We have been the core developers of several TIMES models since the creation of this modelling platform. Most of these are actively supported by us.
TIAM (TIMES Integrated Assessment Model) is a detailed, technology-rich Global TIMES model. It is the outcome of global modeling work since 2001, by us and a few close collaborators. It started with the SAGE model that supported the International Energy Outlook of EIA for a few years. Supported the first ETP report of IEA in 2006. The 2009 version became the ETSAP TIAM model, which has been developed further by several ETSAP partners.
It is a multi-region partial equilibrium model of the energy systems of the entire World divided in sixteen regions. The regional modules are linked by trade variables of the main energy forms (coal, oil, gas) and of emission permits.
This model has participated in several Global EMF studies. Since 2016, we have used it with BP to look at long-term energy transition pathways in several World regions. It contributed to the BP Technology outlook 2018.
This started out as the Pan-European TIMES (PET), a multi-country model where the energy system of each country of the EU27, plus Iceland, Norway and Switzerland was represented separately, and linked to the others by the trade of energy commodities. It was initially developed within the European NEEDS project (New Energy Externalities Developments for Sustainability, a project funded by the 6th Framework Programme of the EU). It was enhanced by RES2020 in the representation of Renewable Energy Sources and Technologies.
It aims to analyse the role of energy technologies and their interaction for meeting European energy and climate change policy targets.
It produces projections (or scenarios) of the EU energy system showing its evolution up to 2060 under different sets of specific technology and policy assumptions and constraints.
The main role of JRC-EU-TIMES is the anticipation and evaluation of technology policy. The baseline scenario of JRC-EU-TIMES is always aligned to the latest EU reference scenario. The model can be used to assess which technological improvements are needed to make technologies competitive under various low-carbon energy scenarios.
The EPAUS9rT is a 9-region database representation of the U.S. energy system. The regional breakdown is based on the nine U.S. census divisions. The database was developed by EPA researchers for use with the TIMES model. TIMES is an energy system optimization model used by local and federal governments, national and international communities and academia. It helps decision makers understand the complex system interactions related to energy use. The Energy Technology Systems Analysis Programme (ETSAP) of the International Energy Agency oversees its development.
The EPAUS9rT is a fully transparent, publicly available database. The unique contribution of this database lies in its thorough representation of greenhouse gas (GHG) and air pollutant emissions. EPA researchers use the TIMES modeling platform to analyze the environmental impacts of potential changes in the way the U.S. produces and uses energy. The EPAUS9rT represents energy supply, technology, and demand throughout the major sectors of the U.S. energy system. The sectors include:
Energy resources represented in the database include:
renewable (e.g., wind, solar, biomass, geothermal, and hydropower).
The EPAUS9rT has a set of baseline assumptions developed characterizing U.S. energy supplies, demands, and technologies through the year 2050 in multi-year increments at the level of the nine U.S. Census Divisions.
FACETS is a highly detailed, technologically-realistic model of the US energy system, designed to address the analytical and communication challenges of the contemporary energy and environmental policy landscape. FACETS can integrate dozens of unconnected policies and projects undertaken at federal, regional and state levels in response to diverse energy, climate, and air quality policy goals. The energy, environmental, and economic impacts of these measures can be assessed in the context of technology, market, and policy uncertainties, allowing high priority actions that are robust to future uncertainties to be identified and explored.
Key features of the FACETS modeling approach are:
- Regional – FACETS captures the geographical relationships – such as those between renewable resources, electricity loads, and transmission capacity – that are key drivers of the costs of energy system change. It enables true state-level policy modeling within the context of regional and federal policies, and allows assessment of important regional differences in the impacts of federal policies.
- Technologically realistic – FACETS represents real energy technologies and the infrastructure that connects them. In the power sector, it models individual power plants and their dispatch, retrofit, and retirement options. Unlike many other powerful energy models, FACETS is transparent, easy to explain, and flexible enough to examine technology futures far from the current energy system. Multiple scenarios can be run and interpreted quickly and easily, to explore uncertainty about key variables, assess alternative policy variants, and design robust strategies.
- Integrative – FACETS can analyze the costs and benefits of policy and technology options over all sectors of the energy system – resources, electricity generation, transportation for people and freight, and industrial and building energy use. Diverse policies and measures can be combined and assessed simultaneously, rather than simply being added up, identifying potential synergies and offsetting effects between approaches. It captures all efficiency-supply interactions, and enables analyses of options that may simultaneously transform multiple sectors, such as widespread use of electric vehicles.
- Insight-driven – FACETS utilizes state of the art data handling, visualization, and geographic information systems (GIS) tools to draw insights from dozens of model runs, identify key relationships within the system, locate and address risks and opportunities, and support an iterative learning and policy development process.
A unique feature of this endeavor was that it contributed to the Scottish Climate Change Plan within a few months of being developed.