Global buildings sector model
The buildings sector is modelled using a global simulation stock accounting framework, split into the residential and non-residential subsectors across 35 countries and regions (Figure A.5). The residential subsector includes all energy-using activities in apartments and houses, including space and water heating, cooling, ventilation, lighting, and the use of appliances and other electrical plug loads. The non-residential subsector includes activities related to trade, finance, real estate, public administration, health, food and lodging, education, and other commercial services. This is also commonly referred to as the commercial and public service sector. It covers energy used for space and water heating, cooling, ventilation, lighting, and a range of other miscellaneous energy-consuming equipment, such as commercial appliances, office equipment, cooking devices and medical equipment.
Figure A.5 - Structure of the buildings sector model
Key Point: Starting from socio-economic assumptions, the buildings sector model determines demand drivers and the related useful energy demands, which are then applied across building end uses and technology choices to calculate final energy consumption across the 35 model countries and regions.
For both subsectors, the model uses socio-economic drivers, such as population, GDP, income (approximated by gross national income [GNI] per capita), urbanisation and electrification rates, to project the major building energy demand drivers, including residential and non-residential floor area, number of households and residential appliance ownership. As far as possible, country statistics are used for historical energy balances by end use, floor area, appliance ownership rates and other building-related technical data and efficiency rates (e.g. technology stock and sales data). These data can be difficult to obtain across many developing countries, so in several cases the historical driver parameters for the ETP buildings sector model have been estimated using a series of applied logistic functions relative to GDP, GNI per capita, urbanisation and electrification, or another combination of proxies as defined by multilinear regressions. Those functions are applied to individual countries, or in cases where few data are available, to country clusters designed to be as homogeneous as possible within the cluster and as heterogeneous as possible between cluster categories. The functions differentiate the applied energy indicators by year to 2060 and across the 35 model countries and regions. The indicators are then applied within a stock accounting framework, which is distinguished by annual vintages, and the technology (or building stock) lifetimes are spread using a Weibull distribution.
Whenever possible, historical data and buildings sector information, such as building energy codes or minimum energy performance standards for end-use equipment, are applied within the model. Depending on the end use or technology, multiple categories are included (or estimated) within the model. For example, the global building stock is broken down into three categories, including near-zero energy buildings (nZEBs), code-compliant buildings, and buildings that do not meet code or do not have an applicable building energy code. Building end-use technologies (e.g. major household appliances) are similarly broken down into categories where applicable, such as best-in-class, median market performance and minimum energy performance technologies.
Using the annually differentiated stock accounting framework by country or region, historical useful energy intensity is estimated across the various building end uses based on assumed technology shares and efficiencies. Building stock characteristics (e.g. nZEB and code-compliant building energy intensity) are applied with heating and cooling equipment to estimate historical and then projected annual demand for space heating and cooling per unit of floor area (i.e. useful energy service delivered). The model also takes into account the ageing, refurbishment or reconstruction of buildings through degradation, improvement, renovation rates or specific lifetime distributions. For the other end uses (e.g. water heating, lighting, appliances and cooking), the useful energy demand is similarly estimated through a differentiated stock accounting framework to determine the useful (or delivered) energy service by end use. Across all end uses and countries/regions, useful energy demand can vary over time (e.g. relative to average GNI per capita growth), where some convergence (in useful energy service) is assumed across similar countries/regions, depending on the building energy technology and policy scenario.
For each of the derived useful energy demands, a suite of technology and fuel options are represented in the model, reflecting current techno-economic characteristics (e.g. efficiencies, costs and lifetimes) as well as their assumed evolution to 2060 in the applied ETP scenario. Depending on the current technology stock, as well as assumptions on the penetration and market share of new technologies in the future, the ETP buildings sector model allows exploration of strategies that meet the different useful energy demands and the quantification of the resulting developments by final energy consumption and related CO2 emissions. Detailed annual results from the model are also applied within a logarithmic mean Divisia index (LMDI) analysis, allowing in-depth tracking of changes in activity, technology and energy performance over time with respect to the various scenarios.