TODAY’S STUDY: THE MANY BENEFITS OF HIGH HOME EFFICIENCY STANDARDS
The Evaluation of the 5-Star Energy Efficiency Standard for Residential Buildings
Michael Ambrose, Melissa James, Andrew Law, Peter Osman and Stephen White, December 2013 (Commonwealth Scientific and Industrial Research Organisation)
In 2006, the Building Code of Australia (BCA) set a new residential building energy efficiency standard of 5 stars, as rated by software tools accredited under the Nationwide House Energy Rating Scheme (NatHERS). To reach the 5-star energy efficiency standard, architects and builders could choose from a large variety of options, such as increasing insulation in ceilings, walls and floors; using double glazing; and redesigning house layout and orientation.
The Regulation Impact Statement (RIS) on the 5-star standard analysed its likely impact on the energy efficiency of new houses relative to the previous standard. The RIS estimated that the 5-star standard would reduce heating and cooling energy costs, as well as greenhouse gas emissions. In 2012, to assess whether the new standard was achieving its goals, the Australian Government asked CSIRO to: i) find out whether the 5-star standards have actually reduced heating and cooling energy use of houses compared with those built to the earlier 3.5 to 4-star standard; and ii) determine the actual benefits and costs of meeting the 5-star standard To undertake this task, CSIRO studied 414 houses in the principal centres of population of three BCA climate zones over a winter and summer period.
This report details CSIRO’s response to the above questions. In this report, 5-star (or above) houses are referred to as higher-rated houses, while houses less than 5-stars were referred to as lower-rated houses.
The findings should be regarded as preliminary, because research work and monitoring is ongoing and relevant only to the houses that were included in this study (i.e. detached houses built in the last ten years in Brisbane, Adelaide and Melbourne). Several factors have made it difficult to draw robust conclusions about the differences in energy use between lower-rated and higher-rated houses that could be applied to other such houses across Australia. Some of the factors causing this uncertainty are briefly described below.
• The uneven distribution of houses across star rating values in the data set means that the sample size restricts the conclusions that we can make.
• The small sample size causes uncertainty about how representative the data set is of Australia’s households, particularly in relation to household type, occupancy patterns and user behaviour.
• The above-average temperatures during the summer period make it likely that air-conditioning appliances were operating at full capacity, regardless of star rating, making it difficult to detect differences between lower and higher-rated houses.
• The higher-rated houses were generally constructed more recently than the lower-rated houses, and further investigation is needed to check whether this caused any inherent bias. For example, the newer, higher-rated houses were more likely to contain younger children, have someone home all day, and identify themselves as high energy users.
• The expected energy ratings of the houses in our sample have not increased in line with the changes in building regulation. The reasons for this, as well as the quality of build compliance issues raised by the study, needs to be further examined.
Increased monitoring of houses across Australia will help to provide a clearer picture of the impact of increasing star ratings on household energy consumption. Data collected through this analysis should also be compared with alternative data sources to provide a more robust understanding of house performance.
Essentially, our main findings are as follows.
• The 5-star standard significantly reduced the energy needed to maintain house temperatures in winter in the houses we studied. As well as saving energy, higher-rated houses were on average held at a temperature around 1 °C higher than lower-rated houses during winter. It is not clear if this was because the occupants had set the temperature higher, or whether it was an innate property of the control system or a result of increased thermal insulation. We estimate in Section 10.2 that if the temperatures had been the same in both groups (thus comparing on a like-for-like basis), then the average energy per unit of conditioned floor area saved in the winter season in the post-2006 cohort of higher-rated houses would have been:
o 0.4 kWh m-2 electricity in Brisbane (climate zone 2): 20% reduction (10.2.1)
o 2.7 kWh m-2 electricity in Adelaide (climate zone 5): 39% reduction (10.2.2)
o 29 kWh (104 MJ m-2) gas in Melbourne (climate zone 6): 56% reduction (10.2.3).
Without compensating for the increased warmth of higher-rated houses, the observed average energy saving for winter was:
o negligible in Brisbane (climate zone 2) (10.2.1)
o 1.3 kWh m-2 electricity in Adelaide (climate zone 5): 19% reduction (10.2.2)
o 25 kWh m-2 (86 MJ m-2) gas in Melbourne (climate zone 6): 50% reduction (10.2.3).
• The average cooling energy use in summer was greater in the higher-rated houses in Brisbane and Melbourne. However, it is not clear whether this was due to the 5-star standard, the make-up of the house occupancy of higher-rated houses with more children and higher rates of full-time occupancy, or other behavioural factors. These include the extent of window opening and closing during summer, and the scale of heat loads from other home appliances and equipment (Chapter 3). There was also no difference in the temperature between the lower and higher-rated houses. CSIRO is continuing measurement and statistical analysis on the houses included in this study.
• Greenhouse gas emissions were reduced in winter in higher-rated houses in all cities (Table 9-1).
However, summer emissions increased in higher-rated houses in all cities (Table 9-2). Overall, greenhouse gas emissions were still reduced by 7% for the higher-rated houses over the year, despite the summer season increase.
• Heating costs were reduced and cooling costs increased in higher-rated houses (Table 9-1 and Table 9-2). The net annual impact was that Brisbane costs were greater in higher-rated houses, whereas Adelaide and Melbourne costs were lower for the higher-rated houses (Table 9-3). The reductions in Adelaide were small, but in Melbourne the reduction was a significant (37% or $194 per year).
• The higher-rated houses cost at least $5000 less in Adelaide and Melbourne for those elements of the building related to energy efficiency than lower-rated houses, and up to $7000 less in Brisbane. Increases in the amount of insulation and an apparent shift to more rectangular house design were the most influential aspects observed in the shift to higher-rated houses.
We conclude that the 5-star standard has produced significant savings in heating energy use in the sample. However, we need to improve our understanding of summer-time house cooling energy efficiency. The smaller-than-expected value of the temperature difference between the interior of the house and the outside environment suggests that additional variables are affecting house cooling compared with house heating. The relatively small sample size used in analysing some cohorts, particularly in Brisbane, may have also affected our ability to draw firm conclusions. Identifying and evaluating these variables will enable architects, building sustainability assessors and equipment designers to provide more thermally efficient house cooling, as well as advise the public about improving thermal comfort and reducing summer energy bills. Further analysis of the massive dataset that CSIRO has produced will help to reveal these areas of potential energy efficiency gains for housing…
Heating and Cooling Energy Use
We analysed the data from the volunteer households to ask whether the 5-star standard actually reduced heating and cooling energy use in houses compared to those built to the earlier 3.5–4-star standard. In other words, are higher-rated houses more energy efficient than lower-rated houses?
The type of heating and cooling equipment varied among the houses in the study. Reverse cycle air-conditioning (heat pumps) were the dominant heating system in Brisbane and Adelaide, whereas gas heating was dominant in Melbourne. In Brisbane and Adelaide, heat pumps were the dominant cooling system. In Melbourne, 40% of houses used evaporative cooling, 40% used heat pumps, and the remaining 20% had no cooling system. As the star rating system does not take into account the type of heating or cooling appliance, we separated houses into cohorts with the same appliance type when performing statistical analysis.
Winter heating energy use
Regardless of climate zone or heating system, we found that the higher-rated houses had slightly higher temperatures than lower-rated houses in the main living area: typically from 0.6 to 0.9 °C higher. This was unexpected, because we anticipated that temperatures would be the same in all houses. The higher temperatures could be due to human behaviour, greater insulation, or an innate property of the control system.
The measurements and statistical analysis provided us with enough information to calculate, at 95% significance, how much energy was being saved (actual savings), as well as how much additional energy (inferred savings) could have been saved if the higher-rated houses had been operating at the same temperature as the lower-star rated houses. From the statistical analysis, the actual and inferred energy saving in winter for a higher-rated house (compared with a lower-rated house) are given below:
• Brisbane: 20% potential savings, if temperatures were kept at the same level as for the lower-rated houses
• Adelaide: 19% actual saving, with an additional 21% potential saving due to the increased temperature in the higher-rated houses
• Melbourne: 50% actual saving, with an additional 6% potential saving due to the increased temperature in the higher-rated houses.
Summer cooling energy use
Energy consumption was increased in summer in houses with higher star ratings in Brisbane and Melbourne, while the test results from Adelaide were not statistically significant for a 95% confidence level. These summer results may have been confounded by the following two factors: i) cooling equipment running at full capacity during the particularly hot 2012–13 summer months (if this was the case, then the measured energy consumption is merely an indicator of the installed capacity of the air conditioners, rather than a measure that can be used to assess the effect of star rating) ii) it was not possible to reliably assess the levels of ventilation being used in the houses.
More measurements and a more detailed analysis are needed to resolve these two issues.
Comparing summer cooling and winter energy use
The difference between interior and exterior house temperatures in summer was relatively low compared with winter. In contrast, heating energy consumption in winter did an effective job of warming the house above the ambient temperature. This difference between winter heating and summer cooling may be because houses contain substantial internal sources of heat that place an additional load on cooling in summer, but assist heating in winter. These might include heat loads, such as ovens, standby1 power, televisions and computers; or ambient heat and solar heat that has entered the house and been stored. Another factor making analysis of these results difficult was the wide variety of cooling methods, such as ventilation, shade, fans and air conditioners.
Benefits and Costs
Possible benefits arising from higher-rated houses could include improved occupant comfort, reduced electricity and gas costs, and reduced greenhouse gas emissions. We analysed each of these by comparing the difference between the inside and outside temperature, analysing energy bills, and measuring the energy used by heating and cooling appliances to determine greenhouse gas emissions, respectively.
In winter, the increased temperature of 0.6–0.9 °C in the higher-rated houses may have improved occupant comfort. However, a greater energy saving benefit may be realised by householders in higher-rated houses if their winter-time thermostat settings were lower and closer to the value in lower-rated houses.
When considering whole-of-house energy consumption, costreductions were observed in Adelaide and Melbourne for higher-rated houses, with a 3% reduction in costs in Adelaide and a 13% reduction in Melbourne. Brisbane houses effectively remained the same (Table 8-3).
When considering heating/cooling appliance energy consumption, we did not see a reduction in electricity costs in higher-rated houses compared with lower-rated houses. It is possible that energy saved from heating higher-rated houses was used elsewhere, for example, to maintain higher temperatures in the house. In houses with gas heating, the gas consumption was 52% less in higher-rated houses than in lower-rated houses (Table 9-1).
In winter, average greenhouse gas emissions from heating appliances were reduced in higher-rated houses compared with lower-rated houses: by 50% in Melbourne, 9% in Adelaide and 13% in Brisbane. In summer, preliminary (not statistically significant) results suggest that greenhouse gas emissions may be increased for the higher-rated houses in all cities: by 37% in Melbourne, 11% in Adelaide and 28% in Brisbane. The result in Melbourne was affected by the high emission factor of brown coal-fired power stations.
As well as the measured energy saved due to the 5-star rating, there were also potential savings to be made due to the increased temperatures in higher-rated houses. Overall, the improved insulation in higher-rated houses appears to have the potential to save energy and greenhouse gas emissions in winter, but makes little difference in summer.
In the RIS, the costs of meeting the 5-star standard were expected to be more than for lower-rated houses. However, our results show that based on the sampled house designs, it has actually been less expensive to meet the 5-star standard than the previous standard. The average cost for those elements of a building that are related to achieving the star rating were $7,500 less in Brisbane, $5,500 less in Adelaide and $5,000 less in Melbourne. This was mainly because of an observed shift to more rectangular floor plans; leading to a larger floor area per unit of wall and glazing (the window-to-wall area ratio was similar). Although the cost of insulation rose, this was outweighed by the savings made on walls and windows. The cause for these changes in design may be due to factors unrelated to the star rating, but their inclusion affects the star rating and the cost of the building.
Recommendations for Further Work
Overall, this research has shown that a great deal of further measurement and analysis is required to enable effective decisions about the future of house cooling energy efficiency in Australia. We have amassed an extremely large data set, which has so far been only partially analysed. More research is required to unlock learnings from this data.
For example, the current study focused on averaged seasonal data sets, rather than on what happens in specific circumstances. Analysing subsets of data from particular time periods under particular search conditions may help to reduce uncertainty by eliminating irrelevant data. It would also help answer a range of additional questions. For example, under what conditions do people turn on their air conditioners? What room temperatures are being achieved when the air conditioner is switched on?
More contextual data may also need to be gathered from the sample houses and occupants to better understand the key drivers of heating and cooling energy use. Maintaining the existing cohort of houses presents Australia with the opportunity to create a register of monitored test houses for future studies.
More research is also required to compare the energy performance of individual houses using the Chenath thermal modelling engine, which forms the basis of the rating tools accredited under NatHERS. Predictions from the Chenath engine should be done under as-occupied assumptions, rather than rating assumptions. This would help to further validate the NatHERS benchmark calculation engine and provide a basis for identifying key hhouse design sensitivities.
The data should also be used to explore a range of industry issues, such as:
• quantifying the impact of thermal loads,such as cooking appliances, entertainment and home office electronics, standby loads and human metabolism, whichmay favour heating efficacy in winter over cooling efficacy in summer
• identifying the variety of human behaviour (e.g. opening windows) and thermal comfort factors (e.g. thermostat settings) affecting energy consumption, and informing the Australian public about improving thermal comfort and saving energy in their houses
• using this information to better understand which house design solutions are most appropriate for summer cooling-dominated climates
• identifying the relationship between the peak cooling demand predicted by the Chenath engine and air-conditioner sizing, and informing the residential air-conditioning industry of opportunities for improving energy efficiency and reducing costs