Jun 23 2017

Dr Finkel, Figures and Dr Fisher’s Mysteries

While the political dogfight over Dr Finkel’s recommendation to introduce a Clean Energy Target raged last week, the team quietly published the modelling report they commissioned from Jacobs. Usually such modelling is of interest only to the geekier element among us, but the Jacobs report indirectly made headlines due to a critique by former senior government economist Dr Brian Fisher[i] commissioned from the Minerals Council of Australia (MCA)[ii]. So do Dr Fisher’s criticisms stand up?

What the modelling shows

Jacobs modelled a “business as usual” scenario, i.e. without any new emissions reduction policy. They then modelled two policy scenarios, Dr Finkel’s preferred Clean Energy Target (CET) and an Emissions Intensity Scheme (EIS). To this they add three further scenarios each with a Limited life policy for existing coal plants (50 years). Finally they modelled a sensitivity to the CET + Limited life scenario (which had the highest levels of variable renewable energy), where a constraint was applied to maintain a minimum level of synchronous generation to ensure a secure energy system at all times. The minimum level was based on analysis by the Melbourne Energy Institute.

Dr Fisher’s mysteries

One of the main issues raised by Dr Fisher is the counter-intuitive result that the business as usual scenario has the lowest resource cost but does not result in lower prices for consumers (the clean energy target, followed by the EIS scenario have the lowest). This phenomenon is not peculiar to Jacobs’ modelling. It has turned up in other modelling exercises, including the modelling for the Warburton review of the Renewable Energy Target, for which Dr Fisher was a member of the expert panel[iii]. What it typically reflects is that the subsidised influx of new generation reduces the returns to existing generation, but critically, not enough to trigger premature closure of that generation. In this way, higher resource costs + lower returns to generators = lower prices. This is something of a Goldilocks scenario, though – tweak the assumptions and you end up with either much higher resource costs, or returns are depressed so much that plant starts exiting, causing the wholesale price to rebound. The latter is close to what we have actually seen as coal plant, in particular Northern and Hazelwood, has exited the market.

In the modelling for the Finkel report, there is something else happening that leads to the outcome of lower prices though, and this is another of the issues raised by Dr Fisher. He suggests that the modelling may overstate the costs of coal plant and understate those of renewables. He identifies to three elements to the coal plant costs, two of which are specifically used in modelling BAU.

  1. In BAU, there is a premium to the cost of capital for new coal plant, reflecting the carbon risk around higher emission plant in the context of policy uncertainty. This premium is not used in modelling the other scenarios as these all have a clear policy in place. Higher costs of capital require higher returns and so this is another way in which a scenario with lower resource costs can result in higher prices. Dr Finkel has defended this particular modelling assumption, saying “we consulted extensively to determine the financing costs associated with project risk for large projects, and the financing costs associated with uncertainty risk in the absence of an emissions reduction policy”[iv].
  2. In the BAU scenario the maintenance schedules of coal-fired generators would be affected with plant owners only carrying out major maintenance or refurbishment if a quick payback can be ensured. This results in deteriorating efficiency and availability.
  3. In all scenarios, coal prices used are higher than Wold Bank estimates of global thermal coal trends to 2030. Conversely they are lower than assumptions used by AEMO. Based on that it’s hard to say they are unreasonably high.
Valid Criticisms?

Whether the first two points are valid criticisms of the modelling depends on whether one accepts that there is currently policy uncertainty, that this will affect investors and owners’ decision-making in ways similar to those modelled by Jacobs and whether the introduction of a stable long-term policy framework would remove these issues. Overall this is at least a plausible position, albeit one that cannot be definitively proven. It is not only Jacobs and the Finkel team that have taken this position. A recent report by the Climate Change authority (CCA) and the Australian Energy Market Commission (AEMC) also supports this conclusion[v]. Analysis undertaken for their report by the Centre for International Economics (2017) indicates that current wholesale electricity prices are above long-run costs by around $27 per megawatt hour (MWh) to $40/MWh. The AEMC and the CCA “are of the view that policy uncertainty is a significant driver of this cost impost”[vi].

Dr Fisher points out that while coal costs are higher due to the above assumptions, renewables costs appear to him to be low. Jacobs assume a capital cost for wind generation of $2,400/kW, as compared with $2,608/kW in the Australian Power Generation Technology Report and estimates in the range of $2,629 to $2,659/kW (depending on the location) applied by AEMO. But this is a case where Jacobs can’t win. Noted renewables cheerleader and blogger Giles Parkinson wrote that Finkel had set the cost of new renewables too high![vii] Dr Finkel himself acknowledges that the benchmarks for new wind and solar PV projects change rapidly: “We were conservative in our estimates of wind and large-scale solar generator prices. Indeed, in recent months the prices for wind generation have already come in lower than what we modelled.”[viii]

More pertinently, Dr Fisher notes that the modelling excludes other relevant costs that may be greater under higher renewables penetration, including new transmission as the location of generating plant shifts from areas with coal deposits to areas with good wind and solar resource. There may also be increased costs associated with providing ancillary services as the existing supply of such services from synchronous generators like coal plant becomes scarcer. Jacobs’ approach of ignoring such costs is not unusual, but market modelling would be more complete if it took account of such costs, as they may well become material over time. Conversely, as we establish new markets and tweak the regulatory framework to enable services to be provided in non-traditional ways, we will find cheaper ways to maintain system security. The one sensitivity where this was modelled (on the CET plus Limited Life) led to only a modest change in the overall outcomes, including on costs.

What the modelling (does and doesn’t) tells us

Part of the point with evaluating such modelling is to be clear about what the modelling does or doesn’t tell us. Such modelling is not a crystal ball into future prices or generation mixes. It is rather a way of telling a story, of illustrating a point. In this instance the main point is that policy uncertainty means that putting any sensible policy in place is cheaper than no policy – as well as having the merit of directly driving abatement. If the assumptions and logic of the model are reasonable then its conclusions can be considered reasonably robust. The secondary point in this case is to suggest that a CET is marginally cheaper than an EIS at delivering the same abatement task while maintaining reliability and system security, and both are better than a limited lifetime (or regulated closure) approach. The modelling carried out for the CCA/AEMC analysis. Ranked an EIS as the most efficient, albeit the comparison was to an enhanced LRET rather than a CET. Given that any resulting policy will be a political solution rather than an objective assessment of policy options, the point is less to try to figure out if an EIS , a CET or some other mechanism is better, and more to get some sort of broadly technology neutral policy in place for the long term.


[i] A bio of Dr Fisher can be found at http://www.baeconomics.com.au/about

[ii] Review of Jacobs’ modelling of the Finkel Review scenarios, BAEconomics, June 2017

[iii] http://webarchive.nla.gov.au/gov/20141215020939/https://retreview.dpmc.gov.au/ret-review-report-0

[iv] Dr Alan Finkel, “National electricity Market Reform – A blueprint for the future”, address at the National Press Club, 21 June

[v] Towards The Next Generation: Delivering Affordable, Secure And Lower Emissions Power, AEMC/CCA, June 2017

[vi] ibid

[vii] http://reneweconomy.com.au/finkel-modelling-ignores-new-technologies-cheaper-renewables-33626/

[viii] National electricity Market Reform – A blueprint for the future

Related Analysis


Texan energy crisis: Lessons for Australian electricity markets

In February Texas endured a winter storm that dragged temperatures well below freezing. Electricity generation plant and gas infrastructure proved unprepared for these temperatures and around a third of the state’s effective capacity went offline for some or all of this period, just as demand was spiking to a new winter record.

Apr 22 2021

Customer benefits don’t necessarily benefit the customer

A perennial discussion in energy market policy is the contest between what we are ultimately trying to achieve: “customer benefits” or “market benefits”. When making market rules, or building monopoly assets, rules require that we assess “net market” benefits. A number of recent government policies have been justified on customer benefit assessments alone.

Mar 18 2021

How do we deal with emerging excess supply?

The economics of traditional plants are well understood, but since their construction, the way they need to operate has changed substantially. This has been driven by a combination of the age of the plants as well as the large influx of renewables, which is changing the supply and demand patterns of the grid.

Mar 18 2021
Do you have a question or comment for AEC?

Send an email with your question or comment, and include your name and a short message and we'll get back to you shortly.

Call Us
+61 (3) 9205 3100