Pricing Elements - AESO · Pricing Elements in the Energy Market ... • Under a capacity market...
Transcript of Pricing Elements - AESO · Pricing Elements in the Energy Market ... • Under a capacity market...
Pricing Elements in the Energy Market
• Should offers into the energy market be mitigated to cost? – Measuring market power (structure) – Determining which offers? (screens) – Determining type of cost mitigation – Impact on pricing
• Consider price cap / floor
• Shortage pricing
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WG 8
WG 9
Pricing Elements
Component Options Approach Structure Concentration Level
- FEOC reg set at 30% Hold constant
Screens Screens for ability to exercise market power ((based on current asset concentration)
Examine options for screens - Structural screens / RSI - Conduct & Impact - Self evaluation
Offer Mitigation Administrative Levels or Market Based
Examine acceptable costs and options for offer mitigation - SRMC + buffer - Ex ante audit - Soft cap option
Pricing Rules associated with pricing - Price Cap / floor - Shortage pricing - Others – dispatch
tolerance, settlement, etc
Conduct pricing impact analysis - Test for impact on pricing
based on fleet - Examine pricing options as
required
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Market Power in Alberta
• Under a capacity market framework, competition in the energy market should drive offers to short-run marginal cost (SRMC)
• Conditions exist in AB that hinder competitive outcome: – Small market – Highly concentrated
• Partly mitigated by market share concentration in FEOC reg (30%) – With introduction of capacity market want to ensure that offers
are tested for market power, then mitigated as required to account for separate capacity payment
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Use of Screens
• To assess which participants have an ability / incentive to exercise market power – Create a screen to test for market power
• If pass screen, offers not mitigated
• If fail screen, offers mitigated
• All energy delivered paid at system marginal price, this simply addresses offer mitigation not payment
• Options – Structural screen – test for pivotal supplier
• Pivotal supplier tests (single and three-pivotal suppler tests)
• Residual supplier Index
– Conduct & Impact Test – Self monitor and evaluate
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Measures to test competitiveness
• Herfindahl-Hirschman index (HHI) – Measure of market competitiveness using size of firm as input – Equals sum of squares of all firms market share, expressed as a
percentage ranging from 0 to 10 000 (monopoly = 100% x 100%) – More weight to larger firms
• Residual supplier indices – test for pivotal suppliers – Is the firm (plus the next two, for a three-pivotal supplier) needed
to meet demand for that hour? • Want to ensure test for risk of market power without overstating issue
• Three pivotal supplier test in Alberta likely too onerous
• RSI test at some threshold less than 1 more applicable
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Testing for residual supply/pivotal supply
• A common test for competitiveness of a market is a residual supply or test of pivotal supply where by for every hour, the residual supply for firm (i) is:
• This method tests for the potential for a firm to exercise market power by withholding all (RSIi ≥ 1) or a portion (RSIi < 1) of their capacity.
• Applying the test to a firm for every hour yields a duration curve that illustrates the portion of hours that a firms aggregate supply (across all assets) is needed to meet demand.
• Using a threshold of less than 1 focuses on the key hours when the exercise of market power can be a concern.
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𝑅𝑅𝑅𝑅𝑅𝑅𝑖𝑖 =∑𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 − 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑖𝑖
𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑
Testing for residual supply/pivotal supply (continued)
• Variations of these tests can be applied to determine the residual supply of a single firm or multiple firms (e.g., a three-pivotal supplier test). – As more firms are added to the test, results in a greater
instances of “failing” – Adding more firms serves the purpose of assessing oligopolistic
market power (i.e., the potential for the largest firms in a market to collude to raise prices)
– However, in a concentrated market like Alberta, the three pivotal supplier test may have limited use as it would likely result in failure in almost all hours.
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Measuring historical competitiveness – 2012 MSA Report …. • These figures, from MSA paper (Measuring Generator Market Power,
2012), demonstrate that during the majority of times, the large firms would fail a structural test of competitiveness if measured at RSI = 1
• Considering a threshold a RSI<1, the test identifies specific hours where the test fails instead of mitigating in all conditions.
– Method using firm-specific residual supplier tests
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Assumptions for 2021 forecast RSI
• No PPA’s are active and Balancing Pool assets were assigned to their owners.
• Additional assets from the LTO 2017 output were not assigned to existing firms.
• The hourly Available Capabilities were taken from the LTO 2017 output. – The capabilities are gross capabilities.
– Imports were excluded. – Wind and solar are taken into account in the supply.
• For demand, Alberta Internal Load (AIL) forecast from the LTO 2017 was used.
• Five major suppliers were considered for calculating RSI
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Further Discussion on Residual Supplier Indices
• RSI tests measures whether or not a firm’s supply is needed to meet demand. – Can be used to gauge the potential for that firm to withhold
capability and impact price or “pivot” the market.
• Setting the threshold level to 1.0 in the duration curve demonstrates the amount of times that the market “needs” all of the firm’s capability to meet demand. – This is a very stringent threshold and perhaps not realistic
because a firm withholding all of their capability would receive no benefit from exercising such market power.
– An alternative to gauge degree of market power is to set this threshold level as some number lower than 1.0
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Structural Ex-ante Measures
• Test of Residual Supply or Pivotal Supply (see above slides) • Used by PJM • Advantages and Disadvantages
– Advantage – upon setting the threshold, the test is clearly fail or not fail.
– Disadvantage - only measures the potential for market power – not if it’s actually exercised nor if it has adverse outcome. Potential to over-mitigate (thus requiring the need for more administrative measures to counteract)
– May be the case that majority of offers in AB fail, especially if testing RSI/PST = 1
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Conduct and Impact Ex-ante Measures
• Used by ISO-NE
• Identifying conduct that demonstrates market power
– Does the offer deviate from a pre-determined threshold that proxies SRMC?
• Measuring Impact of offers that exercise market power
– Do the offer and market conditions result in an increase in price above a pre-determined amount?
• If the answer to both these question is “yes,” then the offer is mitigated to SRMC.
• Challenges with conduct and impact tests mainly revolve around identifying SRMC appropriately and identifying the price impact threshold.
• Advantages of using conduct and impact is that it tests and mitigates when market power is being exercised to an unacceptable degree – allows for self-mitigation, to an extent.
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Ex-post mitigation measures
• Advantages – Less administratively burdensome – After-the-fact knowledge and analysis of actual events can result
in more accurate identification of abuse of market power
• Disadvantages – Potentially higher regulatory/compliance risk for market
participants. You don’t know if you’re breaking rules until after-the-fact • Clear guiding documents could offset this risk
• Considerations for how it can be effectively used in a capacity market framework
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Summary / Conclusions
• Structural
– HHI – measuring market share concentration • Rough measure, weighted to identify large participants
– RSI to identify 5% of hours where market power issues exist • Because this is a test for potential market power, the threshold levels need to
be assessed carefully to as to not over-mitigate
• Preliminary analysis based on forecast of 2021 an example of how it would focus on companies in particular hours.
• Conduct and Impact
– Further discussion is required if this path is chosen • What level above SRMC constitutes failing “conduct”
• What price increase constitutes failing “impact”
• Ex poste mitigation
– Likely to continue to some degree
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Offer mitigation
• Goal – competitive prices – Offers mitigated if concern about market
power; – But opportunity to reflect all costs
• Start up, no load, O&M
– Options • Single part offer
– Range of offers to reflect variable costs
• Three part offers
• Soft cap (by asset, by fuel type)
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Fuel
Env cost
Var. O&M
No load
Start up
Min Run
SRMC
Competitive Outcomes
• Short-run Marginal Cost (SRMC) – many cost-elements to consider including; however the goal is to
focus on converging offers to competitive offers which should be measured by SRMC.
– Brattle proposed “all costs that a supplier without market power would include in forming its profit-maximising offer” • includes all costs of generating energy over a dispatch cycle that
would not have been incurred if the generator had been available but not running
• fuel and non-fuel startup costs amortised over a reasonable expectation of output; all fuel costs once the unit is started up (including no-load costs); operating and maintenance costs that increase when producing energy; and any opportunity cost, such as the opportunity cost of fuel that could otherwise have been sold
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Challenges with determining short-run marginal cost
• How to assess SRMC for – As a starting point, even assuming away cogens, loads, variable
assets that would likely pass the screen, it is still difficult to assess SRMC
– There are standard costs available / used in modelling • Basic entries for costs per technology
• Would have to be adapted as technology changes but sets standard for costs.
– Audit model could allow for costs to be submitted is above “standard” amounts
– Opportunity cost more difficult. • Would still need to consider whether opportunity cost offers are
acceptable and determine how to measure / test
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Cost assumptions in the 2017 LTO
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Generation Cost AssumptionsUnit Combined Cycle1 Simple Cycle Coal-to-Gas Wind PV Solar
Installed Capacity (MW) 455 47.5 368-406 50 15Avg. Capacity Factor2 (%) 56% - 71% 3% - 25% 2%-13% 33% - 39% 16% - 19%Heat Rate (GJ/MWh) 6.7 9.6 10 - 12 - -CO2 Emissions3 (Tonne/MWh) 0.375 0.538 0.560-0.672 - -Overnight Capital Costs (2017 $Cdn/kW) $1,500 - $1,950 $1,000 - $1,500 $225 $2,000 $1,330 - $2,100Fixed O&M (2017 $Cdn/kW-yr) $27 $18 $22 $62 $46Variable O&M (2017 $Cdn/MWh) $8 $4 $4 $0 $0Natural Gas Price4 (2017 $Cdn/GJ)
1. 1x1 combined cycle2. Model output by technology over forecast horizon3. Calculated using 56 kg CO2/GJ and Heat Rate4. Range represents annual average prices between 2017 to 2039
$2.61 - $3.49
The cost assumptions in the 2017 LTO form a starting point on cost discussions. These represent standard cost inputs as collected from industry.
Challenges with determining short-run marginal cost
• Because ex-ante mitigation measures result in potential mitigation before actual costs are incurred, reference levels set around SRMC will always be based on estimated or approximated costs.
• The timeframe for evaluation impacts the determination of costs – For example, expectations of cycling and its impact on
maintenance costs, environmental conditions change the calculation on a immediate timeframe
– Given these dynamics, a range around costs may be acceptable
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Challenges with determining short-run marginal cost
• Single-part offer vs. multi-part offer – If in single part offer, will need to allow range to reflect fact that
SRMC (fuel, env cost, variable O&M) doesn’t reflect full on costs especially depending on cycling costs • Could set range at 20-30% above costs by fuel
– 300% number from other markets reflected competitive zone with no market power, that is no need to bid mitigate
• Could set soft cap and not make it purely cost based.
– A multi part offer specifically is used in optimization models and reflects the incremental costs for start up, no load, minimum run separately • In this model, ranges can have tighter margins as each part of the
offer can more accurately capture a cost-element.
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Bid mitigation Options
• Type of bid structure – Single part – Multi part
• Range versus soft cap – Submitted costs / ex ante / audit model – SRMC plus range – Soft cap model
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Bid Structure: Single-part offer vs. multi-part offer
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• Single-part offer
– Currently used in AB
– Pool participants submit offers for each asset that comprise of a single price associated with a specific quantity
– Single price is meant to capture all of the relevant costs associated with the corresponding volume
• Multi-part offers
– Some jurisdictions employ a multi-part offer that differentiates between cost elements such as: • Start-up costs
• No-load costs
• Incremental energy costs
– Multi-part offers reveal explicit cost elements that enable the potential for more detailed cost schedules (mitigated offers)
Options: Single-part offer vs. multi-part offer and defined costs versus range.
• Because single-part bids must capture all cost elements into one price-quantity offer, there are more “unknown” elements. – Likely an inherent relationship between certainty of cost
estimation and single-part vs. multi-part offer: – Range / offer cap likely larger in single part offer model
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Highly-Stringent (less “range”)
Less Stringent (more “range”)
Single-part offer
Multi-part offer
SRMC and Reference Levels
• Applying SRMC to a reference level (cost-based offer) • Can be applied at a asset-class/technology-type level or unit-
specific level – Other alternatives?
• What cost elements does SRMC and corresponding reference levels capture?
• How to assess SRMC for
– Co-gen assets – Renewables – Import / hydro assets
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Reference Levels by Category
• Unit Specific – Most granular level, potential to capture the unique operating
characteristics or each individual asset – Requires market participants to submit information for each asset
• Asset-type/technology – Requires wider set of assumptions regarding costs by technology
• Potentially requiring more wider “bands” around costs
– Further exploration of what differentiates asset-types required
• Market wide – In practice, very similar to current market (system-wide offer cap,
only based in some manner on production cost)
• Others? 28
Cost-elements Included in Reference Levels
• Fuel
• Environmental
• Variable O&M
• Expected cycling and start-up costs?
• No-load costs
• Others? Action item for WG – what can be included?
• Problem with uncertainty of these elements – need for a “range”?
– How to apply this range?
– Two approaches – integrate all these elements (on a best estimate basis) into the calculation of SRMC but keep a lower buffer; OR, include the elements that can be estimated with greatest accuracy and increase the buffer.
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Soft-cap (offer bands by asset type)
• No need for individual resources to submit cost-offers determined through a regulatory approval process
• Can be wide enough to cover the uncertainty in determining costs.
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Administering Reference Levels (for future discussion)
• Submitting SRMC – Using proxies for resource-types determined at an industry-wide
basis? – Defined at the an asset-level and submitted by market
participants?
• Approval process?
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Summary
• Use RSI < 1 for screen – Hourly basis
• Use basis for SRMC for cost mitigation subject to: – Measurement index – at fuel type? – Determining baseline of typical costs – fuel, env, O&M? – Determining range for “other costs” – 20%?
• For discussion
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Next steps – WG9
• Pricing components – Pricing methodology
• Single price / uplifts?
• Settlement interval
• Price cap / floor
• Shortage / scarcity pricing – Link to NDV results / flexibility needs
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Next Steps
Based on these assumptions for screen / costs, the next step is to calculate any need for changes to price cap/floor / shortage pricing and assess likely pricing in this model and their impact on incentives for investment The goals of this analytical exercise will be to: • Better understand how different ex ante market power
mitigation options may impact energy prices and generator energy market revenues
• Demonstrate how different options would work and identify potential tradeoffs
• Test conclusions given uncertainties in load, generator outages, wind penetration levels, and different scarcity pricing regimes
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Proposed Modelling and Analysis of Mitigation Alternatives
• The AESO has engaged Brattle so perform some quantitative analysis on the price impact of various mitigation alternatives.
• The following is a review of the draft methodology proposed by Brattle. – Overview and purpose – Market power mitigation scenarios – Market modeling framework and assumptions
• The proposed method is subject to continued review and is being raised to the working group to discuss and provide feedback.
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Purpose (cont.)
This analysis will not: • Evaluate impact of market power on market efficiency
– This will not be a market power analysis
• Evaluate long-term impacts on supply resource mix absent a capacity market – Will work in tandem with capacity market analysis, to inform
estimates of generator net energy and ancillary services revenues that will “offset” offers in the capacity market
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Overview
Brattle will use an existing model to analyze the relationship between supplier offer mitigation and market prices in the energy market under a variety of conditions. The analysis will: • Examine the historical and projected relationship between
“tightness” of market (supply minus demand, or supply cushion) and the marginal unit’s offer (& market price)
• Also examine the historical relationship between estimates of generator costs and the marginal unit’s offer (& market price)
• Apply that relationship to a future supply curve and future load levels to estimate market prices on an hourly basis – Assuming alternative market power mitigation options
continued...
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Overview (cont.)
• We will evaluate the potential impact of the following uncertainties: – Load variability – Generator outages – Intertie availability
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Overview (cont.)
The analysis will be designed to also address the following:
• Evaluate pricing and revenue sufficiency under different future market pricing approaches:
– Price caps and floors
– Shortage pricing mechanisms
Assumptions used in the analyses will be:
• Available to the working group members
• Consistent with other AESO analyses:
– Use AESO’s 2017 LTO reference case data to the extent possible
The simulations results will be presented to the Working Group
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Pricing Elements in the Energy Market
When evaluating the potential impact of offer mitigation on market prices, the analyses will test various approaches to mitigate offer prices:
– Consideration for different types of offer mitigation will include: • Unmitigated offers using historical patterns (that are related to supply
cushion)
• Offers at suppliers’ variable operating costs
• Offers at a band around suppliers’ variable operating costs
– Considerations for different price caps and floors – Considerations for different approaches for shortage pricing
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Our scenarios capture bookends (unmitigated/tight mitigation) and two cases in-between
Proposed Market Power Mitigation Scenarios
Unmitigated Lower Price Cap Soft Offer Cap Tight Mitigation Status Quo—
supply can offer anywhere from
price floor ($0) to general price cap
($999.99)
Unmitigated offers but lower general
price cap
All offers mitigated to within a specified
band (e.g., minimum of +200%
and +$100 marginal cost
All offers mitigated to resource-specific
marginal cost
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Market Modeling Framework and Assumptions
Future Supply and Demand
Based on the 2017 Long Term Outlook (LTO) • https://www.aeso.ca/grid/fore
casting/
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Assumption Future year 2030 Load growth 0.9%/year Load shape 2014 Generator retirements
All coal-fired by 2030
Renewable additions
5,000 MW (REP) 30% by 2030
Conventional additions
2,400 MW natural gas conversions
+ 13,900 MW new capacity
Market Modeling Framework and Assumptions
Uncertainty and Monte Carlo
• Load: based on actual hourly variability found in 1998–2014 hourly loads
• Generator availability: based on varying historical capacity installed vs. on outage in 1998–2014
• Intertie availability: based on varying historical flows vs. available transfer capability in 2001–2015
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Market Modeling Framework and Assumptions
Supply Cushion versus Pool Price
• Non-scarcity conditions – Supply cushion >1,000
MW – Price relationship based
on Aurora outputs
• Scarcity conditions – Supply cushion <1,000
MW – Historical relationship,
adjusted for assumed prices at cap ($1,000) if negative supply cushion
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Aurora Energy Prices
Offer-based Scarcity Prices
Historical Energy Prices
Non-Scarcity Pricing from Aurora
Operating Reserve
Shortage
Market Modeling Framework and Assumptions
Key Output Metrics
• Energy market revenue margin for each technology – Energy market revenues margins minus going-forward costs
(energy revenues minus variable costs as compared to going-forward costs) – this would show the net-CONE needed under different pricing arrangements
– For generic new entrant combined cycle and combustion turbine – Under different market mitigation approaches; – Given different scarcity pricing regimes; – And under different levels of reserve margins
• Average energy market prices under each case • And, market price profile among certain time periods
(peak/off-peak; scarcity vs. non-scarcity)
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