Short overview

The TIMES-GEO model is designed for detailed energy system optimization and analysis, relying on technology-rich, bottom-up approaches suitable for examining medium to long-term mitigation scenarios up to 2100. TIMES-GEO is built using the TIMES modelling framework, the widely used family of energy system models well-suited for medium to long-term energy planning analyses.

This model facilitates a structured exploration of energy systems options by mapping the interactions between various technological processes and energy commodities. Through a network known as the Reference Energy System (RES), the model systematically represents energy flows from primary sources to conversion, distribution, and consumption in different end-use sectors, encompassing the full spectrum of current and envisaged energy technologies and their demand implications. It is designed to understand and analyze the uptake and deployment of the most promising mitigation energy technologies and future energy mix, account for GHG emissions, and analyze different world decarbonization pathways.

The model includes over 6,000 technology/process options and more than 600 commodities. It is calibrated against 2018 open-access energy statistics from the Energy Statistics Database of the United Nations Statistics Division (UNSD) , and has been designed to run scenarios up to 2100.

The model's primary inputs include:

  • Techno-economic parameters: specifications of processes such as efficiency, utilization factors, lifetime, emissions, and the financial aspects of capital and operational expenses, alongside discount rates. The model provides a detailed account of regional energy systems, incorporating existing and future technologies across the entire energy value chain.
  • Price Projections: exogenous price projections of the main primary energy commodities including oil, natural gas and coal according to IEA World Energy Outlook estimates.
  • Demand Projections: exogenous demands of material and energy driven by exogenous variables like GDP growth, population dynamics provided at the sub-sectoral level.

The model can generate outputs concerning technological pathways, investment patterns, energy flows, commodity pricing and abatement cost, by adopting a least-cost approach, informing about optimal timing and regional effort sharing decisions. These outputs may comprise:

  • Consumption Patterns: analyzing energy use by commodity type, revealing insights into the mix and utilization of energy resources.
  • Future Technology mix: providing details about needed capacities and stocks to meet future energy demands at sectoral and sub-sectoral levels and for both supply and demand.
  • Future Costs: detailing the investment and operational costs associated with deploying energy technologies and system operations.
  • Emissions Data: quantifying carbon dioxide emissions to assess environmental impact.
  • Commodity Pricing: reflecting on the changing costs of energy and environmental commodities under various scenarios.

The model is able to examine a range of alternative energy pathways and scenarios, by playing with key drivers – such as demographic trends, economic performance, technological development - and policy frameworks. In the released version of the model, TIMES-GEO model uses the variant 2 of the Shared Socioeconomic Pathways developed by the International Institute for Applied Systems Analysis (IIASA) and the National Center for Atmospheric Research (NCAR). The flexibility of the TIMES-GEO enables users to model diverse scenarios, facilitating evidence-based decision-making in scientific, technological, and policy-making contexts and to evaluate the potential implications of different energy and environmental policies, guiding strategic planning towards net-zero energy futures.

The Global Energy Model (TIMES-GEO) is an open-source, global energy system model covering energy systems dynamics for 31 regions of which 16 countries and 15 regional aggregates. The model has been developed by University College Cork and E4SMA in the context of the CHIMERA project , and released publicly under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International Public License. The model finds the lowest-cost pathway to explore the evolution of the world’s energy system for electricity, transport, industry, buildings, energy-related agriculture, and novel fuels like hydrogen, e-fuels, and bioenergy to reduce emissions and meet mitigation targets.

Key features of the TIMES-GEO model

The key features of the TIMES-GEO model are the following:

Geographic coverage. The model represents the world with 31 region disaggregation, including 16 countries and 15 aggregations of countries.

Temporal scope. The time horizon of the model is 80 years, from 2020 to 2100. The year 2018 represents the base year. It offers flexibility in defining time periods, ranging from annual to extended 5-year and decade periods. Each period is divided into 20 time-slices including four seasons a year (winter, spring, summer, and fall), and 4 periods a day.

Full energy system. It covers seven energy sectors, divided into two supply side and five demand sectors. The supply side includes the upstream (UPS) and the power sector (PWR); the five-demand sectors include residential (RSD), services (SRV), industry (IND), transport (TRA) and energy-related agriculture (AGR), shown in figure 1. Each of these sectors is explicitly modelled and, in some cases, further divided into sub-sectors and end-uses.

Figure 1 - High-level reference energy system of the TIMES-GEO Model

Technology-rich model. The model describes the entire energy system with high technological detail (efficiency, investment and operational costs, utilization factor, discount rate) both for the base year and future mitigation options. Technology options include both currently available technologies and innovative technology options for potential future exploitation. The model describes each sector with extensive sets of technology options and level of detail. Some sectors, such as power, buildings (both residential and services) and transport are treated with a high level of detail. For example, the residential sectors comprise several decarbonization options for six different energy uses, such as thermal uses (space and water heating), air conditioning, cooking, electric appliances, lighting and others. Other sectors, such as industry and agriculture are treated with a lower detail, but still include several decarbonization options and details. For example, in industry, energy consumption is disaggregated into seven manufacturing subsectors: iron and steel, non-metallic minerals, chemicals, pulp and paper, wood products, non-ferrous metals and others. Each industrial subsector is further disaggregated through an energy service approach, where main energy service conversions such high-temperature heat (included steam) production, low temperature heat, machine drive and other services are represented.

Climate module & emissions granularity

The model tracks the main sources of greenhouse gases from both combustion and industrial processing in the energy sector, namely carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). These can be also reported as carbon dioxide equivalent emissions (CO2eq). The model currently does not include any climate module to estimate the impacts of emissions pathways in terms of temperature changes. However, a feature of TIMES called ‘Climate module’ can be enabled, expanding the capability of the model of capturing this aspect.

Socioeconomic dimensions

The TIMES-GEO model needs information about how much the need for energy, goods, and services, which lead to greenhouse gas (GHG) emissions, is expected to increase in various countries over the next several decades. Key drivers to the model are the socioeconomic projections such GDP, population growth and others.

TIMES-GEO model uses the Shared Socioeconomic Pathways adopted by IPCC developed by the International Institute for Applied Systems Analysis (IIASA) and the National Center for Atmospheric Research (NCAR) and. In particular the default version of TIMES GEO used variant 2 (SSP2) and its main assumptions include demographic, social and economic lifestyle development. These drivers are transformed into the different annual end-use demand projections, which are essential quantities that the TIMES-GEO model must produce an energy system to satisfy.

Each demand is estimated for each region and each sector, using the following general formula: Demand=〖Driver〗^Elasticity

For each demand, the most relevant drivers and appropriate hypothesis on demand elasticities of each sector and sub-sectors are selected.

Mitigation/adaptation measures and technologies

TIMES-GEO is an advanced, technology-intensive model encapsulating a broad spectrum of crucial fossil fuel and emerging mitigation technologies anticipated to be prevalent throughout the 21st century. This model provides insights and implications of transitioning from high-carbon to low-carbon technologies, contingent upon their respective cost dynamics, as well as emissions goals and policy mechanisms such carbon pricing, standards, etc. TIMES-GEO models the mitigation process via a comprehensive array of diverse measures, as presented in the dedicated table.

Economic rationale and model solution

The TIMES-GEO model computes a dynamic inter-temporal partial equilibrium for multi-regional energy and emission markets, focusing on maximizing total surplus, defined as the sum of surplus from suppliers and consumers. Operating within this analytical framework, the model ensures that the multi-regional system evolves in adherence to intra and inter-temporal partial economic equilibrium, consistently maintaining alignment with the technical possibility frontier. The resolution process of the model identifies the optimal mix of technologies, fuel choices, associated emissions, mining, trading activities, and the pricing and quantity of commodities. This process is delineated in a time series extending from the base year (2018) to the designated time horizon of the model (2100). Furthermore, the model achieves a partial equilibrium within the energy sector by externally setting end-user demands and providing a comprehensive depiction of the supply side, particularly in technology. Through simultaneous optimization across various end-use sectors, it guarantees that each sector operates within a consistent economic context, defined by uniform parameters such as Gross Domestic Product (GDP), fuel prices, and population figures. This approach facilitates a harmonized assessment of the energy sector, balancing the details of supply-side technologies with established demand parameters across all sectors.

Key parameters

The key parameters of the models are the following:

  • Techno-economic characterization of mitigation options. The main parameters are efficiency, specific energy consumption, investment and operational costs, utilization factor, discount rate.
  • Start period (base year) and model horizon: The start period is critical since all the calibration data are required for this year. The base year for the TIMES-GEO is 2018 while the scenario time horizon is until 2100. However, the time horizon of the model is adjustable so it can be extended/reduced to any year in the future, provided that all the necessary exogenous inputs are defined until that year (e.g. GDP projections, population projections etc.).
  • Period durations. TIMES-GEO solves the optimization problem of the energy system over several periods, and each period can extend over a variable number of years. The delivered model is set and tested to run scenarios for the following periods: 2018, 2021, 2025, 2030, 2035, 2040, 2045, 2050, 2060, 2070, 2080, 2090, 2100. The model is flexible, and the duration of the periods can be changed according to the modeller’s needs.
  • Time-slices: Time-slices are the time divisions within a year defined by the user (seasons, portions of the day/night, and/or weekdays/weekends). They are especially important whenever the mode and cost of production of a commodity at different times of the year are significantly different for example, in case of renewable energy generation. In the model, 20 time-slices are defined, as combination of 4 seasons and 5 daily time-blocks. This assumption can be customized.

Policy questions and SDGs

Key policies that can be addressed

As for all TIMES-based models, TIMES-GEO can include policies that affect either the entire energy system, sectors, group or single of technologies and commodities. The main policies that can be implemented in the model are carbon emission trajectories, carbon price at regional level or emission trading scheme; subsidies or grant customized for specific category of technologies (e.g. feed-in tariffs on renewable technology); targets on renewable share, phase-out from specific technologies or pathways, constraints on growth rate of specific technology. The current version of the model can account endogenously for emissions-related policies such as tax or other carbon dioxide pricing systems. The approach adopted in the model is the introduction of emissions constraints. In this case the model can calculate the marginal price to abate the last ton of GHG in the system. Thus, information can be used as a proxy for the needed carbon tax to reach a specific emission goal in the given time period. Emission Trading Schemes for Europe and other countries, with similar carbon pricing mechanisms have not been explicitly implemented in the current version but it can easily be included. The model is potentially able to implement emissions prices of different GHGs that can be linked together for a multi-gas policy.

Implications for other SDGs

The main output parameters produced by the model are related to the SDG 7 Affordable and clean energy. These are the amount of renewable energy use in the final energy sectors, the energy efficiency growth rate, future energy mix included biofuel and other low-emissions fuel consumption available for example for clean cooking.

The contribution to SDG 9 Innovation and Infrastructure is measured by quantifying low-carbon energy technology deployments, investments in new decarbonization options for the different end-use sectors, and energy system costs.

Concerning SDG 8 - Decent Work and economic growth, TIMES-GEO presents the costs of energy systems across various scenarios that can be expressed as GDP percentage that can be use for indicating economic losses attributed to mitigation efforts. However, the potential economic benefits arising from mitigation are not included in the model.

A link with SDG3 - Health consumption of fossil fuels in the residential and road transport sectors can serve as a foundation for estimating local air pollution.


The model was developed in the framework of project Chimera (Multi-model innovations in Integrated Assessment Modelling of Global, Chinese, and Irish energy-economy-environment-climate systems investigating deep decarbonisation pathways from the Paris Agreement to the United Nations sustainable development goals in 2018-2022 funded by the Science Foundation Ireland and National Science Foundation of China. At the moment no case studies have been applied to the model. A documentation paper is currently in preparation.

Reference to the project: https://www.marei.ie/project/chimera/

Reference to Github repository: https://github.com/MaREI-EPMG/TIMES-GEO

Reference to Zenodo: it will be added soon