TIMES Model Generator
Overview
TIMES (The Integrated MARKAL-EFOM System) is a bottom-up optimization model generator for energy-environment systems analysis at various levels of spatial, temporal, and sectoral resolutions [#Loulou2016a; #Loulou2016]. The TIMES code, written in GAMS and available under an open-source license [#IEA-ETSAP2020a], is developed and maintained by the Energy Technology Systems Analysis Programme (ETSAP)[1] , a Technology Collaboration Programme (TCP) of the International Energy Agency (IEA), established in 1976. TIMES models can have single or several regions and typically are rich in technology detail, used for medium- to long-term energy system analysis and planning at a regional, national, or global scale.
Historical Development
TIMES represents the evolution of two pioneering energy system modeling frameworks:
MARKAL (MARKet ALlocation): Developed in the late 1970s, MARKAL was one of the first bottom-up energy system optimization models, focusing on technology-rich representations of energy systems.
EFOM (Energy Flow Optimization Model): A complementary approach that emphasized energy flow balances and sectoral detail.
The integration of these two methodologies into TIMES combined their respective strengths, creating a more flexible and comprehensive modeling framework that has become the global standard for national and regional energy system planning.
Core Principles
TIMES is a linear optimization, techno-economic, partial-equilibrium model generator that assumes perfectly competitive markets and perfect foresight. Model variants enable myopic foresight, general equilibrium, stochastic programming, and a variety of multi-objective function options. The standard objective function maximizes the net total surplus (the sum of producers’ and consumers’ surpluses), which, in a perfect market with perfect foresight, equates to maximizing the net present value (NPV) of the whole energy system, maximizing societal welfare. Profits, taxes, and subsidies are internal transfers, i.e., occurring within the economy, that do not change the NPV (albeit taxes and subsidies can be included to influence the optimization). It calculates the energy system specification that minimizes discounted total energy system costs over the model time horizon, which is the sum of investments, fixed and variable costs, fuel import costs, and export revenues for all the modeled processes, less potential salvage values of investments for which the whole lifetime goes beyond the model time horizon.
Key Characteristics of TIMES Models
Technology Explicit Representation:
TIMES models contain detailed characterizations of hundreds to thousands of individual technologies, each defined by:
Capital costs and operational expenditures
Technical efficiency and performance parameters
Capacity factors and availability constraints
Lifetime and build time specifications
Emission factors for multiple pollutants
Temporal Flexibility:
The framework supports flexible time resolution, allowing modelers to:
Define milestone years for long-term planning (typically 5-year intervals over 30-50 year horizons)
Specify intra-annual time slices to capture seasonal and diurnal variations in energy supply and demand
Model storage technologies and variable renewable energy integration
Multi-Regional Capabilities:
TIMES supports multi-regional modeling with:
Trade flows between regions for energy commodities
Region-specific resource availability and costs
Differentiated demand profiles and growth trajectories
Environmental Accounting:
Comprehensive tracking of environmental impacts including:
Greenhouse gas emissions (CO2, CH4, N2O, F-gases)
Air pollutants (SO2, NOx, particulate matter)
Water usage and land use requirements
Model Inputs
The user inputs the following to the model generator:
Reference Energy System (RES): The process-flow architecture of economic sectors and energy flows (commodity) between processes (technology), which consume and produce energy, energy service demands and/or other commodities such as environmental emissions (including greenhouse gasses) and other materials. The base-year energy flows are calibrated to national energy balances.
Energy service demands: The physical services required by the economy and society for mobility, heat, communications, food, etc., which drive energy demand.
Energy supply curves: The quantities of primary energy resources (e.g., wind power) or imported commodities (e.g., oil, gas, bio-energy) available at specific cost points for differing quality and quantity of energy commodities.
Techno-economic parameters of existing and potential future energy technologies: Economic parameters including current and projected future investment and fixed/variable costs and efficiencies of technologies for energy supply (e.g., solar PV panels, transmission and distribution infrastructure, biorefineries, hydrogen production) and energy demand (e.g., electric vehicles, natural gas boilers, carbon capture and storage); technological parameters including transformation efficiency, availability factor, capacity factor, and emissions factor.
User constraints: Any combination of linear constraints (including fixed, maximum, or minimum bounds on growth, investment, or shares) on technologies or fuels. These are typically used to simulate real-world technology constraints or policy scenarios. A typical user constraint for decarbonization analysis is limiting total annual or cumulative CO2 emissions to model energy system pathways that meet a national decarbonization target.
Model Outputs
TIMES outputs the optimal investment and operation level of all energy technologies that meet future energy service demands at the least cost, while respecting user constraints. The model also produces corresponding energy flows, emissions, and marginal prices of energy and emissions flows.
Key outputs include:
Technology capacity and activity: Optimal investment schedules and operational levels for all technologies
Energy commodity flows: Detailed flows of fuels, electricity, heat, and other energy carriers
Emissions trajectories: Time-series of GHG and pollutant emissions by sector and source
Marginal costs: Shadow prices for energy commodities, emissions constraints, and capacity limits
System costs: Total and annualized costs broken down by cost category and sector
TIMES-Ireland Model (TIM)
Introduction
The TIMES-Ireland Model (TIM) is a single-region national energy system model for Ireland, developed to support evidence-based energy and climate policy analysis. TIM is built using the TIMES framework and provides a comprehensive representation of Ireland’s energy system from primary resource extraction through to final energy service demands.
TIM serves as a critical tool for:
Informing Ireland’s Climate Action Plan and carbon budget allocations
Evaluating technology pathways for achieving net-zero emissions by 2050
Assessing the cost-effectiveness of different decarbonization strategies
Analyzing the role of emerging technologies such as hydrogen, carbon capture, and advanced biofuels
Supporting energy security and infrastructure planning decisions
Model Architecture
Simplified representation of reference energy system in TIM
Figure 1 illustrates a simplified Reference Energy System (RES) within the TIMES-Ireland Model (TIM). It delineates the structure and energy flows, encompassing two primary components:
Supply-side: Encompasses energy resources (domestic fossil fuels and renewables), fuel production and conversion technologies (biorefineries, hydrogen production, power plants), and transmission/distribution infrastructure (gas pipelines, power grid).
Demand-side: Covers end-use sectors (transport, residential, etc.) and their corresponding energy service demands (passenger transport, freight, hot water, etc.).
Energy resources, both domestic and imported, are processed and distributed across the country. End-use technologies consume these energy commodities to satisfy the energy service demands of various sectors. Greenhouse gas (GHG) emissions, arising from fossil fuel combustion and industrial processes, are meticulously tracked at the fuel supply, electricity generation, and sectoral consumption levels.
Sectoral Coverage
TIM provides detailed representation of the following sectors:
Supply Sectors:
Electricity generation (thermal, renewable, storage, interconnection)
Oil refining and distribution
Natural gas supply and distribution
Hydrogen production and delivery
Bioenergy production (biogas, biomethane, biofuels)
District heating
Demand Sectors:
Residential buildings (space heating, water heating, cooking, appliances, lighting)
Commercial and public services (similar end-uses as residential)
Industry (process heat, steam, mechanical drive)
Transport (passenger cars, buses, rail, freight, aviation, shipping)
Agriculture (machinery, heating, other energy uses)
Base Year Calibration
The model’s base year is 2018, with all energy flows, emissions, and energy technology stocks calibrated to the 2018 Irish energy balance [SEAI2019]. This calibration ensures that:
Total primary energy supply matches official statistics
Sectoral final energy consumption is accurately represented
Existing technology stock reflects installed capacities
Emissions inventory aligns with national GHG reporting
Time Horizon and Resolution
TIM typically models the period from 2018 to 2050 or 2070, with:
Milestone years: 1, 5, 10-year intervals (2020, 2025, 2030, etc.)
Intra-annual time slices: Representing seasonal and diurnal variations in energy supply and demand patterns
Technology vintages: Tracking investments by year of installation to model technology turnover
Economic Parameters
Discount Rate:
The discount rate, signifying the degree to which future values are discounted to the present, is a pivotal parameter in the TIMES objective function. A social discount rate reflects societal preferences regarding present versus future costs and benefits, typically lower than a financial discount rate used by firms for investment decisions. The Irish government employs a social discount rate of 4% in this model, aligned with the Social Rate of Time Preference methodology outlined in the Public Spending Code [O’Callaghan2018]. This rate is consistent with recommendations by Garcia-Gusano et al. (2016) for a maximum social discount rate of 4-5% in Energy System Optimization Models (ESOMs).
Technology-Specific Discount Rates:
Technology-specific discount rates, also known as hurdle rates, are often used in ESOMs to model investment decisions from the individual or industry perspective. They account for market imperfections, financial limitations, and behavioral factors that can hinder the adoption of novel or capital-intensive technologies. These parameters are not incorporated in the core TIM version, as it focuses on long-term energy system pathways from a societal viewpoint. However, model variants can be developed to simulate real-world policy and behavioral impacts, potentially including hurdle rates.
Currency and Cost Basis:
All costs in TIM are expressed in constant 2018 Euros, providing a consistent basis for comparing technologies and scenarios across the modeling horizon.
Key Model Features
Renewable Energy Integration:
TIM includes detailed modeling of Ireland’s substantial renewable energy potential, particularly:
Onshore and offshore wind resources with location-specific capacity factors
Solar PV potential accounting for Ireland’s irradiance patterns
Ocean energy (wave and tidal) technologies
Biomass and biogas resources with sustainability constraints
Electrification Pathways:
The model captures cross-sectoral electrification opportunities:
Electric vehicle adoption in transport
Heat pump deployment in buildings
Industrial electrification for low-temperature heat
Hydrogen Economy:
TIM represents emerging hydrogen technologies including:
Green hydrogen production via electrolysis
Blue hydrogen with carbon capture
Hydrogen storage and distribution infrastructure
End-use applications in transport, industry, and power generation
Carbon Management:
Comprehensive carbon accounting and mitigation options:
Carbon capture and storage (CCS) for power generation and industry
Bioenergy with CCS (BECCS) for negative emissions
Direct air capture technologies
Land use and forestry interactions (where applicable)
Policy Applications
TIM has been applied to support numerous policy analyses including:
Ireland’s Climate Action Plan development
Carbon budget allocation across sectors
Renewable electricity target setting
Building retrofit strategy assessment
Transport decarbonization pathway analysis
Industrial emissions reduction planning
Energy security and import dependency analysis