Every model taught us something.
Every lesson became a tool.
Our journey runs from a single doctoral model of India in 1990 to free, ready-to-run models of nearly every country on earth. It looks like a list of models. It is really one long experiment: what happens to energy modeling when you keep raising the level at which people work with it?
The foundation
TIMES, and our place in it
TIMES — The Integrated MARKAL-EFOM System — is the energy systems optimization framework developed under the IEA's Energy Technology Systems Analysis Programme (ETSAP). It is the most widely used methodology of its kind: the analytical engine behind national energy plans, global decarbonization studies, and hundreds of published analyses across dozens of countries.
KanORS has been part of TIMES from the inside. We are among the co-developers of the framework, and we are the sole developers of Veda — the environment through which the global TIMES community builds and runs its models. This is the vantage point the rest of our story comes from: we did not adopt the state of the art; we helped build it. Everything that follows is what that work taught us.
Three decades, one experiment
Models and tools, co-evolving
- 1990
India MARKAL Model
The beginning — and the artisanal baselineDeveloped as doctoral work at IIM Ahmedabad, India's first comprehensive energy system model: energy security, emissions, and technology deployment for a fast-growing economy. Built with FoxPro and MUSS — one country, one researcher, years of work. Published in Energy and Environment Policies for a Sustainable Future and in early greenhouse-gas mitigation studies for India.
What it taught us: structured, data-driven planning works — but at this cost per model, it will never scale. - 1995–2000
Canadian Multi-Region MARKAL
Adding regional dimensions to national modelingThe first multi-region MARKAL model, built for Natural Resources Canada to explore Kyoto Protocol commitments through inter-provincial cooperation and energy trade — introducing region dimensions by manipulating MPS files directly, an innovation at the time.
What it taught us: the questions that matter cross borders — and the tooling, not the mathematics, is the binding constraint. - Early 2000s
SAGE — the first global MARKAL model
Built for the U.S. Energy Information AdministrationSAGE analyzed global energy systems and informed the EIA's International Energy Outlook from 2003 to 2007: comprehensive trade dynamics, regional interconnection, long-term projection at planetary scale.
What it taught us: global scale demands nimbleness in scenario handling — and it was here that Veda was born, first as a results tool, then growing into everything else. - 2005–2010
EFDA TIMES — the first global TIMES model
Fusion energy in global decarbonizationBuilt under the European Fusion Development Agreement to analyze fusion's role in long-term decarbonization, this project produced the first fully functional TIMES data-handling system — advanced input preparation and results analysis in one workflow. It became the foundation of the widely adopted TIAM model.
What it taught us: rigid region, time, and technology aggregations are where large models go to die. Maintainability is a design problem, not a housekeeping problem. - 2010–2015
JMRT · FACETS · PET
Expanding regional and sectoral reachJMRT modeled Japan's post-Fukushima choices — nuclear phase-outs and renewable integration. FACETS examined U.S. state-level policy and electrification, and introduced VedaViz for interactive, shareable results. PET, the Pan-European TIMES model, became the foundation of JRC-EU-TIMES.
What it taught us: stakeholders engage when they can see and touch results. Visualization isn't decoration; it's participation. - 2018–2020
AU-TIMES · IEMM
Scaling up, and the parameter-driven turnAU-TIMES explored renewable integration, the hydrogen economy, and decarbonization pathways for Australia — contributing to Decarbonisation Futures, AEMO system planning inputs, and the National Hydrogen Strategy. IEMM, our first fully parameter-driven model, covered global electricity markets and featured in the EIA's International Energy Outlook 2019.
What it taught us: when a model is generated from parameters instead of hand-assembled, building becomes systematic — and systematic means automatable. - 2020s
KiNESYS · Veda Online · VerveStacks
The lessons, compoundedEverything converged. The hard lessons of the global models — plus IEMM's systematic data processing — became KiNESYS, the platform that revolutionized creating and maintaining Veda-TIMES models, and put them directly in decision-makers' hands. Veda 2.0's data engine, carried to the cloud, became Veda Online — collaborative modeling in the browser. And the whole thirty-year stack, compressed into an automated pipeline, became VerveStacks: professional-grade models of 190+ countries, generated in minutes, free.
Where it leaves the field: what began as one country, one researcher, and years of work is now every country, any user, and an afternoon — or any builder, and a running start.
The arc, in one paragraph
The early global models taught us the cost of rigidity and the burden of maintenance. IEMM taught us that building can be systematic. Veda taught us that when you move mechanics into the machine, builders think at a higher level — and models become legible beyond their makers. KiNESYS and Veda Online carried that legibility to decision-makers and teams. VerveStacks carries it to everyone. Nimbleness and inclusivity are not our slogans; they are what thirty years of lessons, compounded, actually produce.