Sign In

Error
Error
Create an account

Create a free IEA account to download our reports or subcribe to a paid service.

Join for freeJoin for free

About the Global Energy and Climate Model

Overview

Since 1993, the IEA has provided medium- to long-term energy projections using a continually-evolving set of detailed, world-leading modelling tools. First, the World Energy Model (WEM) – a large-scale simulation model designed to replicate how energy markets function – was developed. A decade later, the Energy Technology Perspectives (ETP) model – a technology-rich bottom-up model – was developed, for use in parallel to the WEM. In 2021, the IEA adopted for the first time a new hybrid modelling approach relying on the strengths of both models to develop the world’s first comprehensive study of how to transition to an energy system at net zero CO2 emissions by 2050

Since then, the IEA has worked to develop a new integrated modelling framework: IEA’s Global Energy and Climate (GEC) Model. As of 2022, this model is the principle tool used to generate detailed sector-by-sector and region-by-region long-term scenarios across IEA's publications.  

The GEC Model brings together the modelling capabilities of the WEM and ETP models. The result is a large-scale bottom-up partial-optimisation modelling framework allowing for a unique set of analytical capacities in energy markets, technology trends, policy strategies and investments across the energy sector that would be critical to achieve climate goals. IEA’s GEC Model covers 26 regions individually that can be aggregated to world-level results and all sectors across the energy system with dedicated bottom-up modelling for: 

  • Final energy demand, covering industry, transport, buildings, agriculture and other non-energy use. This is driven by detailed modelling of energy service and material demand. 
  • Energy transformation, including electricity generation and heat production, refineries, the production of biofuels, hydrogen and hydrogen-derived fuels and other energy-related processes, as well as related transmission and distribution systems, storage and trade. 
  • Energy supply, including fossil fuels exploration, extraction and trade, and availability of renewable energy resources. 

Inputs to the model include: historical technology stock, cost and performance; energy statistics and balance data; policies and regulations; and socio-economic drivers. 

Outputs from the model include: projected technology stock, cost, and performance; energy flows by fuel; investment needs and costs; materials and critical minerals demand; CO2 and methane emissions. 

Prices, which are both inputs and outputs of the model, include: fuel, end-user and CO2 prices. 

Overview of IEA's Global Energy and Climate Model

4  Model Description Figure 1 Update

Developments in the 2022 modelling cycle

Sectoral and topic-specific developments this year, undertaken as part of the GEC Model development, include the following:  

  • End use sectors: the GEC Model combines the policy, market and behaviour analysis of the WEM tool with the technology-rich ETP model in an integrated framework. This combination allows for an improved representation of technologies and the impact of policies in energy trends across the end-use sectors industry, transport, buildings and agriculture. 
  • Electricity sector: the grid module has been significantly expanded to consider an increased granularity of line and cable types and an improved representation of transmission grid reinforcements and grid forming requirements in systems with high shares of renewables.  
  • Fossil fuel supply: the oil and gas supply: modules account this year for a wide range of financial risks (e.g. geopolitics, rule of law, regulatory oversight). This improves the representation of decisions made by companies looking to invest in oil and natural gas fields in different countries. 
  • Other transformation: the GEC Model fully integrates the cost-optimisation approach to model merchant hydrogen, hydrogen-based fuels and the required hydrogen infrastructure.  
  • New Critical minerals and Employment modules: the Critical Mineral and Employment modules have been fully integrated into the GEC Model, making it possible to regularly update projections based on latest policy and technology trends. 
  • Governments’ energy related spending: beyond Covid-19 recovery packages, the GEC Model 2022 includes data on government spending enacted for clean energy investment support, as well as for ensuring energy affordability for consumers, from March 2020 to September 2022. 
Methodology

The GEC Model is a bottom-up partial-optimisation model covering energy demand, energy transformation and energy supply. The model uses a partial equilibrium approach, integrating prices sensitivities. It shows the transformation of primary energy along energy supply chains to meet energy service demand, the final energy consumed by the end-user. The various supply, transformation and demand modules of the model are dynamically soft-linked: consumption of electricity, hydrogen and hydrogen-related fuels, biofuels, oil products, coal and natural gas in the end use sector model drives the transformation and supply modules, which in turn feed energy prices back to the demand module in an iterative process. In addition, energy system CO2, CH4 and N2O emissions are assessed. The model contains a number of additional analysis features evaluating further system implications such as investments, critical minerals, employment, temperature outcomes, land-use, and air pollution (see more details below). 

The main exogenous drivers of the scenarios are economic growth, demographics and technological developments. Energy service demand drivers, such as steel demand in industry or number of appliances within households, are estimated econometrically based on historical data and on the socioeconomic drivers. Interactions between energy service demand drivers are also accounted for, such as the influence of the number of vehicles sales on materials demand. This service demand is met by existing and new technologies. All sector modules base their projections on the existing stock of energy infrastructure (e.g. the number of vehicles in transport, production capacity in industry, floor space area in buildings), through detailed stock-accounting frameworks. To assess how the service demand is met in the various scenarios, the model includes a wide range of fuels and technologies (existing and additions). This includes careful accounting of the current energy performance of different technologies and processes, and potential to improve efficiency.  

The sectoral and cross-sectoral energy and emission balances are calculated based on the final energy end uses – the service demand – by determining first the final energy demand needed to serve it, then the required transformations to convert primary energy into the required fuels, and finally the primary energy needs. This is based on a partial equilibrium approach using for some elements a partial optimisation model, within which specific costs play an important role in determining the share of fuels and technologies to satisfy the energy service demand. In different parts of the model, Logit and Weibull functions are used to determine the share of technologies based upon their specific costs. This includes investment costs, operating and maintenance costs, fuel costs and in some cases costs for emitting CO2. In certain sectors, such as hydrogen production, specially designed and linked optimisation modules are used. 

While the model aims to identify an economical way for society to reach the desired scenario outcomes, the results do not necessarily reflect the least-cost way of doing so. This is because an unconstrained least-cost approach may fail to take account of all the issues that need to be considered in practice, such as political or individual preferences, feasible ramp-up rates, capital constraints and public acceptance. Instead, the analysis pursues a portfolio of fuels and technologies within a framework of cost minimisation, considering technical, economical and regulatory constraints. This approach, tailored to each sector and incorporating extensive expert consultation, enables the model to reflect as accurately as possible the realities of different sectors. It also offers a hedge against the real risks associated with the pathways: if one technology or fuel fails to fulfil its expected potential, it can more easily be compensated by another if its share in the overall energy mix is low.  

All fuels and technologies included in the model are either already commercially available or at a relatively advanced stage of development, so that they have at least reached a prototype size from which enough information about expected performance and costs at scale can be derived. Costs for new clean fuels and technologies are expected to fall over time and informed in many cases by learning curve approaches, helping to make a net zero future economically feasible. 

Besides this main feedback loop between supply and demand, there are also linkages between the transformation and supply modules. Further linkages between energy sectors are captured in the model, e.g. material flows or biogenic or atmospheric CO2 via Direct Air Capture for synthetic fuel production. Primary energy needs and availability interact with the supply module. Complete energy balances are compiled at a regional level and the CO2 emissions of each region are then calculated using derived CO2 factors, taking into account reductions from CO2 removal technologies. 

The GEC Model is implemented in the simulation software Vensim, but makes use of a wider range of software tools, including TIMES

Data inputs

The GEC Model is a data-intensive model covering the whole global energy system. Much of the data to calibrate to historical energy supply, transformation and demand, as well as energy prices, is obtained from the IEA’s own databases of energy and economic data. Additional data from a wide range of often sector-specific external sources is also used in particular to establish historic size and performance of energy-consuming stocks. 

The model is each year recalibrated to the latest available data. The formal base year is currently 2020, as this is the last year for which a complete picture of energy demand and production is in place. However, we have used more recent data wherever available, and we include 2021 and 2022 estimates for energy production and demand. Estimates are based on updates of the Global Energy Review reports which relies on a number of sources, including the latest monthly data submissions to the IEA’s Energy Data Centre, other statistical releases from national administrations, and recent market data from the IEA Market Report Series that cover coal, oil, natural gas, renewables and electricity. 

For a summary of selected key data inputs – including macro drivers such as population, economic developments and prices as well as techno-economic inputs such as fossil fuel resources or technology costs - please view the Global Energy and Climate Model key input dataset. 

Regional coverage and time horizon

The GEC Model covers the energy developments in the full global energy system up to 2050, with the capacity to extend beyond 2050 for some regions. Simulations are carried out on an annual basis. The current version of the model provides results for 26 regions of the globe, of which 12 are individual countries. Several supply components of the model have further regional disaggregation: the oil and gas supply model has 113 regions and the coal supply model 32 regions. 

A detailed view of IEA's Global Energy and Climate Model

4  Model Description Figure 2 Update
Capabilities and features

IEA’s GEC Model offers unparalleled scope and detail on the energy system. Its raison d'être is evaluating energy supply and demand, as well as the environmental impacts of energy use and the impacts of policy and technology developments on the energy system. Through long-term scenario analysis, the model enables analysis of possible futures related to the following main areas: 

  • Global and regional energy trends: this includes assessment of energy demand, supply availability and constraints, international trade and energy balances by sector and by fuel.   
  • Environmental impact of energy use: CO2 emissions from fuel combustion are derived from the projections of energy consumption. CO2 process emissions are calculated based on the production of industrial materials and CH4 and N2O emissions are assessed for final energy demand as well as for energy transformation. Methane from oil and gas operations are assessed through bottom-up estimates and direct emissions measurements (see Methane Tracker ). This makes it possible to publish the CO2-equivalend emissions for the entire energy sector. Local air pollutants are also estimated linking the GEC Model with the GAINS model of the International Institute for Applied Systems Analysis (IIASA) and the temperature outcomes of modelled scenarios are assessed.
  • Policy and technology developments: alternative scenarios analyse the impact of a range of policy actions and technological developments on energy demand, supply, trade, investments and emissions. 

Additionally, the GEC Model has multiple detailed features that either underlying or build from analysis of the broader energy trends. These include the following:  

  • Technologies: Detailed techno-economic characterisation of clean energy technologies under development (either at prototype or demonstration stage) including different applications in heavy industries, long distance transport and carbon dioxide removal technologies among more than 800 hundred technologies covered. 
  • People’s centred: Detailed modelling of behavioural changes, energy sector employment and energy affordability among other implications for citizens. 
  • Critical minerals: Comprehensive analysis of projected demand and supply of critical minerals for the energy sector’s transition. 
  • Infrastructure: Detailed modelling and analysis on enabling energy infrastructure development needs and strategies including: electricity systems, fossil fuels, hydrogen-related fuels distribution and CO2 transport options. 
  • Variable renewables potential: Detailed geospatial analysis of variable renewables potentials across the globe and modelling of their impact of exploiting those for hydrogen production.  
  • Modern energy access: Comprehensive modelling of the implications and opportunities to provide energy access to all communities. This includes access to electricity and clean cooking facilities, and an evaluation of additional energy demand, investments and CO2 emissions due to increased energy access.  
  • Material efficiency: Granular modelling of strategies along supply chains to make more efficient use of materials like steel, cement, aluminium, plastics and fertilisers, and their resulting impact on materials demand.   
  • Investments: Detailed modelling of overall energy sector and clean energy investments by sub-sector and technology areas, and comprehensive analysis on effective financing strategies. This includes investment requirements in fuel supply chains to satisfy projected energy demand and for demand-side technologies and measures (e.g. energy efficiency, electrification). Government spending is also tracked. 
  • Decomposition: Detailed mathematical framework to analyse systematically the specific contribution of different strategies to emissions or energy savings between scenarios and over time. 


Connections with the international energy modelling community

The development of the GEC Model benefits from expert review within the IEA and beyond and the IEA works closely with colleagues in the global modelling community. For example, the IEA participates in and regularly hosts the International Energy Workshop , and the analysis for the Net Zero Emissions by 2050 Scenario was informed by discussions with modelling teams from across the world, including from China, the United States, Japan, the United Kingdom, the European Union and the IPCC.   

The IEA also has a long-standing history of working with researchers and modellers around the world as part of its Technology Collaboration Programmes (TCP) network. The TCPs support the work of independent, international groups of experts that enable governments and industries from around the world to lead programmes and projects on a wide range of energy technologies and related issues. The Energy Technology Systems Analysis (ETSAP) TCP, established in 1977, is among the longest running TCPs. Its mission is to support policy makers in improving the evidence base underpinning energy and environmental policy decisions through energy systems modelling tools and capability through a unique network of nearly 200 energy modelling teams from approximately seventy countries. The ETSAP TCP develops, improves and makes available the TIMES energy systems modelling platform. 

IEA’s GEC Model also interacts closely with other internationally recognised models:  

  • The IEA uses the Model for the Assessment of Greenhouse Gas Induced Climate Change (MAGICC), developed and maintained by ClimateResource and often used by IPCC for key publications, to inform its analysis on the impact of different greenhouse gases budgets on the average global temperature rise. 
  • IEA modelling results are coupled with the Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS) model developed and maintained by International Institute for Applied Systems Analysis (IIASA). This allows for detailed analysis on the impact on air pollution of different IEA scenarios. 
  • IEA results are coupled with the Global Biosphere Management Model (GLOBIOM) developed and maintained by IIASA to complement IEA’s analysis on bioenergy supplies and effective use strategies.  
  • The Aviation Integrated Model (AIM) developed by University College London (UCL) forms the basis for our modelling of the aviation sector. 
  • IEA modelling results have been linked to the Global Integrated Monetary and Fiscal (GIMF) model of the International Monetary Fund (IMF) to assess the impacts of changes in investment and spending on global GDP. 
  • The Open Source Spatial Electrification Tool (OnSSET), a GIS-based optimisation tool developed out of a collaboration among several organisation, is used to inform the IEA’s energy access modelling.