Title of Report or Proposal - energy



Emissions and energy savings from potential changes to National Construction Code energy performance requirements - the Code CalculatorPrepared for the Department of the Environment and Energy, June 2017Revision HistoryRev No.DescriptionPrepared byReviewed byAuthorised byDate00ReportPHPMcLPH24/6/201701Report (web accessible)PHPH23/1/2018? 2017 Strategy. Policy. Research.This document is and shall remain the property of Strategy. Policy. Research. Pty Ltd. The document may only be used for the purposes for which it was commissioned and in accordance with the Terms of Engagement for the commission. Unauthorised use of this document in any form is prohibited.Table of Contents TOC \h \z \t "Executive Summary" \c Executive Summary PAGEREF _Toc486081144 \h iv TOC \o "1-2" 1.Background PAGEREF _Toc504470934 \h 11.1Purpose PAGEREF _Toc504470935 \h 11.2Scope of Work PAGEREF _Toc504470936 \h 12.Stock Turnover Model PAGEREF _Toc504470937 \h 22.1Introduction PAGEREF _Toc504470938 \h 22.2Data Sources and Uncertainties PAGEREF _Toc504470939 \h 22.3Residential Buildings PAGEREF _Toc504470940 \h 52.4Commercial Buildings PAGEREF _Toc504470941 \h 83.Residential Building Projections PAGEREF _Toc504470942 \h 133.1Baseline Projections PAGEREF _Toc504470943 \h 133.2Policy Scenarios PAGEREF _Toc504470944 \h 173.3Indicative Results PAGEREF _Toc504470945 \h mercial Building Projections PAGEREF _Toc504470946 \h 234.1Baseline Projections PAGEREF _Toc504470947 \h 234.2Policy Scenarios PAGEREF _Toc504470948 \h 275.Uncertainties and Further Research PAGEREF _Toc504470949 \h 295.1Building Stock PAGEREF _Toc504470950 \h 295.2Refurbishment/Demolition Rate, and Building Compliance PAGEREF _Toc504470951 \h 305.3Reference Energy Intensities PAGEREF _Toc504470952 \h 31Appendix A: User Guide PAGEREF _Toc504470953 \h 32Overview PAGEREF _Toc504470954 \h 32Basic Functions PAGEREF _Toc504470955 \h 32Detailed Results by State/Territory, Building Type, Year and Fuel PAGEREF _Toc504470956 \h 33Detailed Settings PAGEREF _Toc504470957 \h 34Index of Figures TOC \h \z \c "Figure" Figure 1: Residential Building Greenhouse Gas Emissions Savings by Dwelling Type, 2020 – 2050 Cohort, Scenario 2 PAGEREF _Toc486081170 \h vFigure 2: Commercial Building Greenhouse Emissions Savings, 2020 - 2050 Cohort, Scenario 1 PAGEREF _Toc486081171 \h viFigure 3: NEXIS Data Layers PAGEREF _Toc486081172 \h 4Figure 4: Residential Building Stock Totals by Type, 2001 – 2050, Australia PAGEREF _Toc486081173 \h 7Figure 5: Annual Build to Code, Residential Buildings by Type, 2002 – 2050, Australia PAGEREF _Toc486081174 \h 7Figure 6: Distribution of Total Residential Stock by State and Territory, 2017 (‘000 sqm, %) PAGEREF _Toc486081175 \h 8Figure 7: Distribution of Commercial Building Floor Area by NCC Class, Australia, 2017 (‘000 sqm, %) PAGEREF _Toc486081176 \h 10Figure 8: Total Commercial Building Stock by Class, Australia, 2001 - 2050 PAGEREF _Toc486081177 \h 11Figure 9: Distribution of Total Commercial Building Floor Area by State/Territory, 2017 (‘000sqm, %) PAGEREF _Toc486081178 \h 12Figure 10: Distribution of Population by State/Territory, September 2016 (%) PAGEREF _Toc486081179 \h 12Figure 11: Realised AccuRate Ratings by State, 2014 – 2017 PAGEREF _Toc486081180 \h 15Figure 12: Cumulative Space Conditioning Energy Consumption of New Residential Buildings by Type, 2020 - 2050, Reference Scenario PAGEREF _Toc486081181 \h 16Figure 13: Cumulative Greenhouse Gas Emissions (Space Conditioning), New Residential Buildings by Type, 2020 - 2050, Reference Scenario PAGEREF _Toc486081182 \h 17Figure 14: Scenario 1: Space Conditioning Energy Savings by Dwelling Type, Australia PAGEREF _Toc486081183 \h 20Figure 15: Scenario 1: Space Conditioning Greenhouse Gas Emissions Savings by Dwelling Type, Australia PAGEREF _Toc486081184 \h 21Figure 16: Scenario 2: Space Conditioning Energy Savings by Dwelling Type, Australia PAGEREF _Toc486081185 \h 22Figure 17: Scenario 2: Space Conditioning Greenhouse Gas Emissions Savings by Dwelling Type, Australia PAGEREF _Toc486081186 \h 22Figure 18: Commercial Building Energy Consumption, 2020 - 2050 Cohort, Reference Scenario PAGEREF _Toc486081187 \h 26Figure 19: Commercial Building Greenhouse Gas Emissions, 2020 - 2050 New Building Cohort, Reference Scenario PAGEREF _Toc486081188 \h 26Figure 20: Commercial Building Energy Savings, 2020 - 2050 Cohort, Scenario 1 PAGEREF _Toc486081189 \h 27Figure 21: Commercial Building Greenhouse Emissions Savings, 2020 - 2050 Cohort, Scenario 1 PAGEREF _Toc486081190 \h 29Figure 22: Variability of Energy Consumption in Similar Houses (Lochiel Park, SA) PAGEREF _Toc486081191 \h 31Index of Tables TOC \h \z \c "Table" Table 1: Summary Indicators: Scenario 2 Residential and Scenario 1 Commercial PAGEREF _Toc486081192 \h ivTable 2: Identified Stock Totals, as a share of Nexis PAGEREF _Toc486081193 \h 5Table 3: Reference Fuel Mix by State and Territory, Residential Buildings PAGEREF _Toc486081194 \h 14Table 4: Electricity Full Fuel Cycle Greenhouse Gas Emissions Intensity by State and Territory to 2050, Selected Years PAGEREF _Toc486081195 \h 16Table 5: Percentage Reductions in Maximum Thermal Loads by Star Rating, relative to Current Baseline by State and Territory PAGEREF _Toc486081196 \h 18Table 6: Scenario 1 Energy and Greenhouse Savings PAGEREF _Toc486081197 \h 19Table 7: Scenario 2 Energy and Greenhouse Savings PAGEREF _Toc486081198 \h 19Table 8: Building Classes and Forms Simulated PAGEREF _Toc486081199 \h 23Table 9: Reference Climate Zones PAGEREF _Toc486081200 \h 23Table 10: Reference Energy Intensities by Building Class and State/Territory (MJ/m2.a) PAGEREF _Toc486081201 \h 24Table 11: Commercial Building Energy and Greenhouse Gas Emissions Savings – Scenario 1 PAGEREF _Toc486081202 \h 28Executive SummaryThis Report provides a companion document to the Code Calculator, a spreadsheet tool developed by Strategy. Policy. Research. that enables users to estimate energy and greenhouse gas savings associated with possible changes to energy performance requirements in the National Construction Code. In particular, users of the Calculator can simulate the effects of making changes to requirements for all building classes, and all states and territories, at regulatory windows that are expected to open in 2019, 2022, 2025 and 2028. The user can select options from simple drop-down lists, or input preferred values into key fields to vary default variables.While the outputs of the Calculator are dependent upon the input values selected, as an illustration, scenarios depicted in this Report show that energy consumption in 2050 could be some 300 PJ lower than under a reference scenario (in which current energy performance requirements continue through to 2050) – see REF _Ref486079091 \h Table 1. Similarly, cumulative greenhouse gas savings during the FY2020 – FY2030 period alone could amount to almost 55 Mt CO2-e ( REF _Ref486078999 \h Figure 1 and REF _Ref486079006 \h Figure 2). The Calculator does not examine the cost-effectiveness of savings.Table SEQ Table \* ARABIC 1: Summary Indicators: Scenario 2 Residential and Scenario 1 CommercialNCC ClassElectricity savings in 2030Gas savings in 2030Total energy savings in 2030GHG emissions savings in 2030Electricity savings in 2050Gas savings in 2050Total energy savings in 2050GHG emissions savings in 2050Cumulative total energy savings, 2020 - 2030Cumulative total ghg savings, 2020 - 2030PJPJPJMt CO2-ePJPJPJMt CO2-ePJMt CO2-eALL RESIDENTIAL:7.316.523.82.328.469.097.47.9113.111.6ALL COMMERCIAL:38.09.347.38.2161.839.1200.926.0229.743.1TOTAL:45.325.771.010.5190.2108.1298.233.9342.754.7Savings can be estimated individually for every Code building class and for each state and territory. Also, users can over-ride a large range of default variables, at the level of individual building classes and states and territories, for:Building stock growth ratesRefurbishment ratesFuel mixReference (NCC2016) energy intensitiesCoefficients of performance (COP) for electrical and gas space conditioning (residential)Average dwelling sizeGreenhouse gas intensities. For residential buildings, savings scenarios can be generated by star rating, in half-star increments, or by percentage changes from the previously-existing standard. For commercial buildings, savings scenarios are expressed as percentage reductions from previous regulatory standards.Figure SEQ Figure \* ARABIC 1: Residential Building Greenhouse Gas Emissions Savings by Dwelling Type, 2020 – 2050 Cohort, Scenario 2Figure SEQ Figure \* ARABIC 2: Commercial Building Greenhouse Emissions Savings, 2020 - 2050 Cohort, Scenario 1The report highlights some important uncertainties that would ideally (and in some cases are already intended to) be the subject of future research:The absolute size of the commercial building stock in Australia, in particular, with lesser uncertainties affecting our understanding of the size of the residential building stockThe rate of refurbishment and demolition/rebuild of all buildings in Australia – which is particularly important in that all ‘new building work’ should comply with the Code, and therefore contribute to anticipated energy and greenhouse gas emission savingsEvidence regarding the ‘performance gap’ between simulated and actual energy performance of all building types in Australia and, relatedly, the extent of compliance with existing Code energy performance requirements.BackgroundPurposeIn the context of the National Energy Productivity Plan, and specifically Item 31, Advancing the National Construction Code, the Department has a need to be able to estimate likely energy and greenhouse gas savings that could be realised by increasing energy performance requirements in the NCC over time, from both residential and commercial building forms. Given that the size of possible future Code changes in uncertain, an estimator tool, whereby different input values could be assessed, has been developed. This Report provides the technical background to the tool (‘the Code Calculator’). The tool itself includes a user guide, which is reproduced in Appendix A below.The report also highlights areas where there are uncertainties in the data and related methodological issues, and offers a number of recommendations to address these issues.Scope of WorkThe Code Calculator and this Report cover all Classes 1 – 9 in the Code, setting aside Class 4 (caretakers’ offices) and Class 10 (non-habitable buildings or structures). Results are presented by National Construction Code (the Code) building class.Separate results are generated for each state and territory, and for each building class.The Calculator does not attempt to examine the cost-effectiveness or technical feasibility of the scenarios specified by the user. As a result, the user must take care to specify realistic scenarios, and/or undertake additional work to determine the extent to which their scenarios are achievable and cost effective.Stock Turnover ModelIntroductionIn many ways, the core of Code Calculator is the building stock turnover model. The function of the model is to estimate the number of square metres of floor area, by building class, that is constructed to (or brought up to) the then-current Code requirements annually. The annual turnover includes:Net growth in floor area from year to year (eg, to accommodate a higher population/greater economic activity)Buildings/floor area demolished and rebuilt (noting that the replacement building may be of a different class)Extensions/additions to existing buildingsMajor refurbishments, sufficient to trigger the application of the Code energy performance requirements.Data Sources and UncertaintiesUnfortunately, there is considerable uncertainty about many of the key variables in this context. First, the total stock of buildings in Australia (number of square metres, or number of buildings) is not known with precision, and is highly uncertain for commercial buildings in particular. The reasons for this are explored below.Australian Bureau of Statistics DataThere is no statistical series that purports to describe the building stock in Australia. The Australian Bureau of Statistics (ABS) publishes several relevant inter-related series, including:8752.0 – Building Activity, Australia8755.0 – Construction Work Done, Australia8731.0 – Building Approvals, Australia.These are quarterly publications, where the underlying data sources are building approval data and returns from builders and other individuals and organisations engaged in building activity – including Councils and other authorities that provide building approvals. The data includes:Residential ‘jobs’ (projects) valued at $10,000 or moreNon-residential jobs valued at $50,000 or more. The ABS notes that since September 2010, direct data collection occurs for all building work having approval values of $5 million or more, while residential work of less than $50,000 in value, and non-residential work of less than $250,000, is modelled; while a sample survey is conducted of other identified building work.Depending upon the data series, the collections data back to between 1974 and 1987, and provide a reliable indication of the flow of quarterly activity. However, the key limitation is that what is reported is (primarily) the value of work done (by sector, state/territory, building type). The only volume-based indicator that is provided is the number of dwelling unit commencements/completions. No volume indicators at all are provided for non-residential work. The value of work indications include the value of alterations, additions and demolitions, in addition to new buildings, but these components are not separately identified. In short, the ABS data is not helpful for tracking physical activity, including stock turnover, for commercial buildings.For residential work, as noted, the number of commencements and completions is indicated, and detailed data cubes also provide indications of the value of alterations and additions, distinct from new construction. However, the floor area added or addressed by these jobs is not identified. ABS building classifications differ from those used in the National Construction Code. The ABS classification framework is based on primary purpose, or ‘intended major function’, while the origins of the Code’s building classes are unclear and, in some cases, anachronistic.Geoscience Australia NEXIS DatabaseGeoscience Australia has developed the National Exposure Information System (NEXIS) over 15 years, with a primary purpose of providing ‘…comprehensive and nationally consistent exposure information, enabling users to better understand the potential elements at risk in Australia’. It is essentially a database that…compiles publicly-available information, statistics, spatial and survey data to model exposure information about residential, commercial and industrial buildings, institutions (public), infrastructure assets and agricultural commodities.Figure SEQ Figure \* ARABIC 3: NEXIS Data LayersSource: The relevance of NEXIS in this context is that it purports to represent a comprehensive database of all buildings in Australia. It includes many data fields that are relevant to the building stock, including – for residential buildings – building counts, dwelling counts, building floor area; structural information such as construction type, roof type, wall type, etc; residential tenure; and other values. Residential buildings are divided into:Separate houses (which we equate with NCC Class 1a)i)Semi-detached houses (which we equate with NCC Class 1a)ii)Apartments (further divided into 2 storey, 3 storey and 4+ storey.For commercial buildings, it includes building counts, building floor area, construction type, no of storeys and other values. The data is resolved spatially down to the statistical local area 1 (SA1) or local government area (LGA).Limitations of this database, however, include:It includes total stock values, but no stock turnover information (opposite of ABS data)The ‘snapshot’ year represented by the database is not clear – given the use of many different data sources, it is likely to represent a composite of recent years. Metadata refers to 2015.Single storey apartment buildings are not mercial (and industrial) buildings are undifferentiated by type or class, and the boundaries between commercial and industrial buildings are not made clear.Values do not appear to have been validated against other sources, or if so, this work has not been published.Noting the final point above, a key issue with this data source is that its observation for the total stock of commercial buildings does not agree with other sources, as discussed in the 2012 Commercial Building Baseline Study. In short, based on this study, and the range of sources that it drew on (BIS Shrapnel, Jones Lang Lasalle, past RIS stock models commissioned by the former Department of Environment, Water, Heritage and the Arts, state governments), we can only account for between 32% and 65% of the totals shown in NEXIS at the state level, and 43% in total.Table SEQ Table \* ARABIC 2: Identified Stock Totals, as a share of NexisState/Territory2016NSW 51.4%VIC39.0%QLD39.5%SA32.4%WA54.7%TAS28.7%NT65.3%ACT58.1%TOTAL:43.3%While we have not been able to further investigate this discrepancy in the course of this project, it is scheduled to be addressed in the context of work being undertaken by Strategy. Policy. Research., CSIRO, Energy Action and others for ASBEC, in the context of the Code Trajectory project. In particular, we will seek consultations with Geoscience Australia and commercial service providers to attempt to at least close the gap to the extent possible, if not resolve the discrepancy entirely.In this project, we assume that the unidentified commercial buildings exist, but are simply unidentified by type. Therefore, we group them together as ‘other commercial’ buildings and, as discussed further below, assign energy intensity to them based on the average of all identified classes. Residential BuildingsOur overall approach to modelling residential building stock turnover is:2015 total floor area is derived from NEXIS, and backcast (to 2001) and forecast (to 2050) using annual growth rates derived as described belowHistorical (pre-2011) stock observations are derived from ABS Census data for dwelling structures (2001, 2006 and 2011), with linear interpolation of intervening yearsDefault or reference stock growth rates (2011 – 2036) are derived from ABS Household and Family ProjectionsStock growth rates in the 2001 – 2011 period are implied from the Census data, as above, while stock growth rates post 2036 are assumed to remain constant at their 2036 levels through to 2050Annual floor area built to Code is estimated as a function of the change in total dwelling stock from year to year, together with an allowance of 1% of the total stock (as a default value) for demolition/rebuild, additions and major refurbishment activity.As noted, the reference or default rate of dwelling stock growth is generated from ABS projections of the growth in households, using the Household and Family Projections series. To convert household growth to dwelling growth, we assume that family and group households occupy 80% of Class 1 dwellings and 20% of Class 2 dwellings, while 100% of lone person households are assumed to occupy the balance of Class 2 dwellings. This enables projections to be made of the average expected growth rate for Class 1 dwellings (same rate assumed for detached and semi-detached) and Class 2 dwellings by state/territory. In the Code Calculator, stock growth rates can be varied for each class in 'Settings by class'.This methodology generates the following pictures of total residential building stock (floor area in ‘000 sqm), and of annual floor area built to Code (‘000 sqm). Note that the stock is resolved at state/territory level in the Code Calculator, while national totals only are shown in figures for readability. The data indicates a total stock in 2017 of 8.65 million dwellings, with a total floor area of around 2.2 billion sqm (implying an average dwelling size of 258 sqm), and some 79 million sqm being built to Code annually (and rising annually). Of the 2017 residential stock, 86.7% of the floor area is detached dwellings, 5.0% semi-detached dwellings and 8.3% apartment units. By 2050, the total residential stock is projected to rise to some 13.7 million dwellings, with the share of apartments in that year rising to 9.1%, at the expense of detached dwellings (85.9%), while semi-detached dwellings are projected to remain at 5% of the total. Figure SEQ Figure \* ARABIC 4: Residential Building Stock Totals by Type, 2001 – 2050, AustraliaFigure SEQ Figure \* ARABIC 5: Annual Floor Area Built to Code, Residential Buildings by Type, 2002 – 2050, Australia Figure SEQ Figure \* ARABIC 6: Distribution of Total Residential Stock by State and Territory, 2017 (‘000 sqm, %)Commercial BuildingsThe absence of useful ABS data, and the availability of only summary NEXIS data, necessitated a different approach to modelling the stock of commercial buildings. Broadly:The 2001 – 2020 stock of all classes that are identified in the Commercial Building Baseline Study is taken from that source – this in turn reflects data from BIS Shrapnel, BZE and many other sources – see that reference for detailsThe stock model is organised by NCC building class, and by state/territoryDefault growth rates for 2020 – 2050 are the average of those revealed in the 2001 – 2020 data above, with the implicit assumption that stock shares remain the same over time. Growth rates can be varied by building class in the CalculatorAs with residential buildings, we assume that 1% of the total stock is demolished/rebuilt, or undergoes major refurbishment, annually.Regarding specific commercial building classes:Identified Class 3 buildings (accommodation) reflect Baseline Study values for hotels only – therefore it is likely that some part of the unidentified ‘other commercial’ stock are other accommodation buildings, including potentially serviced apartments (although these are likely to be classified as Class 2s), hostels, motels, boarding houses and the like.Office buildings (Class 5) are sub-divided into standalone (or primary purpose) offices and non-standalone offices (office spaces in mixed use buildings, with an observation of total offices, as per the Baseline Study.Retail buildings (Class 6) are sub-divided into retail strips, supermarkets and shopping centres (net of supermarkets in shopping centres), and total retail, again following the Baseline study and other sources such as BZE. This is another where is it possible that some retail buildings (such as big box retail, stand-alone hardware retail, etc) could be contained within the ‘other commercial’ category.Class 7 warehouses were not resolved in the Baseline Study. For the Calculator, we have sourced a 2013 observation of the warehouse stock from the BZE Buildings Plan, and assumed that the default growth rate for this building class is the same as for total retail (on the grounds that they are likely to be broadly proportionate). Class 8 laboratories were similarly not resolved in the Baseline Study, and we are not aware of any valid national data source for this building type. Here we have made the assumption that the floor area of laboratories is equivalent to 20% of the floor area of tertiary education buildings.Class 9 buildings in the Code are a highly diverse mix of broadly ‘public’ or ‘institutional’ buildings. We resolve ‘healthcare’ buildings (9a) using the Baseline Study, but this is based primarily on hospitals, and therefore it is likely that numerous other healthcare buildings (clinics, doctor’s surgeries, specialists’ rooms, etc) are counted in ‘other commercial’. 9b education/assembly buildings are subdivided in to schools, universities, vocational education and training (VET), public buildings (such as galleries, libraries and museums) and total education/assembly, following the Baseline Study9c aged care facilities were sourced from the Baseline StudyTotal class 9 sums the above‘All identified commercial stock’ sums the above classes‘All commercial buildings’ are taken as the NEXIS total commercial buildings (for 2015)‘Other commercial buildings’ represent the difference between all commercial buildings and all identified commercial stock.This methodology indicates that the 2017 commercial building stock is distributed by NCC class as shown in REF _Ref485982090 \h Figure 7 below. As discussed in Section 2.2 above, it is regrettable that 57% of the total commercial building stock is not currently identified by class. Given their large share, these buildings are included in the Calculator, but in a generic manner. A key opportunity to enhance the Calculator would be to resolve some of all of the ‘other’ class into the appropriate NCC classes. REF _Ref485982356 \h Figure 8 shows the historical and reference future growth in the total commercial building stock by NCC class. This indicates that, in line with NEXIS, the total commercial building floor area in 2017 was some 655 million sqm, and this figure is projected to virtually double over the period to 2050, to some 1.24 billion sqm. Figure SEQ Figure \* ARABIC 7: Distribution of Commercial Building Floor Area by NCC Class, Australia, 2017 (‘000 sqm, %)Figure SEQ Figure \* ARABIC 8: Total Commercial Building Stock by Class, Australia, 2001 - 2050 REF _Ref485982848 \h Figure 9 below shows the distribution of all commercial building floor area by state and territory while, for comparison, REF _Ref485983527 \h Figure 10 shows the distribution of Australia’s population by state and territory (as at end September 2016). This indicates that there is a relatively higher share of commercial buildings than population in Victoria, in particular, but also Tasmania, while the reverse is true for most other states, reflecting differences in population density.Figure SEQ Figure \* ARABIC 9: Distribution of Total Commercial Building Floor Area by State/Territory, 2017 (‘000sqm, %)Figure SEQ Figure \* ARABIC 10: Distribution of Population by State/Territory, September 2016 (%)Residential Building ProjectionsBaseline ProjectionsThe conceptual baseline for the reference case is that the current (NCC2016) energy performance requirements remain in place throughout the modelled period which is from 2010 to 2050. This is consistent with a ‘business as usual’ or ‘frozen policy’ scenario, in which no policy changes are assumed as the baseline case, for clarity of comparison.Scope of End-UseThe energy consumption modelled for residential building forms is only that associated with space conditioning. In discussions with the Department, it was noted that other end-use such as appliances and ‘plug load’ are not affected by Code changes, and therefore are not relevant to estimating Code-related savings. For fixed appliances, such as hot water and lighting (and minor one such as pool and spa pumps), which are regulated by the Code, there was concern firstly about the extent to which Code changes in these areas would be additional to future appliance/equipment minimum energy performance standards. Second, it was noted that Code performance requirements for this end-uses may move independently from thermal performance standards (star ratings), and therefore should be considered separately from thermal shell performance. As a result, the model calculates the energy use, and savings, for space conditioning only.Fuel MixA second consideration for the baseline projection is the fuel mix, and in particular the fuel mix that is relevant to new builds, as distinct from the average in the existing stock. We began by sourcing average 2016 fuel consumption data by state and territory from Australian Energy Statistics (Table F), and resolving three fuel classes: electricity, gas + LPG, and wood + solar (ghg emissions free). While the Calculator enables the user to vary the default fuel mix values, we have taken the view that a) wood is very unlikely to play a significant heating role in the new housing stock and b) the share of solar energy is best captured via the greenhouse gas intensity of electricity consumption (see below). Therefore we re-assigned the wood/solar share to electricity for the reference projections. Note that the fuel mix varies considerably by state, and we do not attempt to resolve how it may vary by residential building type. Table SEQ Table \* ARABIC 3: Reference Fuel Mix by State and Territory, Residential BuildingsState/TerritoryElectricity ShareGas ShareNSW75.9%24.1%VIC33.7%66.3%QLD87.2%12.8%SA63.2%36.8%WA72.4%27.6%TAS59.9%4.3%NT87.6%12.4%ACT75.9%24.1%Source: derived from Australian Energy Statistics Table FThe Calculator assumes that the fuel mix (in new dwellings) does not change through time. This is, of course, debateable. Many believe that the combination of higher heat pump coefficients of performance (COP), declining heat pump costs, rising gas prices (although electricity prices have risen strongly too), a continuation of the swing towards solar PV generation on residential roofs – at lower costs through time, due to falling PV panel prices – and rising concerns about greenhouse gas emissions, all suggest that increasing electrification of the (new) housing stock is highly likely. The user of the Calculator can select any fuel mix desired, to simulate the effect of different assumptions here. Note that the general effect of assuming a higher electricity mix is that energy consumption would be lower in the reference scenario, and also lower in ‘with measures’ scenarios, given higher coefficients of performance for heat pumps than gas space heaters.Space Conditioning Equipment/COPsThe Calculator assumes a fixed COP for gas space heating of 0.85. This means that 1/0.85 (or 1.12) units of gas are consumed for each unit of thermal heating requirement. For electrical space conditioning, we assume relatively conservative values for COP of 2.5 (pre-2020), 2.75 from 2020 to 2022, 3.0 from 2023 to 2025, 3.25 from 2026 to 2028, and 3.5 thereafter. These values can be altered in the Calculator if desired.Energy IntensityGiven that our focus is on space conditioning energy consumption associated with thermal performance requirements in the Code, reference energy intensities are derived from NatHERS star bands, sourced from the NatHERS website. The steps involved in this process included:Compiling weighted average maximum thermal load caps by state and territory, by weighting the results for 69 individual climate zones based on the population shares of each climate zone by state, following the methodology outlined in the 2008 Residential Baseline StudySelecting baseline values at 6 star for all jurisdictions except for NT, which remains at 5 star, and NSW, which has been shown to be achieving around 4.5 star on average under its BASIX scheme (see Figure 11 below). Figure SEQ Figure \* ARABIC 11: Realised AccuRate Ratings by State, 2014 – 2017Source: NatHERS websiteGreenhouse Gas IntensitiesHistorical greenhouse gas intensities of fuel consumption are sourced from the NGA Factors Workbook 2016. For gas, we used a value of 51.4 kg CO2/GJ – overlooking the minor contribution of LPG with its higher intensity of 60.2 kg CO2/GJ. For electricity, we used historical factors from this same source (see Table 4 below), while default projections are made by simple linear extrapolation. The Calculator allows different rates of change to be assumed for each state and territory if preferred.Table SEQ Table \* ARABIC 4: Electricity Full Fuel Cycle Greenhouse Gas Emissions Intensity by State and Territory to 2050, Selected Years2010201120122013201420152020203020402050NSW278277276271267265253230210191VIC376371372362346330292228178139QLD277270262260260262248223200179SA221212201192182177144966443WA25124123323122522019415111892TAS92786651353737373737NT220216217214213213206194182170ACT278277276271267265253230210191Baseline Energy Consumption and Greenhouse Gas Emissions REF _Ref485995146 \h Figure 12 below indicates the space conditioning energy expected to be consumed by the cohort of new residential buildings built from FY2020 to FY2050, under reference or business as usual conditions. By 2050, this additional energy consumption would amount to some 124 PJ across all three dwelling types. REF _Ref486000890 \h Figure 13 shows the same data but converted into greenhouse gas emissions, using the factors noted above, with 2050 emissions reaching almost 10 million tonnes of carbon dioxide equivalent.Figure SEQ Figure \* ARABIC 12: Cumulative Space Conditioning Energy Consumption of New Residential Buildings by Type, 2020 - 2050, Reference ScenarioFigure SEQ Figure \* ARABIC 13: Cumulative Greenhouse Gas Emissions (Space Conditioning), New Residential Buildings by Type, 2020 - 2050, Reference ScenarioPolicy ScenariosApproachThe Calculator is designed to enable users to estimate energy and greenhouse gas savings associated with user-selected Code stringency changes in each of four regulatory windows: 2019 (assumed to take effect during FY2020), 2022, 2025 and 2028. The Calculator applies any changes specified, with the assumption that once applied, the changes remain in place, indeed right through to 2050, unless later changes are specified by the user. So if the user selects 7 star in 2019, and no other values, then the Calculator assumes that 7 star applies for all new dwellings through to 2050.The calculation engine is the change in maximum thermal loads associated with specific NatHERS star ratings, relative to the reference case, for each state and territory. Table 5 below shows these percentage reductions for each half-star from 6.5 to 10 star. Savings associated with the step to 6.5 star, for example, are higher for NSW and NT, given their lower starting points. Given that there are more dwellings constructed in NSW annually than in any other state, this result is significant at a national level.Table SEQ Table \* ARABIC 5: Percentage Reductions in Maximum Thermal Loads by Star Rating, relative to Current Baseline by State and TerritoryStar Rating6.577.588.599.510NSW40.6%49.1%57.7%66.1%74.4%82.4%89.4%95.2%VIC14.0%27.3%40.3%53.5%65.9%78.3%89.4%98.8%QLD11.0%20.7%30.4%40.8%50.2%59.3%67.9%75.2%SA13.5%27.1%39.8%52.5%65.8%77.5%88.8%97.4%WA12.7%25.3%36.8%50.2%62.7%74.0%84.9%92.7%TAS13.7%27.1%40.7%54.1%67.1%79.7%90.8%99.8%NT24.2%32.2%40.2%47.9%55.4%62.5%68.5%73.8%ACT13.9%27.3%40.0%53.3%66.1%78.8%89.7%98.8%The Calculator allows the user to specify the star rating requirements assumed to apply in future periods, or else any user-defined % change value. In the latter case, a % change in 2025, for example, is expressed relative to the previously applied standard, and not to the reference case. For example, if a 50% reduction were specified for 2019, and a further 50% reduction in 2022, the total reduction in 2022 relative to 2016 would be 75%, not 100% (X * (1 - 50%) * (1 - 50%) = X * 25%).User-Defined OptionsIn addition to the desired star rating or % change in the previous energy performance standard, the Calculator allows the user to vary default values, for each building class and for each state and territory, for:Fuel mix (mix of electricity, gas/LPG and wood/solar)Average heat pump COPs for each regulatory window.Gas COP can be varied, but whichever value is selected remains constant over time (given an expectation of very little change in gas space conditioning energy efficiency over time)The rate of change in average new dwelling size (default is set to -0.2% per year for all residential classes)The annual demolition/rebuild and major refurbishment rate (defaults to 1% per year)The rate of growth in the building stock.The latter function is set up as a drop-down list of incremental growth values, from -2% per year to +2% per year, in half percentage point increments, relative to the default values. Thus, if the default growth rate for a particular state is 1% per annum, selecting ‘+2%’ makes the growth rate 3% (1% + 2%), while selecting ‘-2%’ makes the growth rate -1% (1% - 2%).As noted above, the annual rate of change in greenhouse intensity of electricity supply in each state and territory can also be selected by the user.Table SEQ Table \* ARABIC 6: Scenario 1 Energy and Greenhouse SavingsNCC ClassElectricity savings in 2030Gas savings in 2030Other Fuel Savings in 2030Total energy savings in 2030GHG emissions savings in 2030Electricity savings in 2050Gas savings in 2050Other Fuel Savings in 2050Total energy savings in 2050GHG emissions savings in 2050Cumulative total energy savings, 2020 - 2030Cumulative total ghg savings, 2020 - 2030Cumulative total energy savings, 2020 - 2050Cumulative total ghg savings, 2020 - 2050PJPJPJPJMt CO2-ePJPJPJPJMt CO2-ePJMt CO2-ePJMt CO2-eDetached4.5910.510.0015.101.4816.6641.130.0057.804.6577.167.92812.6771.26Semi-detached0.260.620.000.890.080.962.450.003.400.274.520.4547.774.10Apartments0.530.950.001.480.161.953.840.005.800.527.500.8680.647.94ALL RESIDENTIAL:5.412.10.017.51.719.647.40.067.05.489.29.2941.183.3Table SEQ Table \* ARABIC 7: Scenario 2 Energy and Greenhouse SavingsNCC ClassElectricity savings in 2030Gas savings in 2030Other Fuel Savings in 2030Total energy savings in 2030GHG emissions savings in 2030Electricity savings in 2050Gas savings in 2050Other Fuel Savings in 2050Total energy savings in 2050GHG emissions savings in 2050Cumulative total energy savings, 2020 - 2030Cumulative total ghg savings, 2020 - 2030Cumulative total energy savings, 2020 - 2050Cumulative total ghg savings, 2020 - 2050PJPJPJPJMt CO2-ePJPJPJPJMt CO2-ePJMt CO2-ePJMt CO2-eDetached6.2114.330.0020.542.0024.1459.850.0083.996.7597.809.971152.79100.61Semi-detached0.350.850.001.200.121.393.560.004.950.395.730.5767.785.78Apartments0.711.310.002.020.222.835.600.008.430.769.531.09114.5711.23ALL RESIDENTIAL:7.316.50.023.82.328.469.00.097.47.9113.111.61335.1117.6Indicative ResultsThe following results are shown as an illustration of the Calculator’s output, noting that the results generated are entirely contingent upon the input values selected by the user.Scenario 1: 7 star in 2019, and half-star increments thereafterThis scenario assumes that all residential classes, in all states and territories, move to a 7 star requirement in 2019, 7.5 star in 2022, 8 star in 2025 and 8.5 star in 2028 and thereafter. As shown in REF _Ref486081089 \h Table 6 above, and also in REF _Ref486081418 \h Figure 14 and REF _Ref486081425 \h Figure 15 below, this scenario generates energy savings that reach 67 PJ by 2050 and cumulative greenhouse gas emissions savings over the FY2020 – FY2030 period of 9.2 Mt.Figure SEQ Figure \* ARABIC 14: Scenario 1: Space Conditioning Energy Savings by Dwelling Type, AustraliaFigure SEQ Figure \* ARABIC 15: Scenario 1: Space Conditioning Greenhouse Gas Emissions Savings by Dwelling Type, AustraliaScenario 2: 7 star in 2019, 8 star in 2022, 9 star in 2025, 10 star in 2028The results of this more ambitious scenario are shown in REF _Ref486058520 \h Table 7 (above) and REF _Ref486058578 \h Figure 16 and REF _Ref486058584 \h Figure 17 below. In this scenario, energy consumption in 2050 is 97 PJ lower than in the reference scenario, while cumulative greenhouse emissions savings over the FY2020-FY2030 period reach 11.6 million tonnes.Figure SEQ Figure \* ARABIC 16: Scenario 2: Space Conditioning Energy Savings by Dwelling Type, AustraliaFigure SEQ Figure \* ARABIC 17: Scenario 2: Space Conditioning Greenhouse Gas Emissions Savings by Dwelling Type, AustraliaCommercial Building ProjectionsBaseline ProjectionsScope of End-Use and Energy IntensityThe scope of commercial energy consumption covered by the Calculator is the same as that covered by the National Construction Code. The energy intensity of different building forms in different climate zones is sourced from Energy Action’s recent work for the Australian Building Codes Board in the context of proposed changes to Section J (energy performance requirements) in 2019. This work simulates the energy performance of a range of building forms and types in each of the eight NCC climate zones, using reference building assumptions as set out in JV3, and other assumptions as noted in this reference – see REF _Ref486063816 \h Table 8 and REF _Ref486063881 \h Table 9 below.Table SEQ Table \* ARABIC 8: Building Classes and Forms SimulatedTable SEQ Table \* ARABIC 9: Reference Climate ZonesThe scope of energy consumption modelled includes heating, ventilation and air conditioning (HVAC); lighting and other (fixed equipment). Energy not included comprises lifts, escalators, and office equipment (although see below). The simulated energy performance of these building forms is a function of choices made with respect to structural elements and materials, glazing, internal loads (which in turn reflect assumptions about occupancy and ‘plug loads’ (eg, office equipment), as documented in the reference), heat gain from lighting choices and operating schedules. Results are generated in MJ/m2.a for each form and climate zone. Given the purpose of Energy Action’s modelling, we can be confident that they accurately reflect the ‘regulated’ energy consumption of NCC2016-compliant buildings – albeit, as discussed further below, the energy intensities appear low compared to actual buildings.As with residential buildings, energy intensities for each form by climate zone needed to be mapped to states and territories, and the same approach was used for this task as described in Section REF _Ref486064695 \n \h 3.1.4 above. This resulted in the following reference energy intensities by building class and state/territory ( REF _Ref486064858 \h Table 10).Table SEQ Table \* ARABIC 10: Reference Energy Intensities by Building Class and State/Territory (MJ/m2.a)Accommo-dation (Hotels)OfficesRetailWarehouseLaboratoryHealthcareEducationAged careOther commercialNSW183353574182465381210320334VIC186334570176441365203335326QLD227424705237519468307368407SA181358572183472385210313334WA189365593190478396226323345TAS200332583178436360215336330NT285494856291603547412474495ACT200332583178436360215336330We note that these values appear low relative to actual buildings. For example, an office (whole building) in Sydney that consumed 353 MJ/m2.a would have a NABERS rating around 5.8, depending upon assumptions regarding fuel mix, number of computers per floor etc, while NCC2016 is more generally understood to deliver office buildings of around 4.5 star. It is likely that the gap between the simulated results, and those identified in NABERS ratings of actual buildings, primarily reflects the reduced scope of energy consumption simulated, but could also indicate that the simulation process is under-estimating real-world energy consumption. To the extent that this occurs, the absolute amount of energy savings estimated by the Calculator could be too low, although the proportionate reductions (% change) should not be affected by any inaccuracies in the reference data. Generally, our assessment is therefore that the energy and greenhouse savings totals generated by the Calculator are quite conservative. The user of the Calculator can specify different energy intensity values than those above to test the sensitivity of results to this factor.Fuel MixThe fuel mix by building type and state/territory was primarily sourced from the Commercial Building Baseline Study. For classes not represented in that reference, eg, warehouses, we assumed 100% electricity consumption, while for laboratories we based on estimate on education buildings (71% electricity). A different fuel mix can be specified by the user if desired for each building type and state and territory.Other User-Defined VariablesAs for residential buildings, for commercial buildings the user can specify non-default values, for each state and territory and building type, for:Annual stock growthAnnual demolition/rebuild and major refurbishment rateNCC2016 energy intensityGreenhouse intensity factors.Baseline Energy Consumption and Greenhouse Gas EmissionsThe values and method above result in the following projection of the baseline or reference energy consumption of the cohort of new buildings (including rebuilds and major refurbishments) from FY2020 to FY2050. The key assumption is that NCC2016 energy performance requirements continue to apply throughout this period. By 2050, this cohort of buildings would be consuming some 306 PJ of energy, and generating almost 40 Mt CO2-e.Figure SEQ Figure \* ARABIC 18: Commercial Building Energy Consumption, 2020 - 2050 Cohort, Reference ScenarioFigure SEQ Figure \* ARABIC 19: Commercial Building Greenhouse Gas Emissions, 2020 - 2050 New Building Cohort, Reference ScenarioPolicy ScenariosAs with residential buildings, policy windows are assumed to be open in 2019, 2022, 2025 and 2028, with any Code changes taking effect from the following financial year. The user is invited to identify potential reductions in NCC2016 Code energy performance requirements in percentage terms. As before, a reduction applied in one regulatory window is assumed to continue through to 2050, unless modified by a subsequent change. Where subsequent percentage changes are applied, the percentage reduction applies to the standard applying in the previous regulatory period, and not (necessarily) to that applying in the baseline.Scenario 1: 40% reduction in 2019; 50% in 2025This scenario models a 40% reduction relative to NCC2016 from FY2020 to FY2025, and a further 50% reduction (relative to NCC2019) from FY2026. Following the logic above, this means that from FY2026, the required standard would be 70% lower than in 2016 (X * (1-40%) * (1-50%) = X * 30%).Results for this scenario are shown in REF _Ref486070233 \h Table 11 below. By 2050, over 200 PJ of energy consumption would be avoided, representing a substantial two thirds of the reference energy consumption for this cohort. Cumulative emissions savings over the FY2020 – FY2030 period would be greater than 43 Mt CO2-e. See also REF _Ref486071173 \h Figure 20 and REF _Ref486071182 \h Figure 21 below.Figure SEQ Figure \* ARABIC 20: Commercial Building Energy Savings, 2020 - 2050 Cohort, Scenario 1Table SEQ Table \* ARABIC 11: Commercial Building Energy and Greenhouse Gas Emissions Savings – Scenario 1NCC ClassElectricity savings in 2030Gas savings in 2030Other Fuel Savings in 2030Total energy savings in 2030GHG emissions savings in 2030Electricity savings in 2050Gas savings in 2050Other Fuel Savings in 2050Total energy savings in 2050GHG emissions savings in 2050Cumulative total energy savings, 2020 - 2030Cumulative total ghg savings, 2020 - 2030Cumulative total energy savings, 2020 - 2050Cumulative total ghg savings, 2020 - 2050PJPJPJPJMt CO2-ePJPJPJPJMt CO2-ePJMt CO2-ePJMt CO2-eHotels0.220.11-0.330.050.850.43-1.290.151.740.2718.002.33Offices5.150.57-5.721.1222.542.48-25.023.6628.605.84330.6455.00Retail8.450.93-9.381.8036.424.00-40.425.8446.909.44537.8788.30Warehouses1.680.00-1.680.357.190.00-7.191.110.841.851.2516.97Laboratories0.140.06-0.200.030.590.24-0.840.101.040.1811.341.57Healthcare0.410.42-0.820.101.561.61-3.170.324.280.5744.394.98Education/ Assembly2.010.82-2.820.468.433.45-11.881.4614.192.39159.7422.22Aged care0.630.26-0.890.142.901.18-4.090.504.420.7552.807.31Other commercial19.306.10-25.404.1281.3025.69-106.9912.83127.6721.761,437.86197.66ALL COMMERCIAL:38.09.3-47.38.2161.839.1-200.926.0229.743.12,593.9396.4Figure SEQ Figure \* ARABIC 21: Commercial Building Greenhouse Emissions Savings, 2020 - 2050 Cohort, Scenario 1Uncertainties and Further ResearchBuilding StockAs noted in Section REF _Ref486073793 \n \h 2.2, the primary uncertainty in estimating Code-related energy and greenhouse gas savings is the significant divergence in observations about the total size of the commercial building stock in particular. NEXIS is regarded as an authoritative source – and is relied upon by emergency services in particular – and yet it lacks resolution of bot commercial building types and of (all) building turnover rates, and is not easily relatable to other and more closely resolved data sources. As noted, NEXIS indicates a total commercial building stock some 50% greater than other sources.As referenced earlier, a forthcoming research project commissioned by ASBEC and others, including the CRC for Low Carbon Living – in the context of identifying an optimal long-term trajectory for Code energy performance settings – will research this issue further. Through collaborating with Geoscience Australia, CSIRO, the Australian Bureau of Statistics and commercial data service providers, Strategy. Policy. Research. hopes to at least reduce uncertainty in this area, and ideally produce a fully-reconciled stock model.While a second-order issue, we also noted in Section REF _Ref486074329 \n \h 2.3 that a combination of NEXIS and ABS data suggests an unreasonably high value for average dwelling size in Australia. This issue will also be investigated further in the context of the trajectory project.Refurbishment/Demolition Rate, and Building ComplianceThe rate of demolition and rebuild, refurbishment, addition/extension to existing buildings – that is, square metres of floor area treated by building type and location – is largely unknown in Australian statistical collections. This despite the fact that every demolition, rebuild and addition/extension, and at least some refurbishments, in Australia requires a building approval, and often a development approval as well. As a result, we can be confident that the information exists, but it is not being collated or reported in a useful form. The importance of this information is that, in principle (but see below), all ‘new building work’ should be complying with the energy performance requirements (inter alia) of the National Construction Code, and thereby realising significant and cost-effective energy and greenhouse gas emissions savings. In the case of a major refurbishment, and subject to varying state-based requirements, there is also a threshold level of building refurbishment work (often 50% within a three-year period) where, in principle, the whole of the building is required to comply with the then-current performance requirements.In addition to a lack of statistical information – which, if available, would assist with auditing and verifying Code compliance – there is a strong view within the Australian building industry that Code energy performance requirements are not being complied with on a systematic basis. The 2014 National Energy Efficient Buildings Project – Phase 1 Report (pitt&sherry) involved consultations with over 1000 stakeholders in this sector, in every state and territory, including regional centres in addition to capital cities, and the concern about a lack of Code compliance was a strong and consistent theme in all regions. Despite this report three years ago, to our knowledge, no jurisdiction in Australia has undertaken any compliance audits with Code energy performance requirements. This fact appears to uphold the view of one state building authority employee, reported in the NEEBP Report, that ‘no-one cares and no-one’s looking’. Given that other industry feedback documented in that report extended to allegations of product substitution, and use of non-conforming products – and particularly in the wake of the Grenfell Building fire in the UK, and similar fires in Australia – it is remarkable that compliance auditing is not being undertaken.Greater attention to capturing meaningful statistical information from planning authorities, regarding the nature and area of work undertaken by the building industry – and not simply the value of that work – and greater attention to auditing performance outcomes associated with that work, would significantly lift confidence in estimates of energy performance and greenhouse gas emissions outcomes actually being achieved in the building industry. Reference Energy IntensitiesFinally, as noted in Section REF _Ref486075759 \n \h 4.1.1, it would appear to be the case that simulations of NCC2016 compliant building forms are reporting energy intensities that are well below values actually encountered in the real world. Whether this relates to simple differences in the scope of energy modelled, problems with simulation modelling, real world as distinct from modelled occupant behaviours and building usage patterns, building control issues, inadequate building commissioning, and/or other issues, is not immediately clear. However, the ‘performance gap’ is an internationally reported phenomenon, with some sources citing evidence of buildings using 5 – 10 times their compliance calculations.,, This issue may also be relevant for residential buildings, but here the primary source of a ‘gap’ between modelled and actual energy consumption is more readily explained by occupant behaviours in particular and, in the short term, weather and climate events. REF _Ref486077518 \h Figure 22 from an analysis of very similar, 7.5-star houses in Lochiel Park in South Australia, illustrates this phenomenon. However, commercial buildings in principle should be less sensitive to both effects, given their generally much larger size and the dominance of internal loads.While not essential for the Calculator, there is uncertainty about the gap between modelled and actual building performance in Australia, which could be explored alongside the question of compliance with energy performance requirements, as noted above.Figure SEQ Figure \* ARABIC 22: Variability of Energy Consumption in Similar Houses (Lochiel Park, SA)Source: Appendix A: User GuideOverviewThe Calculator was commissioned by the Australian Government Department of the Environment & Energy to enable easy quantification of the expected energy and greenhouse gas emissions savings that would arise given user-supplied assumptions about possible changes to the energy performance requirements in the National Construction Code (NCC) in the regulatory windows of 2019, 2022, 2025 and 2028.Key input variables are, for residential buildings, either specific NatHERS star ratings in each regulatory window, or else percentage savings (over the last regulatory window); while for commercial buildings, the key input variables are percentage changes in reference building energy consumption in each regulatory window. These variables can be inputted in the Control Panel tab. Key outputs include energy savings by fuel type, and greenhouse gas savings, in 2030 and 2050; and cumulative energy and greenhouse gas savings over the 2020 - 2030 and 2020 - 2050 periods; for each building type, for total residential buildings, for total commercial buildings, and for all buildings. These outputs can be viewed in the Control Panel tab.In addition to the input variables named, the user may (but does not need to) vary numerous other parameters - for individual building types and for individual states & territories - in the Settings by Class tab. For further information, see User Guide below.Basic FunctionsAll key inputs and outputs can be found on the Control Panel tab. At the top of that tab there is a summary table of total residential, commercial and combined energy and emissions savings - reflecting the input variables pre-selected, or selected by the user, in the light blue shaded cells for each building class.For each residential building class, the user can input a desired % reduction in energy performance requirements (the underlying metric is the maximum thermal energy loads in MJ/m2.a - see Technical Notes below for details) in each regulatory window (2019, 2022, 2025 and 2028). Do this by clicking on the Control Tab panel, and typing in your preferred % reduction in the light blue cells at Row 16 for Class 1ai detached houses, Row 29 for Class 1aii semi-detached dwellings, and Row 33 for Class 2 apartment dwellings. In addition, or alternatively, the user may select different star rating requirements from the drop-down lists in the light blue cells in Row 27, 31 and 44. Note that if the user wishes to see the effect of assuming that, for example, 7 star applies in each regulatory period, then 7 star must be selected for all four regulatory windows. At present, the model assumes that the setting selected in 2028 applies through to 2050. Energy and greenhouse savings are shown by building class in the same rows as noted above (for the light blue boxes), in Columns K - V. Total residential savings are shown at the top of the Control Panel tab, in I4:V9. Note that the user must select whether to view total residential savings calculated using either percentage changes or star ratings, but not both, as the two are not additive. Do this by choosing from the drop-down list at F7 on the Control Panel. Note that Version 5 assumes NSW (BASIX) baseline equivalent to 4.5 star, and NT at 5 star.For commercial buildings, the user can set the desired % reduction in the current or previous period's (estimated) reference building requirement for each commercial building class. To do this, click on the Control Panel tab, and enter your preferred percentage reductions in the light blue boxes at Row 51 to 49. As above, if the user wishes to see the effect of a one-off reduction of, say, 40% in 2019, then 40% must be entered into the light blue boxes for all commercial building classes.Detailed Results by State/Territory, Building Type, Year and FuelDetailed results by building type and state/territory can be viewed - for the scenario created by the settings selected in the Control Panel - by clicking on the relevant tabs and reviewing the data presented. For a detailed view of the savings for residential buildings, click on:Residential Baseline, to view baseline projections assuming 6 star remains in place throughout the whole projection period;Residential with measures (%) to see the effect of the selected percentage savings (specified in Rows 16, 29 and 33 of the Control Panel) on fuel use and emissions by year and state and territory and for each residential building type;Residential Savings (%) to see just the savings, or the differences between the values shown in the Residential Baseline and the Residential with measures (%);Residential with measures (star) to see the effect of the star ratings (specified in Rows 27, 31 and 44 of the Control Panel) on fuel use and emissions by year and state and territory and for each residential building type;Residential savings (star) to see just the savings, or the differences between the values shown in the Residential Baseline and the Residential with measures star).For commercial buildings, similar information may be found for all commercial building classes in:Commercial BaselineCommercial with measures (%); andCommercial savings.To view details of the building stock (floor area, etc) and annual turnover, click on Stock by State.NB: Care should be taken not to change any of the values other than those specified in the Control Panel, Settings by Class (see below) and Greenhouse Factors (see below) tabs, or the Calculator model may not function correctly. Others tabs could be password-protected for the final Calculator if preferred.Detailed SettingsA range of detailed settings for each building class can be varied if required by the user. Settings specific to individual building types are found in the Settings by Class tab.For residential buildings, this tab allows the user to a) view a range of default settings used by the calculator, and b) change those settings by entering an alternative, preferred value in the corresponding light blue box. If any light blue box is empty, the (stated) default value applies. If an alternative value is entered, that alternative value over-rides the default. Note that, in this case, the alternative value will remain in place and affect Calculator results until it is removed or changed by the user. Note that the fuel mix values for each residential class by state/territory are shown for transparency and are not intended to be variables. That said, they could be changed, provided care is taken to ensure they sum to 100%. Also note that wood/solar shares have been set to zero a) as it is unlikely that wood will be a major fuel in the new housing stock (regardless of current fuel use patterns by state), and b) the effect of rising solar use is represented through the greenhouse gas intensity of electricity supply.The user may view default coefficient of performance (COP) values for electrical space heating in columns H - P that are assumed to be the average values (for new builds) that apply in each regulatory window. Note that the COP is the average of electrical space heating values for the dwelling, so where direct resistance heating is used (rarely), then this will reduce COP values that otherwise will reflect the choice of heat pumps installed. The default values are intended to be conservative but may be changed by the user entering alternative values in the adjacent light blue box, separately for each state and territory, if preferred. Note that the average COP of gas space conditioning equipment is shown in D49. This is not expected to change materially, but can be varied by the user if required. In column R, the default rate of change in average dwelling size (for each dwelling type and state and territory) can be viewed, and alternative values may be specified in the light blue boxes in column S. Note that the negative sign denotes a reduction in average dwelling size over time. Entering a positive value will indicate an increase in average dwelling size over time. In column T, the default rate of demolition and rebuild, and major refurbishment to current Code levels, is shown, and this value may be varied in the light blue boxes in column U. In column V, the user can vary the rate of stock growth for each building type and state/territory. To do this, choose a value from the drop down list. Note that the values shown (from -2% to +2% in half % point steps) apply to the default values that are shown in the Stock by State tab adjacent for each building. The default values are based on the historical averages calculated from ABS Census data to 2009 and ABS 32360DO001_20112036 Household and Family Projections, Australia, 2011 to 2036. Post 2036 projections are assumed to remain at the 2036 rate.Australian Bureau of Statistics 32360DO001_20112036 Household and Family Projections, Australia, 2011 to 2036 For commercial buildings, the Settings by Class tab (starting from Row 50) again shows the assumed fuel mix by state/territory, and then default values for the average rate of stock growth (column H), annual demolition and rebuild and major refurbishment to Code rate (column J), and the default values for total energy intensity of NCC2016 compliant reference buildings. As is set out in the Technical Notes below, these values do not represent 100% of the expected energy use of the relevant building forms, but only that portion of the energy use that is affected by the National Construction Code. This means that they provided a valid basis for comparison across regulatory windows, but may not be directly compared with existing buildings or NABERS ratings, for example. In each of these cases, the adjacent light blue boxes can be used to select alternative values if desired.In the Greenhouse Factors tab, the default values for greenhouse intensity of electricity supply may be viewed, while the rate of change in intensity over time by state/territory may be varied in the light blue boxes. Contact:Philip HarringtonPrincipal ConsultantStrategy. Policy. Research.ABN 38 615 039 864philip.harrington@.au0419 106 449.au ................
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