Category Archives: Measurement and Verification

Policies that have lowered Australia’s electricity consumption – part 3

Bruce Rowse

This post looks at a range of other policies not covered earlier to wrap up the discussion on policies that have lowered Australia’s electricity consumption

Summary – parts 1 and 2

In parts 1 and 2 of Policies that have lowered Australia’s electricity consumption I have looked at a range of policies, including the Renewable Energy Target, the Victorian Energy Efficiency Target (VEET) Scheme, appliance standards and building standards. With a focus on the state of Victoria, I have attempted to quantify how much each of these policies have contributed to the lowering of Victoria’s electricity consumption that has occurred over the period 2008 to 2012/13.

Victoria’s electricity consumption has dropped by around 4,000,000 MWh since 2008, and in 2013 was around 8,000,000 MWh lower than had the increasing trend of 2004 to 2008 remained. As the Australian Energy Market Data referred to in Part 1 is for electricity generation for Victoria, I have assumed that consumption  matches generation, i.e. over the course of each year electricity inflows and outflows out of Victoria to other states are roughly equal.

In part 1 I identified that the RET, aided by the state feed in tariff, and the VEET scheme had contributed to a reduction of around 2,000,000 MWh annually. However there is a considerable uncertainty around the actual savings achieved by the VEET scheme.

In part 2 I identified that appliance energy efficiency standards saved roughly an additional 2,500,000 MWh annually, assuming that estimates of savings commissioned by the Equipment Energy Efficiency program are accurate. Building standards made a smaller contribution, possibly in the range of around 300,000 MWh.

Together these four policies examined (plus including the impact of the state solar feed in tariff) account for a reduction in electricity consumption of very roughly 5,000,000 MWh. Compared with the 8,000,000 total reduction (had electricity use continued to rise at the same rate it had from 2004 to 2008) this leaves roughly 3,000,000 MWh of reduction unaccounted for.

So where would the other 3,000,000 MWh of savings come from? Policies of significance could be:

  • The carbon price from 1 July 2012.
  • NABERS and Commercial Building Disclosure
  • The national Energy Efficiency Opportunities (EEO) program, complimented by the state government’s EREP program.
  • The Victorian government’s Greener Government Building’s Program

Additionally rising electricity prices, caused by rising network charges and environmental charges (including the renewable energy target, VEET and carbon pricing) could have resulted in some voluntary reduction in energy use.

Finally the ongoing decline of Australia’s manufacturing sector could have also made a contribution.

In this post I attempt to quantify these impacts.

The carbon price from 1 July 2012

The carbon price has resulted in an increase in the cost of electricity, as electricity generators have passed on their costs of compliance. This has also made renewable generators more competitive in the national electricity market, with greater renewable generation, particularly hydro, reducing emissions from electricity generation.

In Victoria the drop in electricity generation from 2012 to 2013 of 1,400,000 MWh was roughly 750,000 MWh more than the average annual drop 2008 to 2012.

So very roughly it would be fair to assume that roughly 750,000 MWh of savings could be attributed to the carbon pricing, without being specific as to how the reduction arose, with likely reasons being:

  •  Liable entities, particularly EEO participants, making additional investments to reduce their electricity consumption and thus reducing the quantity and total cost of carbon permits.
  • The carbon price was used to fund the Clean Technology Investment Program (CTIP), which awarded grants on a matched basis for energy efficiency/renewable projects in industry. EEO participants would have tapped into this funding, with projects implemented in 2013. Additionally in also funded the Community Energy Efficiency Program (CEEP) which local governments used to fund predominantly energy efficiency investments.
  • Further additional voluntary residential energy savings in response to further electricity price rises.

NABERS and Commercial Building Disclosure (CBD)

NABERS, the National Australian Built Environment Rating System, provides building sustainability ratings covering energy, water, and indoor environment quality, based on the actual performance of the building. NABERS is primarily used to rate the energy performance of large office buildings,

The Commercial Building Disclosure (CBD) Act 2010 requires that office spaces of more than 2000 m2 obtain a Building Energy Efficiency Certificate comprised of a NABERS rating and tenancy lighting assessment at the time of sale or lease.

Whilst the CBD Act does not require energy efficiency works to be implemented, in a market place where building owners compete for tenants, the CBD Act has been effective in driving efficiency improvements. The savings in 2012 in Victoria have been estimated at 0.1PJ, or roughly 60,000 MWh based on a study undertaken by Pitt&Sherry for the Department of Climate Change.

EEO, aided by EREP

The EEO program is widely recognised as making a significant contribution to emissions reduction by Australia’s largest energy users. This program has required large energy users to identify energy saving opportunities with a payback of four years or less. As with the CBD program, there is no obligation for identified opportunities to be implemented.

The Victorian state government Environment and Resource Efficiency Plans (EREP) program, which ran from 2008 to 2012, similarly required large energy users to identify energy saving opportunities and develop an action plan. It was closed because of overlap with the EEO program.

The five year program review found that over the first 5 years of the EEO program from 2006 to 2011 the EEO program is estimated to have saved 35 PJ of energy savings. There is no state by state break down of savings or identification of the separate electricity and fuels (principally natural gas) savings, however Climate works who participated in the program review found that most of the savings attributed to EEO came from the manufacturing sector (22 PJ).

Victoria is Australia’s largest manufacturer. If we assume that 30% of the 35PJ of savings were made in Victoria, that savings were approximately 1/3rd electricity 2/3rds gas (based on energy audits I have undertaken of manufacturing facilities), this would give roughly 3.5 PJ of electricity savings in Victoria over the period 2006 to 2011. As:

  • the EEO program is on-going;
  • It is unlikely that many saving measures were implemented during the initial years of the program (2006 to 2008)
  • Year on year savings could be expected to be increasing as more measures are implemented.
  • The five year evaluation went only to 2011, and savings would have increased in 2012 and further again in 2013
  • It would seem reasonable to assume that very roughly of the total savings measured to 2011 of 35 PJ, by 2013 savings may have risen to perhaps doubled, or say around 70PJ (not including the stimulatory effect of the carbon price and CTIP).
  • On this basis annual savings in 2013 could be estimated at very roughly say 15 to 20 PJ

Then in very rough terms the Victorian electricity savings in 2013 vs 2008 would have been roughly 1.5 to 2.0 PJ, or perhaps up to around 600,000 MWh.

The Greener Government Buildings Program (GGB)

The GGB program is a program that requires Victorian state government departments and agencies to enter into an energy performance contract for buildings that represent 90% of their energy use. The N.S.W. government has now adopted a similar program.

This is a program I personally am very familiar with, as up until the end of 2013 I was the owner of CarbonetiX, one of the energy services contractors implementing energy performance contracts under the GGB program.

By mid 2012 projects delivering around 50,000 tonnes of GHG savings annually had been funded. My estimate is that nearly all of these savings would be in electricity savings, and with additional GGB projects underway since mid 2012 my estimate is that in 2013 approximately to 40,000 MWh of annual electricity savings arose from the program.

Rising electricity prices

A combination of rising network charges and environmental charges have increased electricity prices. Its believed that domestic users decrease electricity consumption in response to rising prices, whilst commercial and industrial users are relatively insensitive to price increases.

Whilst a price elasticity of electricity price for residential consumers has commonly assumed to be -0.25 (ie a 25% reduction for a doubling in electricity prices) I don’t believe this is the case. Residential electricity prices have nearly doubled since 2008, yet its highly unlikely that consumption has reduced by 25%. I believe a residential price elasticity of only -0.05 is more likely, on this basis the doubling of electricity prices would have seen a drop in residential consumption of about 5% since 2008. With residential consumption accounting for roughly 30% of total electricity consumption, this would result in an annual drop in consumption of about 800,000 MWh in Victoria. For arguments sake lets assume its a bit higher at 1,000,000 MWh.

This full amount, cannot however, be directly attributed to carbon policy, with less than half of the electricity price rises due to environmental charges.

The decline of Australian manufacturing

This has no doubt contributed to decreased electricity consumption, although its likely that future declines will be greater, as Victorian car manufacturers shut down over the next few years and the Point Henry aluminium smelter closes down later this year.

I have no figures to substantiate any estimate, but on balance with other figures put the decline at around 500,000 MWh annually in 2013 vs 2008.


This analysis has shown that a range of policies have contributed to reduced electricity consumption in Victoria since 2008. My estimates of the electricity savings attributed to each policy are tabled below.

Driver Savings (MWh)
Policy with the intent of reducing electricity use/ emissions
Appliance standards 2,500,000
Renewable Energy Target (plus feed in tariff) 1,000,000
Victorian Energy Efficiency Target (VEET) 1,000,000
Carbon Pricing 750,000
Energy Efficiency Opportunities Program 600,000
Building standards 300,000
Commercial Building Disclosure / NABERS 60,000
Victorian Greener Government Buildings 40,000
Measures where policy has had a partial, indirect effect
Higher electricity prices 1,000,000
Factors which are largely unrelated to policy
Decline of manufacturing 500,000
TOTAL 7,750,000

As I have indicated through the discussion, the numbers above should largely be considered as approximations only.

So what has been the economic efficiency of achieving these outcomes? Which policies are more cost-effective than others? This will be examined in another posting.

Policies that have lowered Australia’s electricity consumption – part 1

Bruce Rowse

Since 2008 electricity generation in Australia’s National Electricity Market (NEM) has declined. The graphs below, showing generation from the two most populous states in the NEM – N.S.W. and Victoria – illustrate the extent of the decline.


This sustained decline has never occurred before in Australia’s history.

This post has a focus on the state of Victoria, and looks at the contribution the national Renewable Energy Target (RET) – aided by the state Feed in Tariff –  and the Victorian Energy Efficiency Target scheme have had to reducing electricity consumption. Both these schemes require electricity retailers to purchase and surrender a prescribed number of certificates each year.

Renewable Energy Target

Since 2011 the RET has had two types of certificates, Large Generation Certificates (LGCs) and Small Technology Certificates (STCs). For electricity generation LGCs represent generation plants in excess of 100 kW, with these generators joining the NEM. They are therefore already accounted for in the generation figures graphed above. Well over 80% of STCs have come from solar PV systems.

STCs enable an upfront discount by deeming the forward generation by 15 years. Taking this into account, by analysing the data in the REC registery, the amount of actual electricity generation each year from solar PV in Victoria is graphed below from 2004 to 2012. (2013 data not yet finalised).


The rapid decline in the installed cost of PV in Australia, supported by the RET and the Victorian Feed in Tariff, has caused a rapid growth in the number of PV systems installed, so much so that by 2012 small scale PV contributed to slightly more than 2% of state electricity generation.

The RET had a stimulatory multiplier attached to it for systems under 5 kW in size up until June 2013. Similarly Victoria’s feed in tariff’s started off high, then have twice dropped substantially. Once complete 2013 STC data is available I will preparing a post which examines the impact of the RET and the FIT policies in detail and examines their efficiency and effectiveness.

Victorian Energy Efficiency Target (VEET) Scheme

The VEET white certificate scheme has been in place since January 2009. By analysing the data in the VEET registry the amount of electricity saved as a result of the VEET scheme is graphed below.


Whilst there is reasonably high certainty of the amount of electricity generated by a PV system, there is generally less certainty about the savings achieved by energy efficiency measures. The key technology that has produced the greatest number of certificates in the VEET scheme has been Standby Power Controllers, for which I believe that the deeming values used have been excessively high.

Nonetheless, even if the VEET scheme has only achieved half the savings it has deemed to, it has also contributed to reducing Victoria’s electricity consumption by more than 2% since it started in 2009. In another post I’ll be examining the effectiveness of the VEET scheme in more detail.

Together the REC certificates (with feed in tariff support) and energy efficiency white certificates in Victoria appear to have reduced electricity consumption by over 2,000,000 MWh. However with 2013 electricity consumption around 4,000,000 MWh lower than in 2008, and around 8,000,000 MWh lower than had the increasing trend of 2004 to 2008 remained, there have clearly been other factors that have contributed to Victoria’s declining electricity consumption.

These include national equipment energy efficiency standards, building efficiency standards and carbon pricing. Additionally increases in electricity costs may have driven voluntary decreases in electricity consumption, as would have the gradual decline of Victoria’s manufacturing sector. These will be examined in the next part of this discussion on policies that have lowered Australia’s electricity consumption.



Why M&V is so important to carbon policy effectiveness

Bruce Rowse

A key failure of many carbon abatement policies, a mistake that can be very costly, is the failure to adequately incorporate measurement and verification (M&V), also known as measurement reporting and verification (MRV) into policies that aim to reduce GHG emissions. You can’t manage what you don’t measure.

Most certainly you can’t manage what you don’t measure

Every business measures its income and expenses; but when the business fails to monitor them, the chances are that it will go out of business very soon.

The speed of cars is measured by a speedometer, and it is illegal to drive without this instrument functioning. Speedometers and the laws around speeding have saved countless lives around the world.

Every investor is deeply interested in returns and certainty. When a bank promises to pay an interest of 4%, an investor knows that there is extremely high certainty that they will earn 4% interest. Complex financial instruments that may provide higher returns also have less certainty and are not used by conservative investors. Gambling also has the promise of high returns, but on balance punters get less out than they put in.

Climate change is a serious concern and does not warrant a cavalier response. Yet when it comes to climate change policy, M&V to improve certainty of results and thus optimise policy or quickly ditch bad policy is done too infrequently. Policies are tuned too slowly. The scientific method that I was taught in high school and that dominated my university training – develop a hypothesis, prove the hypothesis, and when the hypothesis is proven, apply it elsewhere – often isn’t used with sufficient rigor. Instead, we have policy by modelling. A consultancy is contracted to model the policy. The consultancy will deem that this policy costs $X per tonne of carbon saved. If the numbers look good and public consultation shows industry support, then the policy is implemented. However, too often, there is inadequate M&V to verify the actual cost-effectiveness of the policy in reality.

As a result, inefficient policies can live on and may only change, or be ditched, when there is a change of government, substantially bad publicity or strong lobbying by industry heavyweights who think they are missing out on some of the pie. On the flip side, good policy may be ditched far too early for the same reasons. In addition, when the policy is debated, all sorts of figures may be thrown around, but often no one really has a clue what the actual cost per tonne of carbon abatement is because it hasn’t been robustly measured!

A typical common policy approach seems to be as follows:

  1. Formulate the policy;
  2. Develop an economic model;
  3. Contract a consulting company to develop the policy detail and to model detailed cost–benefit analysis;
  4. Implement the policy;
  5. Review it once, or perhaps twice.

The critical flaw in such policy making is that it assumes that the models developed and the detailed cost–benefit analysis are correct. But often, the certainty around the modelling accuracy is low, and in fact, in a world where technological change is happening exponentially, it is extremely hard if not impossible to model with great confidence. The modelling should be considered as a hypothesis; rather, it is treated as the truth.

In other words, the modeller takes an “educated” bet on the outcome, but there is no guarantee of certainty.

The policy approach that I put forth is different in that M&V must be core to the policy, and that policies should initially be rolled out on a small scale with robust M&V before a large-scale roll-out.

The approach is then as follows:

  1. Formulate the policy;
  2. Model a hypothesis as to the likely costs and benefits of the policy;
  3. Develop an M&V plan that shows how the results will be robustly measured and verified so as to provide a high level of certainty as to the short- and long-term carbon abatement that will be achieved;
  4. Implement the policy on small scale;
  5. Undertake measurement and verification and produce an M&V report;
  6. Compare the results from the M&V report with what was originally hypothesised. In light of the M&V findings, then either completely abandon or tune the policy. In tuning the policy:
    1. Develop an M&V plan for the changed policy;
    2. Implement the policy;
    3. Undertake M&V and report on;
    4. Undertake further tuning of the policy on a periodic basis.

Policy by modelling is a linear approach with few feedback loops to gauge real policy impact or effectiveness, whereas policy with strong M&V is iterative with an emphasis on maximising real benefits.

Policy by modelling is similar to taking a bet at the races.

Policy with robust M&V is like putting your money on term deposit.

Modelled savings versus actual savings – and why modelling should be treated as a hypothesis

As an energy auditor, I have a great deal of experience in estimating or modelling the likely savings that will arise out of an investment in energy efficiency. I have audited over a thousand buildings and produced hundreds of energy audit reports.

An energy audit is essentially a business case for investment in energy efficiency. It lists a range of measures, and for each measure shows the estimated cost, annual savings, payback and annual greenhouse gas (GHG) savings. It could be considered as a form of micro-modelling from a policy perspective.

It is extremely hard to model with a great deal of accuracy. Experience helps. In the following, I list some of the difficult learning experiences that I have been through as an energy auditor. What I’ve gleaned from these learning experiences has no doubt helped me improve my accuracy, but nonetheless it is still extremely difficult to estimate energy and GHG savings from many energy-efficiency measures with a high degree of confidence:

  • On one occasion, where I under-estimated the cost of a lighting controls upgrade in a school by 40%, I ended up doing a lot of work for free and paying contractors out of my own pocket to get the work complete.
  • On another, I overestimated savings from a lighting upgrade by 50%.
  • While in another instance, I guaranteed savings of 7% in a tender bid from installing a voltage optimisation unit. Fortunately, I lost that one. The company that won the job and put in technology similar to what I would have installed, only achieved a 5% saving. Phew! I was out by a factor of 40% in my estimate!
  • On another occasion, the advice I approved resulted in a $350,000 investment in a cogeneration unit. The expected annual cost savings were $27,000 but the actual cost savings were $0. The carbon savings were closer to the estimate. But clearly, this was not cost-effective carbon abatement.

And I am not the only energy auditor who can get it wrong. A study by Texas A&M when evaluating the work of pre-qualified energy auditors 5 years after projects had been implemented found that measured cost savings on average, across 24 projects, were 25.1% lower than estimated. In some cases, savings were as little as 5.5% of what was estimated![1]

If energy auditors, who understand the details of technology and undertake site-specific investigations, can be out by 25% or more on individual projects, how accurate can policy modelling be? Modelling is usually based on a number of assumptions, possibly a small number of case studies, and the results are then assumed to apply to a large number of buildings. It is generally far less rigorous than an energy audit – an energy audit can account for the diversity in an individual building, but modelling needs to somehow account for the diversity across a whole range of buildings.

Policy modelling should only be treated as a hypothesis. Robust M&V is needed to determine the effectiveness of carbon policy with a high degree of certainty.

In my book Carbon Policy – How robust measurement and verification can improve policy effectiveness, I show how policy makers can effectively incorporate  M&V into carbon abatement policy to provide much greater certainty of policy outcomes.

[1] As reported in: Hansen S. and Brown J., Investment Grade Energy Audit: Making Smart Energy Choices, 2004, The Fairmont Press Inc.


Why measure carbon policy effectiveness?

Exploring the topic of carbon policy effectiveness makes the rationale for measuring the effectiveness of carbon policy self evident.

The effectiveness of a policy is dependent on the environmental benefit with respect to the economic costs and benefits of the policy.

I consider the cost of a carbon policy the total cost of the policy to society, which includes government investment in developing and administrating the policy (and in some cases, actually financing the policy) and the costs imposed by the policy either directly or indirectly on households and business. Often policy seeks to leverage household or business investment.

The financial benefits of a carbon policy are the benefits to society, such as reduced power bills. The key environmental benefit is the reduction in GHG emissions, although there may be other environmental benefits also of high importance, such as reduced air pollution because of a reduction in the combustion of fossil fuels.

Can the transaction costs arising from a policy be considered a benefit? For example, under a white certificate scheme, electricity retailers may pass on their costs, with a mark-up, to consumers. These costs actually then reduce the financial benefits to end users – continuing the example of a white certificate scheme, the power bill savings from reduced energy consumption may be partially, wholly or more than offset by the increase in electricity tariffs. Can the profit made by the electricity retailer be considered a benefit? It could be considered an economic benefit (i.e. to shareholders of the retailer), but this economic benefit comes at the cost of others (energy consumers). It adds nothing to the environmental benefit. Whilst transaction costs are unavoidable, the larger the transaction costs for a given amount of carbon saved, the greater the cost of abatement.

Therefore, policy effectiveness, in my view, comes back to the total cost, including the transaction costs, per tonne of carbon saved. The lower the total cost per tonne of GHG emissions saved, the more effective the policy. With all other factors considered equal, this also translates into greater real economic benefit.

The expected or understood cost of carbon abatement may be misrepresented because the transaction cost of the carbon abatement is not included in the analysis. For example, marginal abatement cost curves, which have a focus on individual technologies, do not show the transaction costs of achieving the abatement. Different policy types may have different anticipated and unanticipated transaction costs. Thus the marginal abatement cost curve can be policy specific.

Policy effectiveness is important for a number of reasons.

First, carbon policy fundamentally aims to reduce carbon emissions, and the less this costs, the greater the amount of carbon that can be saved within a given investment.

Second, an ineffective policy does not generate the spin-off effects of an effective policy. For example, a policy that does not effectively reduce the energy used to heat and cool a home does not improve comfort as much as it otherwise would have, and in addition, does not create national competitive advantage in being able to export skills, services and products that effectively reduce home heating and cooling requirements.

Third, ineffective policy means carbon abatement is not an investment that can provide a financial return on investment, but rather becomes an expenese. Many carbon abatement technologies now exist that can, if applied efficiently, provide a reasonable financial return on investment. However, ineffective policy can result in poor or no financial return on investment.

Fourth, ineffective policy reduces the political capital that is so important to reducing carbon emissions. Ineffective policy damages credibility.