the magnitude of the impact of a shift from coal to gas under a
TRANSCRIPT
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The magnitude of the impact of a shift from
coal to gas under a Carbon Price
Liam Wagner1, Lynette Molyneaux, John Foster
Energy Economics and Management Group, School of Economics, University of Queensland, Australia
Abstract
We seek to evaluate the extent of the pass through of increased fuel and carbon costs
to wholesale prices with a shift of generation from coal-fired to gas-fired plants.
Modelling of Australia’s National Electricity Market in 2035 is undertaken using Australian
Energy Market Operator assumptions for fuel costs, capital costs and demand forecasts.
An electricity market simulation package (PLEXOS), which uses deterministic linear
programming techniques and transmission and generating plant data, is used to optimise
the power system and determine the least cost dispatch of generating resources to meet
a given demand. We find that wholesale market prices increase due to the full pass
through of the increased costs of gas over coal as an input fuel and the Carbon Price. In
addition, we find that wholesale prices increase by more than the pass through of fuel
and carbon costs because of the fact that generators can charge infra-marginal rents and
engage in strategic behaviour to maximize their profits.
Keywords: Electricity, markets, infra-marginal rent
JEL Classification Codes: Q41, Q47, C61
1. Introduction
The International Energy Agency (IEA) in its modelling of global energy demand and
supply to 2035 predicts “a pronounced shift away from oil and coal (and, in some
countries, nuclear) towards natural gas and renewables” (IEA, 2012, p. 23). This view is
1 Corresponding author. Address: Energy Economics and Management Group, School of Economics,
University of Queensland, St Lucia, Brisbane, 4072, Australia. Tel: +61 7 3365 6601 Email addresses: [email protected], [email protected], [email protected]
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supported by the recent development of shale gas resources in the United States that has
delivered low gas prices and shifted electricity generation from coal to gas resulting in
generation from gas increasing from 24% in 2010 to 31% in 2012 (EIA, 2013a). However,
as the Energy Information Administration (EIA) points out, “In deciding whether to
dispatch coal or natural gas for electricity, the price of fuel is critical” (EIA, 2013b), such
that increases in gas prices in 2013 have reversed some of the recent trend towards gas.
Notwithstanding the short-term perturbations currently resulting in fuel switching in
the United States, the IEA forecasts that the real price for gas in the US will rise to
$8/MBtu by 2035 because “as demand grows in response to lower prices, costs rise and
export capacity is built.”(IEA, 2012 , P43-44)
Thus with the IEA proposing a global shift from coal to gas, national power systems
are likely to experience cost increases as a result of the shift to a fuel forecast to be more
expensive than coal. This shift is justified by a carbon dioxide (CO2) emission abatement
strategy, facilitated by the introduction of a Carbon Price. Consumers will therefore be
subjected to a cost increase from changing fuel source as well as the introduction of a
Carbon Price.
However, most national power systems will not be able to fund a large scale turnover
of the generation fleet within two decades, so there will continue to be competition
between generators using different fuel sources. We sought therefore to understand how
much of the increased costs of generation would be passed through to consumers in
wholesale prices if generators with different fuel sources were competing to meet
demand.
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In general, increased prices encourage customers to seek substitutes. Electricity
however presents certain challenges to this axiom. Traditionally electricity has been:
• subjected to sustained growth due to pull factors like increased electrification
of household goods,
• supplied from centralised sources,
• distributed to customers through a monopolistic network, and
• demand inelastic because substitutes are either non-existent, involve
substantial investment or are considerably more expensive.
Thus electricity consumers have few options other than to pay the increased cost or
reduce consumption. This is supported by the findings that more than 100% of the
Carbon Price (opportunity cost) was passed through to consumers in the first phase of the
European Union’s Emission Trading Scheme (EU ETS) (Keppler & Cruciani, 2010). Nanduri
and Kazemzadeh, in their bi-level game-theoretic modelling approach to CO2 emissions
permit’s and electricity market interactions, also found a sizable impact on prices as a
result of Carbon Prices, with wide variations in price and increasing cost pass-through as
emissions caps become more stringent (Nanduri & Kazemzadeh, 2012). Therefore we
expected that the full costs associated with higher fuel costs and CO2 costs would be
passed through to consumers.
But, a shift to gas and implementing a Carbon Price are highly contentious issues since
the price of electricity not only impacts on countries’ industrial competitiveness, but also
on the welfare of its people. For countries, like Australia, which are heavily reliant on
cheap coal to power their electricity system, a shift to gas and the introduction of a
Carbon Price has substantial cost implications for the price of electricity. In this paper, we
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seek to evaluate how much of the increased costs associated with the shift to gas and the
introduction of a Carbon Price are passed through to consumers by modelling Australia’s
National Electricity Market (NEM) response to a substantial change in generation two
decades into the future in 2035. The scenarios modelled are: the impact of a shift to gas
in 2035 with no Carbon Price; a shift to gas with the Australian Treasury’s high Carbon
Price projection to avoid CO2concentrations from exceeding 450ppm; and a shift to gas
with the Australian Treasury’s mid-range Carbon Price projection as the expected
scenario. We then compare the average wholesale (Spot) price for the 3 different
scenarios to assess the costs passed through, subject to the competitive behaviour of the
generators experiencing substantial cost increases.
The paper is organized as follows: Section 2 presents the modelling environment;
Section 3 presents the results from the modelling; Section 4 discusses the results; and in
Section 5 we provide some concluding remarks.
2. Modelling Australia’s National Electricity Market in 2035
Australia’s National Electricity Market (NEM) represents more than 80% of Australia’s
power system and provides power to the states of New South Wales, Victoria, South
Australia, Queensland, and via high voltage direct current link, to Tasmania. In 2010, the
NEM comprised 48.8 GW of capacity of which 28GW was coal-fired, 10GW gas-fired, 7GW
hydro-electric and 2GW of wind power. Together these plant generated 215TWh of
energy, 80% of which was from coal. Emissions from the operation of the NEM, is
calculated to be 182.7mtpaCO2, or 0.923 kgCO2 per MWh (sent-out).
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It is assumed that existing plant is retired based on its technical lifespan with the
remaining plant participating in the market in 2035. Investment in generation is targeted
on gas-fired plant to meet increased demand and replace retired coal-fired generators.
Investment in wind power is based on reaching the country’s 2020 target of 20% of
generation from renewable sources which would result in deployment of 12GW of wind
power by 2020. Deployment of new plant in the NEM is calculated based on demand, fuel
and capital cost projections by the Australian Energy Market Operator (AEMO).
Significantly, domestic gas prices are forecast to increase to $8/GJ by 2035 as a result of
the investment in liquefied natural gas (LNG) facilities to gain access to lucrative
international markets.
Three scenarios were considered: a no Carbon Price scenario (Scenario A); a Carbon
Price as projected by the Australian Treasury to be the Carbon Price by 2035 if the
concentration of CO2 in the atmosphere is to be limited to 450 parts per million (Scenario
B); and a Carbon Price as projected by the Australian Treasury to be the likely Carbon
Price by 2035 (Scenario C);.
The modelling was conducted using PLEXOS, a commercially available optimization
theory based electricity market simulation platform. At its core is the implementation of
rigorous operation algorithms and tools such as Linear Programming (LP) and Mixed
Integer Programming (MIP). PLEXOS takes advantage of these tools in combination with
an extensive input database of regional demand forecasts, inter-regional transmission
constraints and generating plant technical data to produce price, generator and demand
forecasts to replicate the SPD (scheduling, pricing and dispatch) engine used by AEMO to
operate the NEM. PLEXOS simulates generator behaviour, such that generators
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participate in the market if they can cover costs and make a profit. Spot price projections
represent generator behaviour and cost recovery, rather than just the latter (Energy
Exemplar, 2012). PLEXOS is a mature, respected modelling package and has been used in
similar modelling-related research, including modelling the impact of electric vehicles on
Ireland’s electricity market (Foley, Tyther, Calnan, & Gallachóir). Denny and O’Malley
found that PLEXOS has given highly accurate predictions of prices and as a result have
used PLEXOS to model market behaviour with the introduction of Carbon Prices(Denny &
O'Malley, 2009).
Therefore, PLEXOS was chosen over other modelling platforms because: it focuses on
optimization to predict generator behaviour; it is currently used in live situations to
predict future wholesale prices in Ireland, Australia and the United States; and the
platform is populated with Australia’s NEM data to enable robust modelling of the NEM.
2.1. A shift to gas (Scenario A)
AEMO’s demand projections from 2010 assume that demand returns to long-term
growth trends and recent reductions in electricity demand in 2011 and 2012 are a short-
term adjustment rather than a long-term trend. Thus, according to AEMO, energy
generated is expected to grow from 215TWh in 2010 to 324TWh in 2035. Scenario A, the
shift to gas in the absence of a Carbon Price, is modelled for two reasons. Firstly, it
recognizes that investing in coal-fired generation to replace retired coal-fired generation
and meet increased demand has substantial risks associated with emissions if it is not
possible to sequester and store CO2, and secondly it establishes the impact of increased
marginal costs associated with gas-fired generation over coal-fired generation.
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The modelling predicts that there would be a 16% decrease in coal-fired generation
and a 4-fold increase in gas-fired generation to replace retired plant and meet increased
demand. This increase in gas-fired generation requires investment in 25 GW of combined
cycle (CCGT) and 3 GW of open cycle gas turbines (OCGT). An investment in 12GW of
wind power is also forecast to meet the Renewable Energy Target (RET) by 2020. By 2035,
coal-fired generation from existing plant would have declined to 44% and gas-fired
generation would have increased to 39%. So the shift to gas, as forecast, is achievable.
Electricity spot prices respond to this new paradigm by increasing from $35/MWh in
2010 to $73/MWh in 2035. What are the underlying changes that contribute to this 108%
increase in the Spot price? First, let’s start with fuel cost. As can be seen in Table 1, there
is a doubling of the cost of fuel used in power generation.
Table 1: Impact of switch to gas on fuel cost
Fuel Use
(PJ)
Fuel use/MWh
(GJ/MWh)
Fuel cost
($m)
Cost/MWh
($/MWh)
2010 (Estimated) 1985 10.35 $2600 $13.55 2035 Scenario A 2368 7.59 $9370 $30.04 Sources: (ACIL Tasman, 2009; AEMO, 2011; ESAA, 2011)
Coal, as a fuel, is a cheap source of energy in Australia. Black coal for electricity
generation in Queensland and New South Wales comes at a cost of approximately
$14.50/MWh and brown coal in Victoria costs around $6.50/MWh, whereas our
calculations of current generation costs suggest that gas costs around $36/MWh.
Thus, of the $38/MWh increase in Spot price, $16.49 is a result of the higher cost of
gas. It can therefore be safely assumed that the increased costs associated with gas are
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passed on in full. There are however other costs which are passed through which need to
be examined.
The report to the DG Environment of the European Commission, highlighted factors
other than generation costs that influence electricity pricing, namely: market strategy to
pursue higher revenue levels; response to institutional factors like regulation or allocation
plans; and market imperfections which highlight risks and uncertainties. Market strategies
are particularly pertinent because wholesale electricity markets are structured to allow
different technologies with widely differing marginal costs to operate together to provide
an undifferentiated product. Market supply bids are accepted to meet a varying level of
demand such that the marginal cost of the last supplier to meet the requisite demand
sets the price for all producers at that demand. So when demand is low, supply from only
the lowest marginal cost producers is accepted to meet demand. When demand surges,
supply is accepted from higher marginal cost producers thus increasing the price paid to
all producers supplying power at that level of demand. The infra-marginal producers
therefore benefit from the price set by the higher marginal cost producers. The authors
concluded that infra-marginal, less CO2 intensive plant operators may well continue to
enjoy windfall profits from the introduction of Carbon Prices due to the unusual structure
of wholesale electricity markets (Sijm, Hers, Lise, & Wetzelaer, 2008).
To understand the impact of infra-marginal rents on the Spot price of electricity, we
sought to separate out generators that are structured to operate as ‘baseload’
(generators that operate all day every day subject to operational constraints) and
‘varload’ (generators that can operate flexibly to meet peaks in demand). In the main it is
neither cost-effective nor, in many cases, technically possible for ‘baseload’ generators to
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supply electricity flexibly. Their bidding strategy in the electricity market is therefore
focused on earning income from continued long-term operation rather than response to
short-term demand and supply conditions. In the NEM, baseload generators have
traditionally supplied more than 75% of the NEM’s electricity and their response to
baseload demand and supply underpins the weighted average Spot price of electricity.
Two examples of change in the baseload fleet highlight the impact of baseload
generators on Spot price. In late 2002 and early 2003, 2.5GW of capacity was
commissioned in the NEM, of which 1.7GW was baseload capacity in Queensland. The
commissioning of these baseload generators created surplus capacity, with the result that
the weighted average Spot price across the NEM slumped from $44/MWh in 2002 to
$27/MWh in 2003, a 39% reduction in price. The impact in Queensland was even greater
with weighted average Spot price reducing from $52/MWh in 2002 to $24/MWh in 2003,
a 54% decline. Then in 2007, as a result of severe drought in Queensland, water for
Queensland generators was restricted, which constrained 1.3GW of baseload power to
the NEM. Wholesale electricity prices responded to this constraint by increasing from a
weighted average Spot price of $35/MWh in 2006 to $72/MWh in 2007, returning to
$48/MWh in 2008 after the arrival of rains and the lifting of water restrictions on
Queensland generators.
Thus to understand the pricing motives for baseload generators, analysis of historic
and future costs is necessary. To calculate short run marginal cost (SRMC) and long run
marginal cost (LRMC) for energy generated in 2010, fuel, variable operating and
maintenance (vom) and fixed operating (fom) costs (excluding financing) are drawn from
ACIL Tasman (ACIL Tasman, 2009) and AEMO’s Statement of Opportunities 2011 (AEMO,
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2011). The weighted average SRMC for baseload in 2010 is calculated to be $14.17 which
points to a coal-fired power station as the marginal generator, ie the generator that sets
the price for baseload. Figure 1 shows the breakdown in costs as estimated.
To calculate SRMC and LRMC for energy in 2035, AEMO’s assumptions of projected
costs are used. If coal-fired power stations are retired and cease to be the baseload price
makers, then a gas-fired power station will become the marginal baseload generator, and
the SRMC of an average combined cycle gas turbine would be approximately $32/MWh at
current gas-prices, and $66/MWh at forecast gas prices; that is an $18/MWh increase in
the price of baseload power at current gas prices, and a $52/MWh at forecast gas prices.
In 2035 Scenario A, baseload energy generated is 242,034 GWh with 119,730GWh
modelled to be dispatched from coal-fired power stations. Applying a $52/MWh price
boost to the coal-fired generators would deliver an additional $6.3 billion profit to the
coal-fired generators as a result of gas-fired generation being the marginal cost
Figure 1: Historic breakdown of components of Spot Price
$0.00
$10.00
$20.00
$30.00
$40.00
$50.00
$60.00
$70.00
2007 2008 2009 2010
No
min
al
$/M
Wh
Baseload fuel cost Baseload carbon cost
Baseload Other operating costs Varload LRMC
Industry Margin
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generator. Distributing the profit windfall, or infra-marginal rent to coal-fired generators,
across all energy delivered in 2035, pushes the average Spot price up by $19.95/MWh.
Therefore adding $16.49 fuel cost to $19.95 infra-marginal rent, increases the
average cost by $36.44/MWh which largely explains the increase in average Spot price of
$38/MWh. Thus, not only do fuel costs double and get passed through to consumers, but
the way that the equilibrium price of energy is calculated, leads to a windfall for coal-fired
generators. Figure 2 shows the changes involved in the make-up of the new average Spot
price.
The impact of wind power, with its higher levelised cos,t is not material since wind
generation, with its very low SRMC and relatively small proportion of electricity
generated, ensures that is not a price setter in the market.
Emissions from power generation in the NEM in 2010 were 183 million tons per
annum of CO2 (mtpaCO2). With this shift to gas, emissions are projected to decrease to
Figure 2: Breakdown of components of Spot price after a shift to gas with no carbon price
$0.00
$10.00
$20.00
$30.00
$40.00
$50.00
$60.00
$70.00
$80.00
2010 2035 (A)
Re
al
$/M
Wh
Baseload fuel cost Baseload carbon cost
Baseload Other operating costs Varload LRMC
Inframarginal rent to baseload Industry Margin
12
174 mtpaCO2 in 2035.This is a mere 5% decrease in emissions, due to the increased
generation required to meet higher levels of demand. The shift to gas therefore does not
ensure that the NEM will even begin to approach an abatement target of 32 mtpaCO2 by
2050.
In short, the shift to gas increases the Spot price of power because the higher fuel
costs and Carbon Price are passed through in full as well as the infra-marginal rents that
are enjoyed by low marginal cost generators because of the market price settlement
process. This higher price of power, however, does not reduce emissions in the NEM and
increases uncertainty due to the risks associated with global energy price volatility.
2.2. Mitigating against climate change: a shift to a high
Carbon Price (Scenario B)
In theory, the internalization of CO2 costs provides an incentive for lower CO2 emitting
generators to operate whilst discouraging the higher CO2 emitting generators. For this
reason Australia has introduced Carbon Price legislation that became effective in 1 July
2012. In the event that global action is motivated towards limiting the impact of high
concentrations of CO2 in the atmosphere, the Australian Treasury predicts that the
Carbon Price could increase to $159 per tCO2 by 2035. In modeling this scenario, the
assumptions made in Scenario A with respect to demand, capital investment and input
costs were unchanged. The high Carbon Price set in Scenario B facilitates a substantial
shift away from coal-fired to gas-fired generation of 70TWh compared to Scenario A. This
shift from coal to gas requires only small changes to the investment required in Scenario
A but increases the cost of fuel for generation for the NEM by $4.8bn. The higher Carbon
Price additionally increases the overall cost of generation for the NEM by $22.7bn
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compared to no Carbon Price scenario. Thus a total of $27.5bn would have to be
recovered, compared to Scenario A due to additional costs. This suggests that a minimum
pass through of $88/MWh, over and above Scenario A, could be expected.
Table 2: The shift to high Carbon Price
Fuel Use
(PJ)
Fuel
use/MWh
(GJ/MWh)
Fuel cost
($m)
Cost/MWh
($/MWh)
mtCO2 Carbon
cost
($m)
2035 Scenario
A
2368 7.59 $9,370 $30.04 174.2 $0
2035
Scenario B
2173 6.97 $14,155 $45.39 129.7 $22,700
Sources: (ACIL Tasman, 2009; AEMO, 2011; ESAA, 2011)
The model predicts that the weighted average Spot price will increase to $188/MWh.
This weighted average Spot price is $115/MWh higher than the no Carbon Price scenario.
Thus, of the $115/MWh increase in Spot price, $15.35 is as a result of the cost of fuel and
$72.78 is as a result of the cost of CO2. It can therefore be safely assumed that the
increased costs associated with gas and CO2 are passed on in full. But that doesn’t explain
the further $26.87 that has been passed through to wholesale price.
In 2035 Scenario C, baseload energy generated is modelled to be 240,219 GWh with
47,791GWh dispatched from coal-fired and 192,428 dispatched from gas-fired power
stations. However, the marginal generator shifts from being a gas-fired generator in
Scenario A to the least efficient of the remaining coal-fired generators in Scenario B. The
SRMC of generating gas-fired baseload power is $134.82/MWh whilst the SRMC of
generating coal-fired baseload power of the least efficient coal-fired power station is
$181.17/MWh, a difference of $46.35/MWh. Applying this $46.35/MWh price boost to
the gas-fired generators delivers an additional $8.9 billion profit to the gas-fired
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generators as a result of coal-fired generation being the marginal cost generator.
Distributing the infra-marginal rent across all energy delivered in 2035, pushes the Spot
price up by $28.60/MWh.
A SRMC of $181/MWh is high enough to encourage the deployment of some
renewable generation, but our assumption is that resistance to deployment of
renewables due to problems perceived with intermittency will lead to low fuel cost but
high CO2 emitting generators remaining prominent even with a high Carbon Price.
Therefore, adding $15.35 fuel cost to $72.78 CO2 cost and $28.60 infra-marginal rent,
increases the total cost by $116.73/MWh which explains the increase in weighted
average Spot price. Thus, not only do fuel and CO2 costs get passed through to
consumers, but the way that the equilibrium price of energy is calculated, leads to a
windfall for gas-fired baseload generators.
Figure 3: Breakdown of components of Spot price with a high carbon price
$0.00
$50.00
$100.00
$150.00
$200.00
2035 (A) 2035 (B)
Re
al
$/M
Wh
Baseload fuel cost Baseload carbon cost
Baseload Other operating costs Varload LRMC
Inframarginal rent to baseload Industry Margin
15
With a high Carbon Price, emissions decrease to 129.7 mtpaCO2 which is closer to the
goal of 32 mtpaCO2 although still not readily achievable, even with very high electricity
prices.
2.3. A measured shift to a Carbon Price (Scenario C)
Projections for the Carbon Price are provided by Australian Treasury and it is forecast
that the most likely Carbon Price will be at approximately $74 per tCO2 in 2035
(Australian Government, 2011). Exactly the same demand, capital investment and costs as
Scenario A are assumed, such that all conditions facing the generators are identical,
except that their input costs change by the amount of the Carbon Price.
The modelling predicts that 7TWh would shift from coal to gas generation as a result
of the Carbon Price. This requires only small adjustments to investment to meet demand
compared to Scenario A. Carbon cost would add $13.5 billion to the generation cost bill,
so there would be an expectation for a pass-through of around $43/MWh. Table 2 shows
the changes in generation cost comparing Scenario A to Scenario C.
Attempting to cover these costs, the model predicts that generators will bid such that
the weighted average Spot price increases from $73/MWh without a Carbon Price to
$154/MWh, an increase of $81/MWh.
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Table 3: The shift to a high Carbon Price
If we look to the costs associated with increased gas-fired generation, we find that gas
increases costs by $2/MWh and the Carbon Price increases costs by $43.38/MWh. This
fuel and CO2 cost explain $45/MWh wholesale price increase which confirms that the
costs are passed on in full, but there is still a gap of$36/MWh to the average price as bid.
Examining the infra-marginal rents accruing shows that the marginal baseload
generator is a combined cycle gas-fired generator with a SRMC of $110/MWh as opposed
to the average SRMC for coal fired generators of $81.75/MWh. This gap of $28.25/MWh
is applied to 114,438GWh of coal-fired baseload generation, providing a windfall gain of
$3.2 billion to coal-fired generators. This equates to $10.35/MWh for infra-marginal rents
which falls short of the increase in weighted average Spot price.
On further analysis of the demand and price bids, Scenario C showed considerable
evidence of volatility. Historical actual annual standard deviation in Spot price from 2000
to 2010 ranged between $81.63 and $194.27/MWh (the highest annual average Spot
price was in 2007 when Queensland generators were constrained by water shortages) on
annual mean Spot prices of between $24.72 and $65.50/MWh. When modelling the
market response in 2035, Scenario A showed an annual standard deviation in Spot price
Fuel Use
(PJ)
Fuel
use/MWh
(GJ/MWh)
Fuel cost
($m)
Cost/MWh
($/MWh)
mtCO2 Carbon
cost
($m)
2035 Scenario
A
2368 7.59 $9,370 $30.04 174.2 $0
2035
Scenario C
2372 7.59 $9,999 $32.02 166.9 $13,548
Sources: (ACIL Tasman, 2009; AEMO, 2011; ESAA, 2011)
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of $17.69 on annual mean Spot price of $78.10/MWh. However, modelling for Scenario C
shows an annual standard deviation on Spot price of $642.73. This volatility is clustered
around 8 distinct events where prices surged for between 13 and 18 hours, in different
groups of states. We assume that PLEXOS calculated that one or more generators would
fail to bid where margins were too low, resulting in a reduction in supply and significant
volatility which would drive up Spot price and baseload margins. We tested this
assumption by removing the Spot prices for the 8 distinct events and replacing them with
pricing for the same day and time from a week after each event. This adjustment caused
the standard deviation to drop to $138.14 on a mean Spot of $90.04. However, a
weighted average Spot price of $90 would result in baseload gas-fired generators
operating at a gross loss (i.e. LRMC greater than Revenue) and coal-fired generators
would be operating at no margin at all (i.e. LRMC equal to Revenue).
We therefore concluded that generators are compelled to introduce volatility into
bidding behaviour when profits are too low to sustain baseload generator margin. So,
whilst the infra-marginal rent is in effect producer surplus, this surplus creates market
stability. Where the infra-marginal rent is too low, there is an inherent incentive for
Figure 4: Breakdown of components of Spot price with a mid-range carbon price
$0.00
$20.00
$40.00
$60.00
$80.00
$100.00
$120.00
$140.00
$160.00
$180.00
2035 (A) 2035 (C)
Re
al
$/M
Wh
Baseload fuel cost Baseload carbon cost
Baseload Other operating costs Varload LRMC
Inframarginal rent to baseload Industry Margin
18
generators to find a way to create volatility to drive prices up to make a profit. Figure 4
provides detail of the contribution of costs to Spot price under a mid-range carbon price.
As with Scenario A, there is no evidence that wind power has a material impact on the
average Spot price.
So, whilst the increased costs associated with gas and Carbon Price are passed
through in full, generators need to engage in strategic behaviour to operate at acceptable
margins. Emissions decrease from 174 mtpaCO2 in Scenario A to 167 mtpaCO2 in Scenario
C, indicating a very small improvement in abatement as a result of the shift to a Carbon
Price. This would suggest that even the introduction of a mid-range Carbon Price and
substantially higher electricity wholesale prices would not achieve the desired abatement
goal.
3. Discussion
Over the decades, there has been considerable discussion around modelling and
forecasting energy prices under uncertainty. Pindyck looked to model and forecast energy
prices to assist with the strategic planning of investment under uncertainty (Pindyck,
1999) and, more recently, Tolis et al and Garcia-Martos et al (Garcia-Martos, Rodriguez, &
Sanchez, 2013; Tolis & Rentizelas, 2011) modelled electricity prices based on multiple
uncertainties. In general, modelling has sought to draw out the impact of increasing input
costs and uncertainty based on the historic behaviour of changes to a relatively stable
fleet but in this paper we have examined the impact of very large increases in cost, and
associated upheaval in the generation fleet, on bidding behaviour in the future.
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The performance of electricity prices after the introduction of the EU ETS is a
predictor of how electricity prices elsewhere have reacted to the introduction of
substantial increased costs such as a Carbon Price. Whilst CO2 allowances were provided
free to power generators in Phase 1 of the scheme, the opportunity cost of the
allowances was passed through to consumers resulting in significant increases in power
prices in the EU. This was generally seen to be evidence of a Carbon Price working as
designed, but it raises the question of how infra-marginal rents impact upon the
operation of the electricity market. Our modeling, however, indicated that infra-marginal
rents provide a stabilizing effect on market participants because, when infra-marginal
rents reduce substantially, volatility is required to recover costs and produce an
acceptable profit margin. Thus, it provides evidence that generators bid strategically and
do not price only on a cost pass-through basis.
Keppler and Cruciani undertook an analysis of infra-marginal rents earned by
generators during the EU ETS in Phase 1. They assessed the infra-marginal rents to be of
the order of Eur 5.5bn and extended the analysis to predict the impact of infra-marginal
rents in Phase 3 of the EU ETS and found that it was likely to increase to Eur 10bn
(Keppler & Cruciani, 2010). So, the findings of Sjim et al and Keppler and Cruciani both
support our findings that increases to marginal producers’ costs increases the income
earned by the producers as a whole more than just the increase in marginal costs.
To what extent is it realistic to suppose that generators engage in strategic behaviour
when there are substantial changes to cost structures or when the marginal cost pricing
mechanism fails to deliver sufficient profit to baseload generators? Wholesale electricity
markets, and especially the baseload generators, have an oligopolistic structure because
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of the limited number of suppliers, long construction periods for power plants, and large
capital investment requirements (Li, Shi, & Qu, 2011), so it is to be expected that
generators will seek to use market power to manipulate market price to do more than
simply cover costs.
To get an overview of whether generators are earning sufficient to cover costs, the
analysis in Table 4 compares the relationship between weighted average LRMC and
weighted average Spot price over the three scenarios modelled. It is reasonable to
exclude wind from the comparison for two reasons, namely: the SRMC of wind is $0 and
is not involved in price setting; and energy generated from wind in 2010 was a small
percentage whereas that percentage increases in our projections to 2035, so it is
important for that not to allow this to distort the analysis. Table 4 provides an indication
of the current cost/revenue levels, compared to the levels modelled in 2035.
Table 4: Proportion of cost of non-wind generation
Fuel cost
/ MWh
Carbon
cost
/ MWh
SRMC /
MWh
LRMC /
MWh
Spot / MWh LRMC % of
price
2010
Estimated
$13.54 $0 $15.16 $25.28 $35 72%
2035 Scen A
excl Wind
$34.23 $0 $35.55 $43.92 $71 62%
2035 Scen B
excl Wind
$51.72 $82.94 $136.26 $145.27 $190 76%
2035 Scen C
excl Wind
$36.482 $49.42 $87.40 $96.30 $154 63%
What is noticeable is that the estimate of costs in 2010 shows a high proportion of
long run marginal cost in the weighted average Spot price, suggesting that profit margins
were relatively low in 2010. An analysis of New South Wales and Queensland baseload
21
generator company statements reveals that the companies were indeed facing very
reduced profit levels. The Macquarie Generation Chairman and Chief Executive Report
best describes much of the commentary to be found in generator company Annual
Reports
“..conditions have muted the wholesale electricity market, therefore reducing volatility
and limiting high price opportunities for generators.”(Macquarie Generation, 2011)
To sustain a robust industry, it is therefore logical to see in our modelling that 2035
profit levels are better than are currently enjoyed by baseload generators. What we see
in Scenario A and C, the no Carbon Price and mid-range Carbon Price scenarios, is a better
profit margin for generators as a result of infra-marginal rents.. Scenario B shows smaller
profit rates as a result of the introduction of a very high Carbon Price. This suggests that
relatively high cost coal-fired ‘baseload’ generators would exit the market because of low
or no profit levels, requiring a greater investment in gas-fired generation to meet
demand. Coal-fired generators exiting the market because of a high Carbon Price and
reduced profit levels is entirely predictable but what underlies the shift to a large fleet of
gas-fired generators with very similar cost structures, is the incentive to introduce
volatility to increase profit levels, as observed in the modelling of Scenario C. So, given
that Scenario C may be closest to what will eventuate, volatility in price, and associated
increases in costs to consumers, could well become the norm when baseload power is
delivered by gas-fired generators.
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4. Conclusion
Our analysis reports the results of modelling Australia’s National Electricity Market
using the sophisticated PLEXOS platform which found that the effect of a shift away from
coal to gas-fired generation is only small reduction in emissions, at a large price tag. In
fact the modelling suggests that all costs associated with fuel price increases and the
introduction of a Carbon Price will be passed on in full to consumers. In addition, the
oligopolistic structure of the market allows baseload generators to earn infra-marginal
rents to provide them with adequate levels of profit. Where competition is too fierce,
such that there is an absence of infra-marginal rents it is rational for baseload generators
to induce price volatility into the electricity market to enjoy healthy profit margins.
Whatever drives bidding behaviour, consumers are likely to face a substantial
electricity price increase as a result of a significant shift to gas-fired generation. This
suggests that policymakers should exercise caution in promoting a policy that employs
gas as a ‘transitional’ fuel for power generation.
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