This is the change in social welfare, and is a proxy for the
societal cost of the instrument. It is the sum of government
transfers and consumer and producer surpluses. It is an important
metric, since all scenarios achieve the same emissions reduction
target yet have differing social costs.
14. Welfare
relative to emissions price. This is simply a ratio
that indicates the welfare costs of each scenario compared with
the emissions price scenario. The emissions price is selected
as the basis for comparison because it has the lowest welfare
cost.
Table 7
Summary of Modelling Results
($CAN, 2000)
|
Base
Case
|
Emissions
Price
|
Renewable
Portfolio Standard
|
Renewable
Generation Subsidy
|
Combination
RPS and RGS
|
Renewable
Research Subsidy
|
1.
Policy level for 12% emissions reduction |
|
$10/tonne
of CO2
|
24%
of all generation (excluding major hydro and nuclear)
is renewable *
|
$0.006
|
RPS
= 24.21%
RGS = $0.002
|
61%
increase
|
2.
Electricity price ($/kWh)
|
|
|
|
|
|
|
1st
stage |
$0.092
|
$0.097
|
$0.095
|
$0.092
|
0.095
|
0.092
|
2nd
stage |
$0.092
|
$0.097
|
$0.093
|
$0.092
|
0.092
|
0.092
|
3.
Carbon emissions (MT CO2)
|
|
|
|
|
|
|
1st
stage |
106
|
98.10
|
91.00
|
98.97
|
91.08
|
104.00
|
2nd
stage |
106
|
84.40
|
91.60
|
83.50
|
91.95
|
77.40
|
4.
Renewable generation (MWh 10^11)
|
|
|
|
|
|
|
1st
stage |
0.29
|
0.40
|
0.54
|
0.42
|
0.55
|
0.31
|
2nd
stage |
0.38
|
0.66
|
0.55
|
0.72
|
0.55
|
0.83
|
5.
Fossil generation (MWh 10^11)
|
|
|
|
|
|
|
1st
stage |
2.00
|
1.85
|
1.71
|
1.87
|
1.72
|
1.98
|
2nd
stage |
1.91
|
1.59
|
1.73
|
1.57
|
1.73
|
1.46
|
6.
Total electricity generation (MWh 10^11)
|
|
|
|
|
|
|
1st
stage |
2.29
|
2.25
|
2.26
|
2.29
|
2.27
|
2.29
|
2nd
stage |
2.29
|
2.25
|
2.28
|
2.29
|
2.29
|
2.29
|
7.
Renewable R&D ($ million)
|
$129
|
$450
|
$320
|
$533
|
$325
|
$1,576
|
8.
Additional renewables cost reduction (%) |
0%
|
15%
|
13%
|
16%
|
13%
|
26%
|
9.
Consumer
surplus ($ million) |
$0
|
($11,690)
|
($4,521)
|
$0
|
($3,533)
|
0
|
10.
Producer
surplus ($ million) |
$0
|
$2,215
|
$3,480
|
$2,846
|
$3,547
|
$1,590
|
11.
Transfers
($ million) |
$0
|
$8,896
|
$0
|
($3,557)
|
($1,072)
|
($3,890)
|
12. Welfare
- no benefits measured
($ million) (9+10+11=12)
|
$0
|
($579)
|
($1,041)
|
($711)
|
($1,058)
|
($2,300)
|
13.
Welfare
relative to emissions price |
-
|
1.00
|
1.80
|
1.23
|
1.83
|
3.97
|
Source: Marbek and Resources for the Future.
Note: Figures may not add because of rounding.
* This is 9% of all annual Canadian generation.
4.4 DETAILED RESULTS BY INSTRUMENT
BASE CASE
The base case provides the reference from which the percentage
changes are estimated in Table 6. Renewables penetration is
forecast based on the relative costs of fossil fuel and renewable
generation. Renewables penetration increases over time as
innovation reduces the cost of renewable generation.
Total electricity generation is fixed in both stages in the
base case;3 increased renewables
penetration therefore decreases the carbon intensity of all
generation, from 106 megatonnes/year in the first stage to
101 megatonnes/year in the second stage.
EMISSIONS PRICE
An emissions price works to reduce emissions by reflecting
their cost, either in terms of environmental damages (as with
a carbon tax) 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. Because the price of fossil energy includes
the cost of the carbon associated with that form of generation,
the price of electricity rises. This signals consumers
to reduce their energy use (by, for example, using more energy
efficient appliances). It also increases the price received
by renewable energy producers, encouraging
production and investment in RETs.
-
Consumers face the highest
electricity prices and consumer surplus loss under the emissions
price scenario. Because many consumers are also taxpayers,
the amount of government transfers also affects them.
-
For renewable electricity generators,
the emissions price has a modest but significant impact
on renewable generation, production costs and the producer
surplus. This impact is relatively consistent across both
stages.
-
For fossil fuel electricity generators,
the emissions price is the only instrument with an incentive
to reduce emissions intensity. Although profits for the
fossil sector are not modeled—rather, they are assumed
to be driven to zero in the long run by the market—the
potential costs to the fossil sector of an emissions price
would depend on its ability to pass on to consumers the
production costs increases from carbon abatement (i.e.,
moving from coal to gas), as well as any windfall gains
from being allocated emissions permits.
-
For government, significant
revenue could be raised under the emissions price, either
through a carbon tax or through the allocation or auctioning
of carbon permits under an emissions trading system. This
is the only scenario with the potential for significant
increases in government revenue. 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,
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. Reserving some permits for
allocation to trade-exposed sectors that are electricity
intensive could mitigate this impact.
An advantage of a cap-and-trade system is certainty in reaching
the carbon target; however, uncertainty will then manifest
itself in the price of electricity. All the other instruments
face challenges in setting a policy level that would achieve
the emissions target with certainty.
RENEWABLE PORTFOLIO STANDARD
The RPS requires that total electricity generation include
a minimum share of renewable generation. Although there
are several ways to implement an RPS (e.g., 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, renewable 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 renewable producers is equal to the
total effective tax paid by fossil generators, so no net
revenues are raised or lost by the government.
Since the RPS does not favour any fossil fuel technology,
there is no incentive to reduce emissions intensity in
that sector. Consumer prices rise because of the effective
tax on fossil energy to fund the renewables subsidy (i.e.,
buy green certificates), but not as much as with an emissions
price.
Although more renewable energy is generated under the
RPS than under the emissions price, the timing of that
generation differs. Normally, when prices are fixed renewable
generation expands as costs fall over time. However, the
RPS fixes the renewables share in both periods and over
time this share becomes easier to meet. The effective
tax and subsidy therefore fall (i.e., the price of green
certificates falls) while total electricity generation
increases with the reduced price (the market price is
equal to the price of electricity plus the price of green
certificates, which fall over time as a result of innovation;
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).
-
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 the result of 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, electricity) is higher in the first stage
but lower in the second.
-
For renewable producers,
the RPS increases renewable generation at a uniform
rate in both stages, which is not surprising since the
RPS fixes the share of renewables in both stages. Producer
profits are high. 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,
the share of all generation remains steady in the two
stages; it’s lower than in other scenarios in
the first stage and higher in the second. 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 the sector is not able
to pass along the full costs of green certificates to
consumers.
-
For government, the
RPS has no impact.
-
From society’s perspective,
the welfare costs are greater than under the emissions
price and generation subsidy, but lower than under the
R&D subsidy and the combined RPS and generation
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
could cause economy-wide competitiveness (which could
lead to decreased productivity or reduced exports, for
example). This economy-wide competitiveness would not
be as severe as under the emissions price, particularly
in the second stage of the RPS.
RENEWABLE GENERATION SUBSIDY
This fiscal instrument includes a range of policies that
subsidize renewable generation (e.g., tax credits, direct
subsidies). They do nothing, however, to reduce the emissions
intensity of fossil fuel generation. As well, they have
no impact on the price of electricity; consumers are therefore
not encouraged to reduced demand and, in turn, carbon
emissions. Hence, much more effort must be expended on
higher priced renewables to displace fossil generation
and meet the carbon reduction target.
-
Consumer prices are
not affected because all of the reductions are supplied
through lower renewables costs, which do not affect
the fossil fuel sector directly. Consumers are indirectly
affected because their tax revenue funds a portion of
the subsidy.
-
For renewable producers,
the generation subsidy has the largest impact on profits,
since it encourages the displacement of fossil fuel
generation more than the preceding scenarios. On-going
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
generation as the emissions price, since the additional
renewable generation is partly offset by additional
demand. The decline in fossil fuel generation is slightly
larger in the second stage because innovation dramatically
increases the competitiveness of renewables. That fossil
fuel generation may be lower with the subsidy than with
the emissions price—with no increase in electricity
prices—may seem surprising. However, 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 emissions reduction
target is a significant disbursement.
-
From society’s perspective,
the welfare costs are greater than under the emissions
price, but less than under all other scenarios. There
is more uncertainty, however, that the emissions target
will be met with the generation subsidy than under the
preceding scenarios, for two reasons:
-
The scope and speed of cost reductions
in renewable generation is likely more uncertain
than the cost of abatement in the fossil sector
or the extent of conservation by consumers.
-
Even if all cost uncertainties were
similar, reliance on only one method of emissions
reductions raises the overall uncertainty. In a
broader scenario, if innovation does not lower renewable
generation costs significantly, one could engage
in relatively more emissions abatement or conservation,
whichever turns out to have the lower costs.
There is also uncertainty about the revenue required
to meet the emissions reduction target. If the cost of
renewable generation falls more than expected, a high
subsidy would reduce emissions by more than the target.
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.
A COMBINATION OF RPS AND GENERATION SUBSIDY
Particularly in renewable energy, a combination of policies
is often implemented, partly because of the overlapping
jurisdictions of federal, provincial and local governments,
and perhaps out of a diversification motive. We have estimated
the effects of putting an RPS and a renewable production
subsidy in place simultaneously. The key result is that
the subsidy weakens the effect of the RPS and raises costs
slightly.
With both policies, the fossil fuel producer must still
purchase “green certificates” for every unit
of electricity generated. For the renewable producer,
there are now two subsidies—the value of a green
certificate and the direct subsidy. Because the direct
subsidy boosts renewable generation, the equilibrium price
of a green certificate does not need to be as high to
reach the RPS (as compared with the RPS alone). Consequently,
when the policy target is a portfolio share, a direct
subsidy to renewables primarily offsets the burden to
fossil producers and consumers instead.
Because we assume the RPS drives this scenario, the results
are quite similar to those under 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 generation
is 0.5% higher and R&D spending is 1.5% higher.
-
Fossil fuel generation
is almost exactly the same as under the RSP alone.
-
The government 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 that the subsidy does affect behaviour,
it tends to lower prices and raise 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 under the emissions price.
RENEWABLE R&D SUBSIDY
The renewable R&D subsidy uses current investments
in reducing costs to increase future renewable generation.
Because it does not change any price incentives for demand
or production, nor does it change current costs, all the
burden of emissions reduction is placed on future displacement
of fossil generation 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 of an R&D subsidy alone to
deliver all of this is clearly uncertain.
-
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 revenues that fund the R&D subsidy.
-
For renewable producers,
the second stage of the R&D subsidy induces the
highest increase in renewable generation of all the
scenarios. This increase is driven exclusively by innovation
that decreases the cost of renewable generation. However,
the degree to which Canadian learning by doing and R&D
can drive cost decreases is uncertain. Although such
cost decreases are observed in Canada and internationally,
it is not certain that Canadian R&D alone will decrease
costs enough to increase renewable generation by the
amount predicted in this scenario. One reason for this
uncertainty is that innovation in renewable generation
generally 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 affect electricity prices,
but does significantly reduce fossil fuel generation
in the second stage. Fossil fuel generators could therefore
face costs associated with stranded assets or variable
costs resulting from lower capacity utilization (these
costs are not modelled). 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
all the instruments. That said, promoting innovation
is a government policy and therefore R&D subsidies
are generally part of the desired 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 with
an R&D subsidy.
-
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 general uncertainty about the
success of innovation—particularly domestic innovation—it
is highly uncertain that a domestic R&D program alone
could significantly reduce CO2 emissions by
increasing renewable generation. 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.
4.5 SENSITIVITY ANALYSIS
To further test the robustness of the results, a sensitivity
analysis was conducted with respect to the following:
-
An increase in the baseline
electricity price. 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. This price differential
also affects the desirability of an RPS versus a renewable
generation subsidy. 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.
-
An increase in the baseline
price of natural gas. The sensitivity results
indicate that increasing natural gas prices have a minimal
impact on the results. Increasing gas prices could,
however, increase the price of electricity.
THE SENSITIVITY TESTING CONCLUDES THAT THE RESULTS ARE
ROBUST TO CHANGING KEY VARIABLE ASSUMPTIONS. INDEED,
OUR CORE OBSERVATION HOLDS: THE ECONOMIC EFFICIENCY
AND ENVIRONMENTAL EFFECTIVENESS OF THE FISCAL INSTRUMENTS
IS LINKED TO THEIR ABILITY TO INFLUENCE THE ENTIRE ELECTRICITY
MARKET AND THE THREE DECARBONISING DRIVERS IN PARTICULAR.
A FISCAL INSTRUMENT WILL GENERALLY BE MORE EFFICIENT
AND EFFECTIVE IF IT SIGNALS TO MULTIPLE AGENTS IN THE
ELECTRICITY MARKET THAT CARBON IS MORE EXPENSIVE: FOSSIL
FUEL PRODUCERS WILL REDUCE THEIR EMISSIONS INTENSITY,
RENEWABLE PRODUCERS WILL PRODUCE MORE WHEN THE PRICE
DIFFERENTIAL BETWEEN RENEWABLE GENERATION AND FOSSIL
FUEL GENERATION DECREASES, AND CONSUMERS WILL CONSERVE.
THIS FINDING HOLDS UNDER MULTIPLE INPUT ASSUMPTIONS
AND EXPLAINS WHY AN EMISSION PRICE IS PREFERABLE TO
AN RPS OR RENEWABLE GENERATION SUBSIDY [AND TO THE COMBO
AND R&D SUBSIDY?]. A GOOD EXAMPLE OF THE INCREASED
RISK IN USING A SINGLE INSTRUMENT IS HIGHLIGHTED BY
THE R&D SCENARIO, IN WHICH THE REDUCTION OF EMISSIONS
RELIES ENTIRELY ON THE ABILITY OF DOMESTIC R&D INVESTMENTS
TO PRODUCE INNOVATION THAT REDUCES THE COST OF RENEWABLE
GENERATION. ALTHOUGH R&D SPENDING IS EXPECTED TO
REDUCE THE COST OF RENEWABLE GENERATION, THERE IS UNCERTAINTY
ABOUT THE SCOPE OF THE REDUCTIONS AND THEREFORE THE
EFFECTIVENESS OF THE FISCAL INSTRUMENT.
Notes
1 It is widely recognized
that issues related to grid access, grid capacity and the costs
of grid extension will be particularly influential in determining
the practical potential of grid-power RETs. While these issues
are beginning to be addressed in some regions, they are far from
being resolved at this time. Further consideration of these issues
is well beyond the scope of this case study.
2 While it is not strictly
true that fossil fuel technologies will experience no technological
advance, incorporating a rate of advance in the model would complicate
the analysis without adding substantial insight.
3 It is recognized that electrical production
is increasing over time, but total electricity generation in the
model is fixed in both stages so that the effects of the instruments
on demand and supply can be better understood.
|
|